Prof Bruno Kieffer

Dr Antoine Loquet

Prof Philippe Dumas

Dr Human Rezaei

Prof Gonen

Keywords: complex systems, AR, NMR, amyloid, self-assembly, p-DOSY

of scientific research, but mainly, it summarizes three years of my life. Three years abroad,

Nouvelles approches en RMN et en biophysique pour l'étude de systèmes complexes, Application au domaine N-terminal du récepteur aux androgènes.

Novel approaches in NMR and biophysics for the study of complex systems, Application to the N-terminal domain of the Androgen Receptor.

Julia ASENCIO HERNANDEZ

Directeur de thèse, Marc-André DELSUC Mon sujet de thèse vise à développer de nouvelles méthodologies RMN (Résonance Magnétique Nucléaire) pour l'étude des systèmes complexes. Ce projet de thèse est une collaboration entre la société NMRTEC (Illkirch) et l'équipe de RMN biomoléculaire de l'IGBMC (Strasbourg).

Ce travail a été porté par la société NMRTEC, et réalisé dans le cadre du projet européen ITN-ReAd. Ce projet européen regroupe une dizaine de laboratoires, et deux entreprises, sur lťétude des systèmes chimiques complexes, tel que les systèmes autoréplicatifs, ou le développement de nouveaux senseurs. Dans ce consortium, le rôle de lťentreprise est de développer de nouvelles approches dťanalyse de ces systèmes.

Dans ce cadre, mon projet vise à réaliser une étude approfondie sur le développement de méthodologies pour l'analyse de mélanges complexes. Cela peut comprendre l'étude des grandes bibliothèques chimiques, des systèmes auto-assemblage, les interactions ligand-protéine et les systèmes biologiques désordonnés. Les méthodes développées recouvrent principalement la RMN (1D, 2D, et multinucléaire), la mesure de diffusion par RMN (DOSY) mais également d'autres techniques telles que la spectrométrie de masse, le dichroïsme circulaire (CD), la microscopie électronique (EM) et diffusion des rayons X aux petits angles (SAXS).

Ainsi, pour mener à bien cette étude, nous avons commencé à explorer les expériences de RMN pour l'étude des systèmes hors d'équilibre. La spectroscopie RMN est un bon outil pour la surveillance des réactions chimiques in situ. En particulier, la mesure DOSY est bien adaptée pour caractériser les espèces transitoires par la détermination de leurs tailles. Cependant, nous rencontrons une difficulté dans les expériences DOSY effectuées sur des systèmes hors d'équilibre. Dans ces systèmes, l'évolution de la concentration des espèces interfère avec le processus de mesure, et crée un biais sur la détermination du coefficient de diffusion qui peut conduire à des interprétations erronées. Nous montrons qu'une permutation aléatoire des intensités des gradients utilisés pendant l'expérience DOSY permet d'éliminer ce biais (Figure 1 Dans une deuxième partie de ma thèse, la partie N-terminale du récepteur des androgènes (AR) est utilisée comme un système complexe. D'après la littérature, il est connu que cette région joue un rôle important pour l'activité du récepteur, et elle est également décrite comme étant intrinsèquement désordonnée. De ce fait, la technique de spectroscopie RMN est la seule méthode spectroscopique pour appréhender ce domaine au niveau structural. Les résultats que j'ai acquis durant la thèse m'ont permis d'identifier une petite région de ce domaine, impliquée dans la formation réversible de fibres amyloïdes, par modulation des conditions d'oxydo-réduction du milieu.

L'auto-assemblage est un processus spontané par lequel des molécules s'organisent en structures pluri-moléculaires ordonnées. L'une des structures couramment présentées par des peptides et des protéines est la formation de fibrilles connues comme de fibres amyloïdes. Ces fibres peuvent spontanément s'agréger et produire des dépôts dans les tissus, et sont alors impliquées dans différentes pathologies dégénératives, tel que Alzheimer et Parkinson. Dans le domaine N-terminal de AR (NTD-AR), il existe une séquence primaire, unique à cette protéine dans l'ensemble du génome humain et qui est parfaitement conservée chez tous les vertébrés (Figure 3). L'originalité des résultats révèle un aspect inconnu du mécanisme de AR et nous permet d'expliquer l'observation de structures amyloïdes dans des biopsies de vésicules séminales, déjà décrite dans la littérature. L'étude du lien fonctionnel entre le stress oxydatif et l'activité de régulation de la transcription du récepteur des androgènes pourrait ouvrir des perspectives inédites pour le traitement du cancer de la prostate.

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En raison de la nouveauté du système, une étude plus approfondie est nécessaire pour améliorer la compréhension de son role dans le mécanisme d'activité de AR.

De nos jours, dans la literature le domaine N-terminal du récepteur des androgènes est présenté comme un potentiel cible pour le développement de nouveaux médicaments pour le cancer de la prostate, particulièrement lorsque le cancer de la prostate resistant à la castration (CRPC) apparaît et la sensibilité à la thérapie anti-androgène est perdue.

Dans les dernières années de nouvelles études ont été publiées, en présentant la molécule EPI-001 (Figure 6) et certains dérivés, comme un nouveau médicament pour la régression du cancer de la prostate [Andersen 2010, McEwan 2011]. Ces molécules sont un dérivé de l'un des perturbateurs endocriniens le plus connu, le Bisphénol A (BPA) (Figure 6). Récemment, d'autres nouvelles molécules ont fait leur apparition dans la littérature [Bañuelos 2014].

Pour toutes ces raisons, la stratégie est de montrer que les fibres amyloïdes, formées lors de l'oxydation du peptide provenant du NTD-AR, peut être un site cible pour toutes ces nouvelles molécules. En outre, les fibres analysées dans cet travail pourraient présenter un rôle biologique, pour cette raison, des hormones impliquées dans l'activité Ici, nous avons montré que les dérivés de BPA famille de petites molécules accélère la cinétique de l'agrégation de fibres amyloïdes. En outre, le BPA a été rapporté dans la littérature pour accélérer la formation d'amyloïde toxique [Gong 2013]. Ce résultat va dans le même sens que dans l'étude présentée ici et peut ouvrir de nouvelles voies de recherche pour contrôler l'agrégation amyloïde.

Enfin, l'interaction de EPI-001 au sein de la NTD-AR, est prouvée sur le cadre de cette étude. Une interaction covalente est caractérisée par HPLC/MS, liaison covalente formé par la Cys du peptide et le EPI-001. Tout ensemble, il a été démontré dans cet étude que, séquence hautement conservée de NTD-AR non seulement s'aggrège sous forme de fibres amyloïdes dans des conditions oxydantes, mais pourrait aussi être un site cible potentiel pour de nouveaux médicaments.

Jusqu'à ce point, dans la thèse, nous avons mis l'accent dans les systèmes complexes d'un point de vue biologique. Mais, les systèmes complexes sont présents tout autour de nous. Au sein de ces grands systèmes avec multiples composantes, où de nombreuses parties interagissent de manière non-linéaire et les interactions faibles entre leurs parties sont cruciales pour le développement et l'émergence de nouvelles propriétés. Dans cette Chapter 1

Complex Systems

Complex Systems and their features

Complex systems exist all around us, from chemical mixtures to galaxy dynamics, from metabolic pathways to eco-systems, from stock markets to social network. All these systems share in common a few typical characteristics that are the topic of the new science of complex systems, and have been intensively scrutinized.

The most commonly put forward feature for complex systems, is emergence. Emergence describes the occurrence in a system, of a new property or behavior which can not be extrapolated from the characteristic of the many simple elements which compose the system.

Emergence of planets from the interstellar gas, emergence of the organism from the genome, emergence of bubbles (or crashes) from financial market rules, are few examples.

Emergence is the most striking characteristic, however it is based on a series of fundamental properties that are found in many complex systems [Barabasi 1999].

Emergence is by definition related to the fact that "the whole is more than the sum of its parts", which is in other words, the fact that complex systems do not satisfy the superposition principle. This is intrinsically related to the nonlinearity of the interactions taking place in the system.

Chapter 1. Complex Systems

A large multiple-component system, with many parts interacting in a non-linear manner, displays a complex dynamic behavior, with the absence of long term coherence, but rather pseudo cyclic features -named attractors -local (in time or in space). This property is usually described as chaotic.

The chaotic dynamic of the system, which may evolves in one direction or another depending on small variations of the initial conditions, leads to the impossibility to predict the long term behavior of the system [Stavrinides 2013]. This creates a non-proportionality of the cause and on its effect, creates a non predictability of the system, even though each elementary dynamic step in the system is acting in a purely deterministic manner [Crutchfield 2011].

The classical example of a chaotic non-predictable system is the weather variation developing in the earth atmosphere.

Of course, this implies that the system is in an out-of-equilibrium state. In these conditions, higher structures may even appear. These dissipative structures display generally a multi-scale aspect, with the shorter scales (in space or in time) dominated by the simple inter-part interactions, while larger scale organized structures, unrelated to the formers, may appear [Sales-Pardo 2007].

The development of such systems is also dependent on weak interactions between the parts. Strong interactions usually reduce the number of possible degrees of freedom, and do not allow the development of complex behaviors.

All these characteristics, if present in a system, lead to complex behaviors, with the possibility of the emergence of larger structures, depending in a complex and fully non-linear manner on the external conditions, leading to some adaptation capabilities of the system.

Science in general, as a human activity, and Biology in particular is all about how, from the interaction of the molecules and atoms, new structures may emerge, leading to life, to organism interaction, to consciousness, to social interactions, and finally to activities such as the process of writing a thesis on complex systems in biology [Barroso 2015].

Molecular Complex systems

Molecular complex systems start with a simple atom bond formation. Complexity comes from the basis of chemical arrangement to form molecules, these molecules can assemble into macromolecules with a function in biological organisms [Ross 2009]. This exemplifies the concept of emergence, going from chemistry to life by placing complex interactions within bionetworks or bioassemblies.

The characterization of complex systems covers most scientific disciplines [Liu 2011], al-though the quantitative description of a complex system is intrinsically limited by the experimental accessibility. Weak interactions, including van der Waals force, H-bonding and ⇡ electron interactions, play an important role in many elemental processes in chemistry, physics, materials science and biology. Despite the fact that the energies of weak interactions are lower than ionic interactions or covalent bonds, their cumulative effect can be more relevant. The presence of these weak interactions together with the dynamics of complex systems, imply the presence of out-of-equilibrium systems. The out-of-equilibrium systems arise as objects of study in different contexts such as interacting particle systems, reaction-diffusion processes, on slow dynamics conditions and the possibility of undergoing phase transitions. This dynamics leads complex systems to be highly sensitive to initial conditions with not proportionality between cause and effect. Small perturbations in initial conditions derivate in a widely number of diverging outcomes, leading a none predictable situation [Crutchfield 2011], as nucleation.

Nucleation is the first step in the formation of either a new structure or phase, via self-assembly or self-organization. This process will occur on a different ways for identical systems, resulting a stochastic process. The nonlinearity can be exemplified by allostery, the process by which biological macromolecules when they bind at one site, the effect is transferred to a different active site. This phenomenon has been associated to the intrinsically disordered proteins (IDPs), a challenge to the structure-function paradigm [Motlagh 2014].

From a molecular point of view, the study of complex systems in chemistry has changed in the last years due to the development of analytical tools and the changes in research of molecular networks. The concept of complex systems in chemistry is related to the concept of Supramolecular chemistry. Introduced by Jean-Marie Lehn [Lehn 1993], this concept aims to develop chemical systems with highly complexity from components that interact via weak intermolecular forces. The principal exponents of these areas are self-replicating systems (kinetically controlled) and dynamic combinatorial libraries, that represent thermodynamically controlled systems. A molecule in a dynamic combinatorial library can bind and copy itself, this situation may lead to self-assembly into nanoscale structure [Carnall 2010]. Within this topic, the peptides self-assembly and self-replicating systems have been used to understand the organizational principles of biological systems with a final aim of understanding the origin of life [Rubinov 2009]. Also self-assembled nanomaterials can be built based on aromatic peptide amphiphiles [Abul-Haija 2013] for developing of cell-instructive biomaterials.

Contrary to what happens in Chemistry, historically, the study of complex systems has been better stablished in Biology. The hierarchy of complexity levels of organization in proteins and the consequence in its function, exemplifies perfectly the concept of complex system in Biology.

The presence of nonlinearity related to small modifications or differences in its primary structure can conclude in an allosteric effect, or functionality disruption. Nevertheless the absence of the structure also plays an important role in the complexity network of biology.

As said above, complex systems include a wide range of different topics, research approaches, complex molecular networks and different molecular self-organization. Within this huge range of possibilities, it exists some key concepts that require a special mention and they will be the main actors in this thesis research.

Self-assembly

Self-assembly is a key concept in complex systems, specially in supramolecular chemistry, but also in biology. Self-assembly is a process in which a disordered system spontaneously organizes itself into an ordered structured system or pattern, as a consequence of specific local interactions without external contributions. The nanostructure builds itself.

Self-assembly from a chemist point of view implies order and weak interactions. From the point of view of biology, molecular self-assembly refers mainly to intermolecular self-assembly, while folding refers the intramolecular analog.

Molecular self-assembly underlies the construction of biologic macromolecular assemblies in living organisms, and so is crucial to the function of cells. It is exhibited in the selfassembly of lipids to form the membrane, the formation of double helical DNA through hydrogen bonding of the individual strands, and the assembly of proteins to form quaternary structures.

Molecular self-assembly of incorrectly folded proteins into insoluble amyloid fibers is responsible for infectious prion-related neurodegenerative diseases [Noinville 2008].

Proteins structures

Complexity, organization and function are concepts that form part of the definition of protein.

Proteins are commonly described in terms of four hierarchical levels of organization. Proteins are biological molecules or macromolecules, formed by atoms, atoms that are organized into amino acid residues. These 20 different amino acids, act as monomeric building blocks of proteins and covalent bound in a polypeptide chain. This organization represents the primary structure of a protein.

In a next level, the polypeptide chains can adopt different spatial arrangements, secondary structure. This secondary structure, without any stabilizing interaction, displays a random coil organization. However, when the stabilization appears as hydrogen bonds between certain residues, different secondary structures can be adopted, as ↵-helix or -sheet. These structures were suggested, before any experimental evidence, in 1951 by Linus Pauling and coworkers

Chapter 1. Complex Systems [Pauling 1951a, Pauling 1951b]. Apart from these, there are also other secondary structure such as 3 10 -helix, ⇡-helix, polyproline-helix, ↵-sheet and -turn.

Tertiary structure refers to the three-dimensional structure of a protein, and to its geometric shape, the three-dimensional arrangement of all the amino acids residues. In contrast to secondary structure, which is stabilized by hydrogen bonds, tertiary structure is stabilized by hydrophobic interactions between the nonpolar side chains and, in some proteins, by disulfide bonds. Leading an hydrophobic core and an hydrophilic surface that are the driving forces of the tertiary structure, as hydrogen bounds for the secondary structure and chemical bounds for the primary structure.

Finally, multimeric proteins present a quaternary structure. It is the three-dimensional structure of a multi-subunit protein and the way that the subunits fit together. In this context, the quaternary structure is stabilized by the same non-covalent interactions and disulfide bonds as the tertiary structure.

In a similar manner to the hierarchy of structures that make up a protein, proteins them- [Piana 2008[START_REF] Davies | Consequences of poly-glutamine repeat length for the conformation and folding of the androgen receptor amino-terminal domain[END_REF], protein expression, protein function and protein-protein interactions [Luscombe 2002, Lapouge 2008]. Mutations in proteins have a major role in the onset and development of cancer [Brooke 2009, Papa 2014], their special role is determined by the diversity of their impact on molecular function, in a multi-scale manner.

Intrinsically Disordered Proteins (IDPs)

Within the family of proteins, there is a class that does not present a tertiary structure named Intrinsically Disordered Proteins (IDPs). IDPs have been overlooked for many years, however a third of the proteins in higher eukaryotes is expected to be disordered. The lack of three dimensional structure together with their plasticity makes them to play a crucial role in cell signaling and regulation [Myers 2013]. Furthermore, a high percentage of oncoprotein contain intrinsically disordered regions.

Intrinsic disorder is common in proteins associated with many human genetic diseases and its role in many different pathologies make them important target for the research and development of new therapies [Marasco 2015, Guharoy 2015].

Chapter 1. Complex Systems

The absence of structure of the IDP makes particularly difficult the understanding of the relationship between the different transient folding that they can adopt and their function [Fuxreiter 2014], and new methodological development have to be made. Decoding the hot spots in their sequence to find and to analyze them, is crucial for this proposal. Approaches such as a phylogenic analysis to find non expected conserved regions, and other bioinformatic analysis are essential to map possible binding sites.

The study of IDPs requires to work in solution state, the lack of structure makes impossible the use of X-ray crystallography and difficult the use of electron microscopy (EM). Nowadays, Nuclear Magnetic Resonance (NMR) is the best technique to study and analyze these interactions, as well as Small Angle X-ray scattering (SAXS), interesting not at atomic level, but giving shape information and changes in conformation up to binding.

Amyloids

Many of the well-known neurodegenerative diseases are related to protein missfolding. These disorders arise from the failure of a protein to adopt its native functional state. As consequences of miss-folding, protein aggregates into fibers, which leads to loss of function and increase its toxic function. There are proteins that present an intrinsic tendency to assume a pathologic conformation, this conformation becomes evident with high concentrations or aging. Paradoxically, for structured proteins the first step in fibrillation is the partial unfolding whereas for IDPs is their partial folding.

Many neurodegenerative diseases are amyloidoses. The term Amyloid defines the deposition of insoluble protein aggregates, associated with different diseases as Alzheimer's disease, Parkinson's disease, Huntington's disease, also non-degenerative diseases as type II diabetes and prion diseases as Creutzfeldt-Jakob Disease (CJD) [Sipe 2000, Knowles 2014]. These protein aggregates share a specific structural traits, they are composed of a -sheet structure in a characteristic croos-conformation [START_REF] Geddes | Cross-" conformation in proteins[END_REF]], although they have different primary structures [Pastor 2008]. Amyloid formation is a complex process that takes place through several intermediates of various size and morphologies.

Historically, the term amyloid has been strictly used to describe the extracellular deposition of proteins fibrils [START_REF] Westermark | Aspects on human amyloid forms and their fibril polypeptides[END_REF]] with a characteristic pattern under the electronic microscope (linear and unbranched), a X-ray diffraction pattern of -strands and -sheets and with an affinity for Congo red with concomitant green birefringence. But in many cases aggregates accumulate intracellularly forming similar amyloid structures, that are called amyloidlike [Li 2009]. However, the term Amyloid is common used in the scientific literature, expanding the definition to include any aggregates of proteins, as well as synthetic peptides, that possess

Chapter 1. Complex Systems some but not necessarily all of the above characteristics [START_REF] Westermark | Aspects on human amyloid forms and their fibril polypeptides[END_REF]].

Generally, the proteins associated with amyloid diseases used to be classified into two groups, globular proteins and natively unfolded proteins [Li 2009]. An example of the first group, is the prion protein family, on which amyloid formation requires a partial unfolding step, forming non stable oligomers-intermediates that after self-assembly into -sheet aggregates.

The other group, that includes amyloid -protein (A ), tau and ↵-synuclein, maybe the three best known proteins related with amyloid-diseases.

Initially, the toxic species were believed to be the fibrils deposition in tissue, responsible for cell death, but nowadays there are new evidences indicating that the intermediate oligomers,

are the cytotoxic species on the amyloid pathway [Kayed 2003, Simoneau 2007].

To characterize and to study the formation and structural attributes of the amyloid fibrils, regarding their assembly state, we can use different biophysical methods and techniques. For the atomic structure, using solution-state NMR for the monomeric or oligomeric state, or solidstate NMR or X-ray for the fibril state. To study the secondary structure, the most common technique used is Circular dichroism (CD).

Novel approaches for the biophysics study of complex systems

The aim of this thesis is to develop novel approaches in Nuclear Magnetic resonance (NMR)

and biophysics for the study of complex systems. Within this topic, this thesis aims to conduct a study on the development of methodologies for the analysis of complex mixtures. This can include the study of large chemical libraries, self-assembly systems, protein-ligand complex interactions and disordered biological systems. The best methods for this purpose are NMR, the diffusion measurement by NMR (DOSY) but also other techniques such as mass spectrometry, circular dichroism (CD), electron microscopy (EM) and small angle X-ray scattering (SAXS).

In order to achieve this objective, a first part of the thesis will be focused in the technique development, specifically on NMR. With the purpose, a complex system has to be set as object of study. The study of out-of-equilibrium systems is a good example of complexity.

NMR spectroscopy is a good tool for monitoring chemical reactions. In particular, the DOSY experiment is well suited to characterize transient species and to separate them by the differences in diffusion coefficient. However, in these systems, the evolution of the concentration of different species in solution, interferes with the measurement process, and creates a bias in the determination of the diffusion coefficient which can lead to misinterpretation. We try to solve this difficulty by introducing a new experiment named p-DOSY.

In the second part of my thesis, the N-terminal domain of the Androgen Receptor (AR) is studied as a complex system. The Androgen Receptor belong to the superfamily of Nuclear Receptors (NRs). Human genome encodes 48 different nuclear receptors. NRs are a good example of the non-linearity in biology, only 48 different proteins are in charge of the control of the all human gene expression. Furthermore, these nuclear receptors share a common structure with high degree of conservation in some domains among the phylogenetic organisms.

According to the literature, the N-terminal domain of the receptor plays an important role in the receptor activity, and is also described as being intrinsically disordered. This characteristic makes NMR the best technique to study it at the structural level. As said above, an IDP can assemble into amyloid aggregates. This phenomenon of fibers formation, will be shown within this work, can be regulated with a redox control of the environmental conditions. In addition, aggregation is reversible by the addition of a reducing agent. The discovery of this property opens up new possibilities in terms of supramolecular organization and self-assembly and could be generalized to other systems. The originality of the results reveals an unknown aspect of the receptor mechanism. And this region could be consider as a target site for drug development and allosteric regulation, if it could be demonstrate that it plays an important role for the receptor activity.

In addition, the presence of amyloid fibers can be used as a target site for weak interactions.

The interaction with small molecules can disturb is kinetics aggregation, these weak interactions could cause the inhibition of the fibers formation and furthermore be used as amyloid inhibiting therapies for different amyloid diseases. On the other hand, they can cause the opposite effect and to accelerate the fibril formation.

As a result, a complete study of different examples of complex systems is carried out. This project covers many different aspects, from technical characterization of complexity to complex biological mechanisms.

Chapter 2

Androgen Receptor and its role in Prostate Cancer The superfamily is sub-divided into different classes. A first class is the thyroid/retinoid family, including the thyroid receptor (TR), vitamin D receptor (VDR), the retinoic acid receptor (RAR) and the peroxisome proliferator-activated receptor (PPAR). A second class defined as retinoid X receptor family, with the retinoid X receptor (RXR) or the testicular receptor (TR2-4). A third class is the steroid receptor family, including the estrogen receptor (ER), the progesterone receptor (PR), the androgen receptor (AR), the glucocorticoid receptor (GR)

and the mineralocorticoid receptor (MR). Finally, a last class of nuclear receptor is known as the orphan receptor family, including a set of proteins sharing significant sequence homology to other known nuclear receptors but with unknowns ligands.

Chapter 2. Androgen Receptor and its role in Prostate Cancer

Androgen Receptor

The androgen receptor (AR) belongs to the steroid hormone group of nuclear receptors, (NR3C4, subfamily 3, group c and gene 4). AR is located in the X chromosome, in the region q11-12 [Migeon 1981]. The AR gene presents 8 exons that encodes a 110kDa protein consisting of 919 amino acids and occurs as a single form in mammalian cells. The exon 1 encodes the NTD, the DBD is encoded by the exon 2 and 3 that also encode respectively the zing finger allowing the DNA recognition and the zing finger used as dimerization interface.

The exons from 4 to 8, encode the hinge and the LBD [Gelmann 2002].

The Androgen Receptor is a ligand-dependent transcription factor. AR is activated by binding of the androgenic hormones, 5↵-dihydrotestosterone (DHT) or testosterone. Upon activation, AR is translocated into the nucleus, where it recognizes specific DNA sequences and regulates genes expression [van de Wijngaart 2011]. However, AR is also responsible for the initiation of male sexual differentiation, and to the development and maintenance of male reproductive tissues [Li 2009, Matsumoto 2013].

AR presents the architecture in 5 domains common to all Nuclear Receptor: a disordered N-terminal region (NTD), which presents the intrinsic activation function (AF-1), a DNAbinding domain (DBD) followed by a short hinge region, a ligand-binding domain (LBD) which presents the ligand dependent activation function (AF-2), and finally a short C-terminal region.

The N-terminal domain AR has the peculiarity of presenting a very large NTD (Figure 2.1) that represents more than half of the entire protein, around 60% of the AR size (residues 1-555). This region contains the major transactivation function 1 (AF1), which contains transactivation units Tau-1 and Tau-5 (see Figure 2.1) important for AR transactivation. Deletion of the Ligand Binding Domain results in a constitutively active AR, implying that AF1 contributes all the activity of the receptor [Bevan 1999]. AF1 appears to be the predominant activation region in AR and depends on androgen binding for activation [Simental 1991].

The NTD-AR contains an FxxLF motif (x is any amino acid) that has been described to have an important role for interactions with the LBD [He 2000]. This represents a key interaction for receptor function, stabilizing bound hormone [He 1999] and behaving as competitor for AF2

surface with certain co-regulators, providing an alternative mechanism for AR transcriptional activity [He 2002, Li 2009]. Furthermore, the FQNLF motif in the AR N-terminal domain is also involved in the receptor dimerization [van Royen 2012].

This NTD of AR is a flexible domain with a high degree of intrinsic disorder characteristics of The AR polyQ track length has been used as a marker in human population genetics and is involved in the conformation and folding of the androgen receptor amino-terminal domain [START_REF] Davies | Consequences of poly-glutamine repeat length for the conformation and folding of the androgen receptor amino-terminal domain[END_REF]]. The presence of a repeat track polyQ with a length of more than 40 glutamine residues results in Kennedy's disease or adult onset spinal bulbar muscular atrophy [La Spada 1991, Tan 2014]. And a shorter polyQ repeat length (less than 21 glutamine residues) increases the risk of prostate cancer [Zhou 1994]. The AR polyQ length does not present the same conservation among the mammals (see Figure 2.1). Contrary to the human sequence, many species present a short glutamine repeat in the same position than the Human Chapter 2. Androgen Receptor and its role in Prostate Cancer polyQ, but remarkably, they present a glutamine repeat expansion slightly further where is located the human Q5 (see Figure 2.1) [Tan 1988[START_REF] Tan | The rat androgen receptor: primary structure, autoregulation of its messenger ribonucleic acid, and immunocytochemical localization of the receptor protein[END_REF].

The limited structure of the NTD-AR is thought to require interactions with other proteins to assume correct folding for further protein-protein interactions including interactions with bridging factors such as CBP and the basal transcriptional machinery for active transcription. and each monomeric form is composed of two zinc fingers, each zinc ion being coordinated to four cysteine residues [Shaffer 2004](PDB:1R4I). This domain is highly structured, compact and globular, composed by two perpendicular ↵-helix stabilized by the 2 zinc-fingers, a short -sheet is also present as well as some residues without secondary structure [Pawlak 2012].

The first ↵-helix of the N-terminal zinc finger, interacts directly with the DNA major groove, nucleotides from the hormone response element.

The proximal box (P-box) is a short motif, CxxCK, located in the first zinc finger, responsible for the DNA specific binding. The helix in C-terminal contributes to the stabilization of the whole complex by establishing a weak non-specific binding to DNA. Additional residues at the second zinc finger forming the D box are involved in receptor dimerization and also contribute to the stabilization of the complex.

The hinge

The DNA-binding domain is contiguous to a hinge region that spans amino acid residues 624-665 and links with LBD. The nuclear localization signal (NLS) (residues 617-633), forms part of the DBD and the hinge and is responsible for nuclear import of the receptor. The NLS is a nuclear targeting signal composed of two clusters of basic amino acids separated by Chapter 2. Androgen Receptor and its role in Prostate Cancer 10 residues. This region presents the 629-RKLKKLGN-636 motif, also involved in the DNA binding as a coactivator recruitment and in the N/C interaction [Tan 2014].

The ligand binding domain

Similarly to the DBD, the ligand binding domain (LBD) is a highly conserved domain and its structure has been well characterized. The LBD composes the last C-terminal part of the androgen receptor (residues 666-919). The LBD allows ligand-dependent activation of the receptor, receptor homodimerization and presents binding sites for chaperones interactions [Shaffer 2004]. The LBD architecture presents eleven ↵-helices (H1-H12) and two antiparallel -sheets. This tridimensional structure, as for the DBD, is similar in all the members of the nuclear receptors family but in the androgen receptor the helix H2 is not present, and is replaced by a flexible linker. The LBD contains a ligand-dependent transactivation domain, AF2 (activation function 2), and mutations or deletion of this region drastically reduces transcriptional activation as response to a ligand. Moreover, Ligand binding induces a conformational change which stabilizes the helix H12, allowing the interaction with the NTD-AR [Li 2009, Pawlak 2012].

Androgen Receptor Ligands

A large diversity of small molecules interact with the androgen receptor, naturals or synthetics.

These molecules can be classified as agonists or antagonists, regarding their ability to activate or inhibit the transcription of target genes and to modulate AR function.

AR agonists

Testosterone and Dihydrotestosterone (DHT), are the most important endogenous androgens that exists (Figure 2.2). Testosterone is secreted by the testicles in males and in the ovaries in females, and it was first characterized in 1935 by Prof Ernst LAQUEUR. DHT was discovered later, when it was observed that a fraction of the testosterone is metabolized to DHT by a 5↵-reductase [Tan 2014].

AR antagonists

The antagonist ligands of the androgen receptor are known as antiandrogens, steroidal or nonsteroidal, and they antagonize the androgens actions by competing for the binding sites in AR. Antiandrogens inhibit circulating androgens by blocking androgen receptors, suppressing androgen synthesis, or acting in both ways. In 2012, a second-generation of AR antagonist was Chapter 2. Androgen Receptor and its role in Prostate Cancer developed, enzalutamide (Figure 2.3), a more potent antagonist that binds to the AR ligandbinding pocket with higher affinity than the first generation molecules, and also restrain the receptor translocation into the nucleus [Tran 2009].

Androgen Receptor mode of action

Androgen Receptor is a hormono-inducible DNA-binding transcription factor that can adopt different modes of action (Figure 2.4). In classical AR signaling, in the absence of ligand, AR is located in the cytosol and forms a complex with heat shock proteins (HSP), chaperone and co-chaperone proteins with the objective to maintain AR in a ligand-binding competent state Testosterone is synthesized in the testes in men, and in the ovaries in women. In men, once it is produced, the free form enters prostate cells. In the prostate, testosterone is converted to 5↵-DHT by the enzyme 5↵-reductase, which is the high affinity ligand for AR and promotes the growth and survival of prostate cells. Upon hormone binding, HSP are displaced from AR allowing hormone-bound AR to dimerize and to translocate to the nucleus. Then, different modes of action can occur. In the best characterized and the most common case (see Figure 2.4 1), AR binds to AREs (androgen response elements) on the DNA and interacts with different transcription co-regulators to regulate gene expression. These different co-activators Chapter 2. Androgen Receptor and its role in Prostate Cancer complexes remodel the chromatin allowing general transcription factors and RNA Polymerase II to begin the process of transcription [Shafi 2013, Matsumoto 2013].

In a second less well characterized mechanism (Figure 2.4 2) AR recruits co-repressors and can inhibit transcription [Shafi 2013]. Moreover, in a third mechanism (Figure 2.4 3), AR also regulates transcription through a tethering mechanism by binding to other transcription factors (TFs) and recruiting additional co-activators to target genes. Finally, in addition to classical AR signaling, AR can initiate extranuclear signaling (Figure 2.4 4). The activated complex formed by hormone-bound AR, dimerizes and can interact with kinases. As a result of this interaction, an activation of a kinase cascade occurs. The resulting signaling cascade can activate other TFs in the absence of direct AR binding to the gene [Shafi 2013].

Androgen Receptor and different related pathologies

The androgen receptor has a fundamental role in androgen signaling for differentiation of male sexual characteristics. Its role in male physiology and the reproductive system, is highlighted by the hereditary disorder of the Androgen Insensitivity Syndrome (AIS). AIS can be defined as the partial or complete inability of cells to respond to androgens [Hughes 2012]. In the AR, missense1 and nonsense2 mutations cause a large number of abnormalities in male development. The effects of these mutations can result from a light virilization to a total reverse phenotype male-female [Matsumoto 2013]. Nowadays, around 1000 different mutations have been identified in the human AR gene, described in the Androgen Receptor Gene Mutations Database World Wide Web Server (http://androgendb.mcgill.ca/AR23C.pdf) [Gottlieb 1998].

Androgens also regulate spermatogenesis via the expression of AR in somatic cells of the testes [Verhoeven 2010]. They could also have an effect mediated by androgens in the development of the brain masculinization but this is still controversial [Arnold 1984]. Agerelated osteoporosis is a poorly known phenomenon; although the reduction of the use of androgens is closely correlated with a wide variety of conditions associated with aging including reduced muscle mass, decrease in bone mass and reduced strength [Kang 2008]. AR would have a direct role in the maintenance of bone through the matrix synthesis and their mineralization

[Matsumoto 2013].
Furthermore, an other well known androgen-related disease is the Spinal Bulbar Muscular Atrophy (SBMA) or Kennedy's disease. The SBMA is a progressive neurodegenerative disease Chapter 2. Androgen Receptor and its role in Prostate Cancer that appears when there is a polyQ expansion in the N-terminal domain of the androgen receptor. Polymorphism repeated CAG normally consists of 9 to 36 repetitions, expansion beyond 40 causes neurotoxicity [La Spada 1991[START_REF] Davies | Consequences of poly-glutamine repeat length for the conformation and folding of the androgen receptor amino-terminal domain[END_REF].

Androgens have been always associated with male and the men reproductive system development, even if AR is located on the human chromosome X.

Despite the fact that AR is located on the human chromosome X, little is known about androgens actions in female physiology, but the detection of hyperandrogenism in polycystic ovarian syndrome (PCOS) which causes infertility with abnormal menstrual cycles suggests that the androgen signaling plays an important role in women [Matsumoto 2008].

As has been described above, AR is involved in many different pathologies. Nevertheless, prostate cancer it remains the best known and most studied disease related with the androgen receptor.

Androgen Receptor's role in prostate cancer

The androgen receptor activity is directly related with prostate cancer, which is a leading cause of death of men in the industrialized world. It is the most commonly diagnosed cancer in men in U.S.A and the second leading cause of cancer deaths. With an increasing incidence, 71.500 new cases per year in France in 2010, remains a major public health problem. Around 159 of the AR mutation described, predispose males to develop prostate cancer [Tan 2014]. In addition, a shorter polyQ (<21 residues) influences prostate cancer risk in men [START_REF] Davies | Consequences of poly-glutamine repeat length for the conformation and folding of the androgen receptor amino-terminal domain[END_REF]].

The prostate gland is under a strict hormonal control. Prostate cancer cells, as normal prostate cells, are androgens dependent for their growth and their survival. The role of androgens in prostate cancer has been described by Huggins and Hodges in 1941, they demonstrated the reduction of prostate tumors during androgen deprivation. Charles Huggins received the Nobel Prize in Medicine and Physiology in 1966 for the treatment of cancer from hormone therapy. As prostate cancer develops initially as an androgen-dependent disease, this explains the initial effectiveness of anti-androgens therapies for advanced prostate cancers. However, in most cases, a resistance to androgen deprivation develops in one to three years and prostate cancer cells undergo recurrent growth despite low levels of circulating androgens and the presence of synthetic androgen antagonists [Matsumoto 2013].

Castration or androgen deprivation therapy is the standard treatment for metastatic prostate cancer local recurrence after radiotherapy. Inevitably, an exhaust androgen suppression is observed after a median of 12 to 18 months. Many factors contribute to the activation of AR despite a low level of androgens. Alterations in androgen signaling pathway have been as-Chapter 2. Androgen Receptor and its role in Prostate Cancer sociated with castration resistance such as amplification of the androgen receptor gene, the emergence of mutations in the ligand binding domain which extend the receiver sensitivity spectrum to other steroids that androgens or expression of constitutively active forms, without the ligand binding domain [Funderburk 2009]. Relapsed prostate cancer, known as Castration Resistant Prostate Cancer (CRPC), is associated with a high mortality due to the lack of effective longterm treatment strategies. It is a complex disease that develops during the course of anti-androgen therapy but nonetheless maintains a dependence on AR for its metastatic potential.

The mechanism for the CRPC development remains unclear, furthermore different possibilities have been proposed: an increased sensitivity of the AR to its agonists; some mutations that makes AR reactive to non-androgen ligands; activation of the AR independent of ligands or an other mechanism AR independent [Tan 2014].

Raising evidences support the concept that the development of CRPC is causally related to continued transactivation of AR. All current therapies that target the AR are dependent on the presence of the C-terminal LBD and its activation function 2 (AF2). Consequently when the CRPC is developed, and constitutively active AR splice variants that lack the LBD ( LBD) appear [Lapouge 2008], these therapies fail. Then, the activity of the receptor is regulated by the N-terminal domain and its activation function 1 (AF1). Functionally, AR N-terminal domain (NTD) plays the primary role in regulating target gene transcription activation nevertheless the absence of the AF2 makes the receptor as constitutively active. Therefore modulation of NTD function can be considered as an efficient strategy to target AR action.

New strategies to target the Androgen Receptor

The fact that current therapies for the prostate cancer (based on androgem ablation or antiandrogens) fail, put in evidence the necessity of developing new drugs to reduce androgens levels as well as more potent AR antagonists. As explained above, most antiandrogens are designed to target the ligand binding domain. However, when CRPC is developed, the AR splice variants LBD appear and antiandrogens targeting the LBD become useless, without effect in the receptor activity. Then, the NTD-AR with its AF1 becomes the responsible of the receptor activity and appears as a new target strategy for drug development.

The N-terminal domain, as has been introduce previously, is a wide domain with 550 residues and with the absence of structure. These characteristics make it difficult to study it and it has been poorly studied. This structural plasticity of the NTD allows an allosteric regulation of protein folding and function in response to hormone, DNA response element architecture, and coregulatory protein binding partners. This aspect was recently investigated by Kumar and McEwan in a comprehensive review on the allosteric modulation of steroid hormone receptors [Kumar 2012]. NTD-AR is also known to be the site of many cancer related mutation, either as genetic predisposition for prostate cancer or as somatic mutations, usually specific to the castration-resistant tumor [Matsumoto 2013].

Recent studies [Sadar 2011] have shown that several small molecules (see Figure 2.5) interact with NTD-AR and modulate its activity, for instance by blocking its AF-1 activity, thus showing a potential new therapeutic route. Chromatin immunoprecipitation analyses showed that EPI-001 reduced the interaction of AR with the response elements of the target genes, including PSA and TM-PRSS2. EPI-001 binds to the NTD of AR and inhibits the recruitment of the transcriptional cofactors CBP and RAP74, suggesting that EPI-001 functions by blocking protein-protein interactions at the NTD. EPI-001 reduced androgen-dependent and androgen-independent proliferation of LNCaP prostate cancer cells that express AR and had no effect on cells that do not require AR activation for growth [Andersen 2010 The biophysical study and structural characterization of an IDP can be addressed trough different strategies. The project can be raised to study the entire protein complex or domain, or to study different small peptides constructs from the protein sequence. The choice on these different strategies depends on the behavior of the protein in solution, the availability of the different techniques and our expertise, or the objectives we want to achieve.

Using as an example the N-terminal domain of the Androgen Receptor the same two strategies can be adopted. As explained in Chapter 2, the NTD-AR is a large non-structured domain with 550 residues implying the difficulty of the production and its low stability in solution. A good alternative to characterize this domain is to study it by choosing different small peptide regions which could be easier to manipulate and to stabilize.

The flexible nature of IDPs precludes their study by crystallographic methods. For this reason, the best strategy to achieve this study is to characterize the object in solution. A wide range of biophysical techniques can be used, as fluorescence spectroscopy, circular dichroism (CD), mass spectrometry (MS), small angle X-ray scattering (SAXS) and nuclear magnetic resonance (NMR). Although the electron microscopy (EM) is not considered a solution technique, it preserves the specimen in a snapshot of its solution state. For that, it can be also used for the study of an IDP.

Chapter 3. Biophysical methods to characterize different peptide regions of an IDP

The biophysical methods addressed in this thesis, for the peptide study of the NTD-AR, are explained below.

Fluorescence spectroscopy

Fluorescence application in protein and peptide analysis is mainly a probe sensing changes in the fuorophore local environment. Fluorescence is a popular spectrosocopy technique due to its sensitivity and simplicity of data acquisition. The tryptophan residue is used as a intrinsic fluorescent probe for the study of protein folding. And also, for the interaction studies, it can be used to estimate the nature of microenvironment changes up to binding. Fluorescence is a dynamic phenomenon and the variation of the lifetime of the excited state is sufficient to detect a variety of chemical reaction [Ladokhin 2006]. The anisotropy decay is also sensitive to the rotational diffusion of the molecule, and its variation is a sensor to molecular interactions.

The characteristic time of fluorescence ranges in the nanosecond and is a good complement to other spectroscopic techniques sensitive to dynamics, such as NMR. Proteins that lack aromatic residues can be coupled to fluorophore to performed these experiments, or an specific dye can be also used. As example the Thioflavine T for the characterization of amyloid fibers [Nilsson 2004].

Circular Dichroism (CD)

Circular dichroism (CD) spectroscopy measures the difference in the absorption of left-and right-circularly polarized light. This occurs at wavelengths of light that can be absorbed by a chiral molecule. At these wavelengths left-and right-circularly polarized light will be absorbed to different extents due to the molecule chirality. The CD spectrum is obtained when the dichroism is measured as a function of wavelength. The units of CD results are reported in degrees of ellipticity (✓, mdeg), molar ellipticity (circular dichroism corrected for concentration).

CD spectroscopy has a wide range of applications in many different fields. A primary use of UV CD is to investigate the secondary structure of proteins [Brahms 1980]. This application can be extended to study molecular interactions or changes due to environmental conditions.

Reaction kinetics and thermodynamic information can be also obtained [Kelly 2005].

The far-UV CD (180-250 nm) spectrum is used for the study of the secondary structure of proteins (Figure 3.1). In this aspect, CD gives the information to estimate the fraction of a molecule that is in the alpha-helix conformation, the beta-sheet conformation, the beta-turn conformation, or random coil. The near-UV CD spectrum of proteins provides information

Mass Spectrometry (MS)

Mass spectrometry (MS) is an important technique in proteomics and systems biology. MS is an analytical technique used to identify the mass of the species present in solution, by measuring the mass/charge ratio (m/z). It allows high-throughput analysis and requires small amounts of material (nM-fM range). The study of biological samples by MS has been revolutionized by the ESI ionization technique which allows to transfer to gas phase biological molecules with virtually no limit in the molecular size. As proteins and nucleic acids are naturally ionized, it is straightforward to measure MS spectra of complete proteins or of their fragments. This open the possibility to directly characterize the proteins present in the solution. The precise determination of the mass allows the determination of the present species, and to determine their eventual covalent modification (post-translational modification, adduct formation, etc).

Modern applications of high-resolution mass spectrometry to the metabolism of drug or to study complex aspects of metabolism. Or quantitative analysis of proteins on proteomics [Guengerich 2011].

Electron Microscopy (EM)

The use of electron microscopy (EM) is appropriated for the study of large molecular assemblies.

The best approach to study biological samples is cryo-microscopy, however for a rapid, and less precise, identification of the object size and shape, the transmission electron microscopy (TEM) can be a good option. TEM is a microscope technique in which a beam of electrons is transmitted through an ultra-thin specimen, and interacting with it while is passing through Uranium staining. As a result, an image is formed and focused onto a fluorescence screen.

On the other hand, if a three-dimensional study of the large molecular assemblies is desired, the use of cryo-EM is needed. The method detects projections of a frozen hydrated specimen. For a 3D reconstruction of the particle shape, a large number of such projections from particles in all orientations are collected, averaged and analyzed [Göbl 2014]. High structural homogeneity and integrity is required for high resolution reconstructions. EM requires less material and tolerates more impurities than SAXS or NMR, and is a good technique to solve molecular structures of large molecules in combination with these methods.

Small Angle X-ray Scattering (SAXS)

Small Angle X-ray Scattering (SAXS), is a fundamental tool for the study of macromolecules in solution. SAXS is a good complementary technique to high resolution techniques such as nuclear magnetic resonance or X-ray crystallography. Furthermore it can be used in dynamic systems or disordered systems which are limited in X-ray crystallography, in the sense that it requires good crystals formation. In these situations, SAXS becomes an interesting alternative.

SAXS gives information about the shape and the size of the object in solution, consequently is a useful technique to obtain structural information in disordered systems.

The sample preparation requires an homogeneous dilute solution. This is necessary in order to obtain a monodisperse system of particles in solution with a random orientation. As a result, a spherical averaging of the particle scattering will be obtained.

The experiment consists in shining an X-ray beam through the solution sample, and to measure the X-rays scattered at small angles by the scattering particles present in the solution.

The scattered X-rays form a pattern which is then detected at the detector. The scattering pattern contains the information on the structure of the sample. This equation summarize the information we can obtain with a SAXS experiments.

Where the scattering vector is defined by q = 4⇡ sin(✓) .

The scattering curve can be analyzed at several levels, depending on the domain of the curve which is considered (Figure 3.2):

Figure 3.2: In a double logarithmic plot an initial slope of 0, -1 or -2 indicates globular, cylindrical or lamellar shape, respectively. If the slope is steeper than that then the particles are larger than the resolution limit and the Porod region is the only part of the form factor that can be observed.

For ideal monodisperse systems, the Guinier plot (ln(I(q)) versus q 2 ) should be a linear function, whose intercept gives I 0 and the slope yields the radius of gyration Rg of the scattering particles (see Figure 3.2 and 3.3). The Kratky plot, which analyses the large q domain, is useful to rapidly identify if the system is folded or unfolded (see Figure 3. Figure from [Svergun 2003].

Nuclear Magnetic Resonance (NMR)

The origins of the Nuclear Magnetic Resonance (NMR) were formulated in the late 1930s and early 1940, but it was only in the 1980s when NMR starts to be used to obtain information about the structure and dynamics of proteins, and also nucleic acids [Wüthrich 1982] and its use for three-dimensional triple-resonance experiments with 13 C and 15 N enriched proteins [Kay 1990].

NMR involves the quantum mechanical properties of the spin of the central nucleus of the atom. These properties depend of the molecular environment at the local level, and their measurement provides a map of the chemical bond between the atoms, how close they are in space and their movement rate with respect to each other.

Most biological samples are studied in water by solution state NMR, but solid state NMR can be also used with solid samples.

The most common nuclei studied by NMR are those with S=1/2 (where S is the spin quantum number). These nuclei include the naturally occurring isotopes 1 H and 31 P found in high-abundance (close to 100%) in proteins and nucleic acids; and others such as the lowabundance 13 C (1.1%) and 15 N (0.4%), requiring isotopic enrichment through biochemical techniques for optimal sensitivity [Greenbaum 2001]. The engineering development for the isotopic labelling of the proteins and other macromolecules, helped to the development and improvement of the multidimensional NMR experiments in order to achieve the atomic assignment of the signals for further structural calculations. Currently the protein complexes can be studied routinely up to a molecular weight of about 40 kDa. Recent developments in hardware and pulse programs have extended the study of proteins with a molecular weight around 100 kDa [Tugarinov 2004].

The nuclear magnetic resonance is also used for the description of the dynamics of biological macromolecules. Relaxation measures can be also used to measure molecular motion to help to identify potentially more flexible regions of importance to the function of the protein. Currently it is the second most used method in the determination of high-resolution structure after the X-ray diffraction but with the advantage that by NMR the macromolecule study is dynamic and you can observe the transient different conformations adopted.

Peptide structural characterization

Coming back to the strategy to study short peptides regions of the NTD-AR, a set of different NMR experiments is needed for their characterization.

H 1D experiment

All NMR characterization starts performing a 1 H 1D experiment (Figure 3.4). Where RF signal is transmitted during few µs (90 pulse). In order to move the magnetization vector from the z-axis to the x,y-plane. The signal that evolves due to precession of the magnetization vector is measured after the pulse. At the end of the process, the vector returns to equilibrium on the z-axis. The process is called free induction decay (FID) of the magnetization. The Fourier transform is performed to the recorded FID, in order to obtain the NMR spectrum. This simple experiment gives rapidly, the information of the nature of the sample. Figure 3.5 shows the spectral range for the proton chemical shift ( ), which helps to identify the different amino acids that form the peptide sequence and to detect the presence of possible impurities. To succeed in the peptide assignment it is necessary to identify the amino acid side chains and the neighboring residues in the peptide sequence. The combination of both give the primary structure assignment of the amino acid sequence. The contacts with the residue neighbors allows to also obtain information about the secondary structure of the residues chain. This objective can be achieved performing TOCSY and ROESY experiments.

TOCSY (TOtal Correlation SpectroscopY)

This method is used to observe the effect of scalar couplings, which appears between 1 H spin located at a distance of 2 to 3 chemical bounds. TOCSY is used to assign each amino acid individually. Figure 3.6 shows the NMR sequence for the TOCSY experiment. Firstly, the 90 pulse rotates the magnetization from z to the xOy plane, where they evolve during t 1 . After that, a spin lock on the x axis is applied of a duration time t m (mixing time), and then the spectrum is acquired. When working with peptides a problem arises. NOE depends strongly on correlation time and goes through zero for !⌧ c = 1 which corresponds to medium-sized molecules (M W range 700-1200 Da for a 600-700 MHz spectrometer). This corresponds to most of the peptides studied here. However, in these situations an alternative is to use the ROE effect (Rotating frame Overhause) to detect correlation between nucleus that are spatially close. In this case, a spin-lock is employed to ensure that correlation between spins, which are close in space but have zero NOE, are seen.

ROESY (Rotating frame Overhauser Effect SpectroscopY)

The aim of this experiment is to observe through space dipole-dipole coupling. The result of a ROESY experiment is a 2D spectrum in which the out off diagonal signals arise from the Overhauser enhancement effect between space coupled protons. ROESY is useful for determining which signals arise from protons that are close to each other in space even if they are distant in the molecular topology, and is used to to identify the position of the amino acids within the sequence.

The sequence is equivalent to the one in Figure 3.6 but the difference resides in the strength/efficiency of the field during t m . In TOCSY, an efficient decoupling of the spins is desired, for this reason, a strong RF field ( 10kHz) and an efficient composite decoupling scheme (MLEV, DIPSI, etc...) are applied. In ROESY, the magnetization is locked in the plane, and the RF field not too strong to avoid the observation of the TOCSY effect.

The correlation peaks obtained from the ROE effect show an opposite sign compared to the diagonal. On the other had, the correlation peaks coming from the chemical exchange present the same sign than the diagonal, allowing to distinguish easily between dipolar interactions and chemical exchange effects.

Figure 3.8 outlines the information that can be obtained with either a TOCSY or a ROESY experiment. In a TOCSY, all spins are seen, for each individual residue. The ROESY will have both intra-residue correlations, as well as inter-residue correlations, which allows us to find which residue is next to which in the peptide chain.

52

Chapter 3. Biophysical methods to characterize different peptide regions of an IDP Nuclear magnetic resonance (NMR) spectroscopy has been extensively used in chemistry, biology and medicine for the mixtures analysis. Among all the different NMR experiment that exist, Diffusion Ordered SpectroscopY (DOSY) is in particular a widely applied technique in life sciences for complex mixtures analysis [Barjat 1998, Lucas 2002, Gilard 2011], reactive intermediates [Schlörer 2002[START_REF] Giuseppone | DOSY NMR experiments as a tool for the analysis of constitutional and motional dynamic processes: implementation for the driven evolution of dynamic combinatorial libraries of helical strands[END_REF]] and molecular organization [Šmejkalová 2008, Cohen 2012[START_REF] Nonappa ; Nonappa | Studies on supramolecular gel formation using DOSY NMR[END_REF].

TOCSY N C α C' N C α C' H O H O H CH 3
The analysis of the diffusion coefficients is a powerful tool to gain insight on molecular sizes and shapes [Wilkins 1999, Gomez 2009, Floquet 2009], and can also be used to investigate molecular interactions [Lucas 2004, Cohen 2012[START_REF] Nonappa ; Nonappa | Studies on supramolecular gel formation using DOSY NMR[END_REF], polymer polydispersity [Stchedroff 2004, Viéville 2011], or to characterize reactive intermediates [Schlörer 2002, Li 2009, Nguyen 2009, García-Álvarez 2011].

Chapter 4. Permutated DOSY (p-DOSY) for the study of complex systems A spectrum of the different components in the mixture can be separated based on the apparent diffusion coefficients by measuring the NMR signal decay. Furthermore, DOSY experiments setups and methodology can be easily standardized and automated.

Translational diffusion from an atomic point of view can be defined as the result of the random walk of the diffusing particles, where the molecules are self-propelled by thermal energy.

The random walk of small molecules in suspension in a fluid was first described by Robert Brown in 1827, and this phenomenon is known as Brownian motion. The diffusion of particles observed in this phenomenon can be measured as a translational coefficient or as hydrodynamic radius r H , which are inversely proportional, as described by the Stokes-Einstein eq. 4.1 for spherical shaped molecules.

D = k B T 6⇡⌘r H (4.1)
where k B is the Boltzmann's constant, T is the absolute temperature, and ⌘ is the viscosity.

Other shapes can be handled either with extended analytical models [Evans 2013] or by a statistical description [Augé 2009, Hernandez Santiago 2015].

Diffusion Ordered SpectroscopY (DOSY)

NMR can be used to measure the diffusion coefficient (D) of molecules in solution by using special sequences that use pulsed-field gradients (PFGs) along the sample axis (z). In order to understand how the experiment works, we should start by defining the Larmor frequency ! (radians s 1 ), ! = B 0 , where is the gyromagnetic ratio of the nucleus and B 0 k is the magnetic field. When a PFG is applied along z (G(z)), ! becomes spatially dependent.

! = (B 0 + G(z)z) (4.
I = I 0 e D 2 g 2 2 ( 3 ) (4.3)
Where D is the diffusion coefficient, the gyromagnetic ratio, and g and the intensity and the duration of the PFG, respectively. I o is the signal intensity obtained in the absence of field gradient and I in the presence of a gradient of strength g; is the effective diffusion delay defined as the time between the start of the bipolar gradient pairs; see [Sinnaeve 2012] for details.

From which D can be obtained after the acquisition of a series of free induction decays (FID) varying the gradient strength.

The result of a DOSY experiment is a bidimensional NMR spectrum with the diffusion coefficient D as vertical axis. This representation was proposed by Morris and Johnson [Morris 1992] in 1992, and it has been reported in the literature by different reviews [Johnson 1999, Antalek 2002]. The main features of a DOSY experiment are, that it is an NMR technique not based on the time dependence of the signal, only the intensities of coding and decoding gradients are varying and all delays are kept constant. It is also remarkable that in contrary to most NMR experiments that use the Fourier transform for spectral analysis, the DOSY experiment is using the Laplace transform because the signal variations follows an exponential law.

The different NMR experiments used in DOSY acquisition are reported in Figure 4.1.

Spin-echo (SE)

The original spin-echo (SE) experiment Figure 4.1a) is the simplest pulse sequence that can be used for diffusion measurement and it is based on the analysis of the decay of the spin-echo signal intensity with increasing PFG intensities. A 90 pulse is applied and the magnetization is aligned on the xOy plane perpendicular to the applied static magnetic field. This static field is then momentarily perturbed by the first PFG with a length of . When the PFG is applied, the field intensity varies linearly along the main axis of the sample. As a result of this, a dephasing of the bulk NMR signal is introduced due to a spatial phase encoding which depends on the spin position along the z-axis. A magnetization helix is observed at the end of the PFG. The 180 in the middle of the experiment inverse the magnetization and it creates a

Hahn echo that removes any contribution of the chemical shift to the evolution. The final PFG applies an opposite dephasing to the magnetization, allowing the signal restore to its initial state. However, the diffusion takes place during the delay between the two PFG. If the mean molecular displacement is on the order of the pitch of the magnetization helix, this helix is blurred and the intensity of the signal is decreased.

Stimulated Echo (STE)

The Stimulated Echo pulse sequence (STE) experiment Also, an extra final delay (LED) is added during which the magnetization is stored along the z-axis to let all the generated fluctuations die away before the acquisition. These two optimizations have the same purpose that is to reduce the intensity of the eddy current generated by the PFG and to minimize its impact on the observed signal.

OneShot experiment

The OneShot experiment ( Spectral resolution can be considerably improved by using 3D DOSY experiments, where diffusion weighting is added before or after to a 2D experiment. But also by suppressing the multiplet structure in the proton spectrum to give a pure shift experiment.

3D DOSY

As said previously, the most common solution to the overlap problem in DOSY, is to add a diffusion dimension to a 2D experiment and for this reason, many different pulse sequences for 3D DOSY have been published [Barjat 1998, Lucas 2002, Bradley 2005] A 3D DOSY sequence can be achieved with different strategies: appending the diffusion encoding (X-DOSY), prepending the diffusion encoding (DOSY-X) or incorporating it internally

(IDOSY)
The result of this extra diffusion dimension incorporated into a classical 2D experiment is shown in Figure 4.2, where the D dimension coupled with the HMQC helps the spectral elucidation.

As the DOSY-HMQC [Barjat 1998] experiment shown as example of a 3D DOSY many other sequences have been reported in the literature, as DOSY-TOCSY [Birlirakis 1996],

DOSY-COSY [Wu 1996, Balayssac 2009] or the DOSY-TROSY [START_REF] Didenko | [END_REF]] more recently.

IDOSY

The IDOSY sequence is a 3D DOSY experiment where the diffusion encoding is added internally into the 2D sequence chosen for adding an extra diffusion dimension. The first sequence describing a iDOSY experiment was 2DJ-IDOSY by [Nilsson 2004], which improves the signalto-noise ratio and reduces the time of acquisition compared with the previous 3D experiments described. Furthermore, with this sequence no phase cycling is needed for the diffusion encoding.

Other iDOSY experiments have been also published applying the same strategy, as the COSY-IDOSY [Nilsson 2005], DQF-COSY-IDOSY [Newman 2007] or constant-time-HSQC-IDOSY [Vitorge 2006]. This method achieves a good resolution for 1H DOSY comparable to the one obtained using 3D DOSY methods such as DOSY-HMQC, but without the need to involve low abundance heteronuclei. However, the pure-shift advantage comes to the price of a much lowered sensitivity method.

DOSY on evolving systems

This chapter presents the special case of measuring DOSY experiment on an evolving system. In this case, a difficulty arises. According to the classical Stejskal-Tanner equation, the intensity at each gradient strength depends on the intensity I o with no gradient applied Eq. 4.3. Usually, I o is measured at the beginning of the DOSY experiment and considered constant throughout the measurement. However, in out-of-equilibrium systems, I o is not constant anymore but varies continuously, due to evolution of the concentrations. These variations cause the intensity I to depend not only on the applied gradient but also on a varying I o . Consequently, throughout the DOSY measurement, the signal intensity measured for a given species, depends on the concentration evolution as well as the increasing gradient strength, and appears to decay either too rapidly or too slowly, depending on the evolution of a concentration decreasing or increasing over the time of the measurement, creating a bias in the analysis.

The kinetic rates of the out-of-equilibrium system has to be taken into account and be compared to the timeframe of the DOSY measurement. Rapid DOSY measurements monitoring systems with slow kinetic rates are not affected to a significant degree, because only minor concentration changes occur over the experimental time. On the other hand, long DOSY measurements monitoring systems with fast kinetic rates are not affected either, but fail to record dynamic information of the system such as reactive intermediates.

The effect is dramatic for systems with intermediate kinetic rates monitored by DOSY measurements performed in a time similar to the kinetic constant of the chemical systems.

In this case, the DOSY spectra display an apparent shift of the peaks along the diffusion coefficient axis leading to wrong results.

Nilsson et al. [Nilsson 2009] proposed the use of trilinear multivariate analysis in order to characterize both the reaction kinetics and the diffusion coefficient, in the analysis of a set of diffusion experiments measured during the chemical reaction. In this case the concentration variations is used as a third dimension in the multiway analysis. However in this approach, the DOSY measurements are supposed to be rapid compared to the kinetic rates, and there is no compensation for the unavoidable bias in the diffusion coefficient measure. To our knowledge, the DOSY studies performed so far on out-of-equilibrium systems [Schlörer 2002, Li 2009, Nguyen 2009, García-Álvarez 2011, Nilsson 2009] have not taken into account the analytical bias caused by concentration variations.

We propose here to measure, within a single DOSY measurement, a series of stimulated echo spectra with pulse gradient strengths sampled in a permutated manner, as it was already proposed in order to reduce F 1 artifacts in 2D NMR spectroscopy [START_REF] Bowyer | Randomized acquisition for the suppression of systematic F1 artifacts in two-dimensional NMR spectroscopy[END_REF]]. From the sequential list of pulse field gradient strengths, a random permutation is computed, and the DOSY is measured with a new list of gradient strengths in permutated order. This protocol has been called permutated-DOSY (p-DOSY). To test the effect of the permutated acquisition on the accuracy of the measure, the diffusion coefficient of glucose was monitored during the equilibration from pure ↵-glucose to the anomer equilibrium of ↵ and -glucose [Gurst 1991] (see Figure 4.5).

p-DOSY: application on evolving systems

The p-DOSY approach, and its capacity to restore accuracy in the determination of diffusion coefficients was tested using glucose anomerization as a test case for out-of-equilibrium systems.

Glucose crystalizes in the ↵ form, as a consequence, this form is dominant in the solution just after solubilization.

The ↵, -D-glucose was studied by NMR and the assignment of the molecule was done in order to be able to characterize the ↵ and protons for further analysis. This assignment is shown in the 1D spectrum in Figure 4.6 and it corresponds to the numbering of both anomeric molecules in Figure 4.5. The anomerization of ↵-to -glucose was followed by acquiring DOSY measurements for approximately 6.0 hours, with ↵-D-glucose varying from 96.6% to 44.6%. The same experiment was performed twice, the first time with the standard DOSY method, and the second time using the p-DOSY approach. While the anomerization was followed by DOSY measurments, a 1D kinetics Figure 4.7 was also acquired by recording a 1D 1 H spectrum between each DOSY experiment. This allows to follow easily the ↵ signal appearing while the peaks are disappearing.

The diffusion coefficients in water of both species ↵ and -glucose are expected to be very similar, as they have very similar shapes. However, they appear with quite different diffusion coefficients when measured with a standard DOSY experiment, acquired in a sequential manner, as can bee seen in figures 4.8 and 4.11. In particular, the signals from the -glucose are found initially at a marked slower diffusion coefficient and recover the normal value over the course of the experiment. This is the result of the progressive increase of concentration of -glucose over the duration of a single DOSY measurement, which creates a bias in the exponential analysis of the signal. At the end of the 6 hours experiment, the recovery is not complete. On the other hand, this bias is completely absent when the anomerization equilibrium is monitored using the p-DOSY measurements, run in the same conditions (see figure 4.9). This improvement in the diffusion coefficient is clearly shown in Figure 4.10 where at the beginning of the ↵, -glucose anomerization the standard DOSY experiment display a bias on the diffusion value for the beta protons whereas the p-DOSY experiment withdraw the bias.

In both experiments, the diffusion coefficients of water and DMSO display the standard values for all experiments run during the kinetics, indicating that the error on -glucose is not due to an experimental bias but uniquely to the variation of the concentration. Figure 4.11 presents the evolution of the DOSY signal intensities and of the apparent diffusion coefficients over the course of the experiment. It shows that the initial -glucose concentration is very low, and that the two populations equilibrate slowly, so that 6 hours are not sufficient to reach the complete equilibrium. When measured with the standard DOSY experiment, the apparent -glucose diffusion coefficient, varies in an anomalous manner before converging toward the correct value, while the p-DOSY measure presents stable measurements for both species.

The poor accuracy of the diffusion coefficient of -glucose is attributed to miscalculation of the analysis of the reference intensity, I o . The diffusion coefficient of -glucose consequently, appears to have an incorrect low value. This effect is stronger in the first DOSY measurements since there is a higher kinetic rate. Similarly, the ↵-glucose that evolves in the opposite direction, displays an apparent diffusion coefficient slightly larger than expected in the first DOSY measurements. The effect is less marked because the relative concentration variation of the ↵-glucose is less important than in the case of -glucose.

On the other hand, the experiment performed with a series of p-DOSY measurements does not display this systematic error, and accurate values are determined over the whole experiment.

Because of the dispersion effect of the random permutation operation, the systematic evolution of the concentration is transformed here into random errors on the I o value. This added random noise has no effect on the analysis, but disperses in a random manner the concentration variation over the gradient list, thus providing a way to average out bias. However, because of the added noise, a slightly less precise determination of the diffusion coefficients is expected. This effect, while not very strong, can be observed on In a nutshell, one can say that the p-DOSY experiment provides on evolving chemical systems, a slightly less precise, but much more accurate determination of the diffusion coefficient that the standard DOSY experiment. a)

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Conclusions

The accurate estimation of diffusion coefficients is challenging in systems away from equilibrium. An inherent characteristic of out-of-equilibrium systems is the evolution of the concentration of the different components during a DOSY NMR experiment. Since the basis of a single DOSY measurement is the analysis of exponential decay of the signal over an increasing gradient strength, concentration evolution, within the characteristic measurement time, creates a bias, which can lead to large errors in the diffusion coefficient estimation. This was observed for the test case of the anomerization of glucose. Randomizing the list of gradient strength arrays within a single DOSY measurement, decouples the gradient evolution to the concentration evolution and removes the bias in the analysis, thus restoring the accuracy of the measure. The concentration evolution is still there though, as a noise source, and may have an impact on the precision of the measurement compared to a static sample, although its impact is minimum. Depending on the spectrometer software, this experiment requires little or no modification of the standard procedure, and the produced data-set can easily be analyzed using regular processing programs.

Altogether, the DOSY experiment with a randomized list of gradients (the permutated DOSY or p-DOSY) is an experiment exempt of bias in presence of an evolving system, in contrast with conventional DOSY. It is perfectly suited for the analysis of chemical reactions and out-of-equilibrium systems and can be used to monitor the rate of reaction kinetics, to characterize in-operando transient species and measure their diffusion coefficient, or to observed molecular organization phenomena and dynamics effects.

The robustness of p-DOSY can also be used to protect diffusion results from any experimental artifact, such as temperature shift or spectrometer drift. As it does not add any burden in the acquisition step nor at the processing step, we recommend spectroscopists to use p-DOSY systematically in diffusion and DOSY experiments.

Publication

The work presented in this chapter resulted in a publication in Journal of Magnetic Resonance The Androgen Receptor as a complex system and its role in prostate cancer have been introduced in Chapter 2. Within this topic, the receptor and specially its N-terminal domain is presented as the main actor when the castration resistance prostate cancer is developed. The constitutively active AR splice variants that lack the LBD appear and the current therapies (based on antiandrogens) become inefficient. Then, the NTD-AR and its activation function AF1 are responsible for the receptor activity. Consequently, the NTD-AR represents a new target for drug development.

Within this topic, our strategy is to find these potential target regions from the NTD-AR sequence and to characterize them. In order to achieve this objective, we propose a peptide study instead of the entire domain study. For that, an extensively bioinformatic study is carried out to find the hot spots within the sequence then, these peptide regions are going to be characterized using different biophysical methods.

Chapter 5. Biophysical characterization of a high conserved peptide from the N-terminal Domain of the Androgen Receptor

Bioinformatic analysis of the NTD-AR

In order to address the objective of this study, to characterize and to find partial secondary structure in the N-terminal domain of the Androgen Receptor, a bioinformatic study of this domain was carried out.

For this reason, the disorder tendency using metaPrDOS have been studied within the NTD-AR sequence in order to spot the most ordered predicted regions. These regions, with higher order tendency shown in Figure 5.1, give a hint for finding the sequences more likely to present a secondary structure.

Figure 5.1: Disorder tendency prediction obtained with the metaPrDOS analysis performed on the NTD-AR sequence. Residues below the 0.5 threshold are predicted as ordered, residues over 0.5 are predicted as disordered.

To complement this information, other studies are performed using different bioinformatic tools. MeDor is used to establish the secondary structure prediction on the NTD-AR based on the hydrophobic clusters formed in the amino acid sequence. As a result, a prediction of potential structured regions is stablished, see Figure 5.2.

The results of secondary structure prediction using the different bioinformatic tools explained in Appendix B (MeDor, NPS@, PAT) are summarize in Table 5.1. From this study a list of five peptides are selected from the higher consensus between the different methods, Besides these results, also other rationals are taken into consideration. The first aspect is to look for somatic mutations present in prostate cancer using the androgendb database [Gottlieb 1998, Gottlieb 2012], which url address is: http://androgendb.mcgill.ca/, some mutations are found in the five sequences shown in Table 5.1

The second aspect that is taken into consideration is the presence of recognition motifs, as

LxxLL or WxxLF that are present in two of the selected peptides. LxxLL has been reported in the literature as a motif in cofactor proteins for interactions with hormone dependent nuclear receptors [Heery 1997], as the androgen receptor [START_REF] Hendrikus | Distinct Recognition Modes of FXXLF and LXXLL Motifs by the Androgen Receptor[END_REF]], but also in other transcriptional regulation protein-protein interactions and a novel interaction implicated in leukemia [Garber 2005]. And the WxxLF motif, involved in interaction of the N-terminal domain with the ligand binding domain of the androgen receptor [He 2000].

There are also other important peculiarities in the sequence of the human NTD-AR, as the presence of numerous hydrophobic and aromatic residues usually absent in disordered regions.

Is the case of the presence of alternates hydrophobic and hydrophilic residues in peptide 2 (KELCKAVSVSM), a signature of -sheet structure. Or the presence or several tryptophan, tyrosine or phenylalanine in the ending part of the N-terminal domain, close to the beginning of the DNA binding domain represented in the peptides 4 and 5.

In order to complete the study of the primary sequence of the NTD-AR for selecting the peptides for a further biophysical study, an alignment of the AR was performed among twelve vertebrate species.

Chapter 5. Biophysical characterization of a high conserved peptide from the N-terminal Domain of the Androgen Receptor (corresponding to the peptide 2 obtained above with the different predictors of structure) that is highly conserved across all vertebrates, at a level equivalent to that of the DBD.

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Biophysical characterization of different peptides from the NTD-AR

After completion of the bioinformatic analysis of the NTD-AR, a series of different peptides were chosen to carry out a structural characterization using different biophysical methods. The peptides numbering presented below is referred to the Table 5.1.

Peptides study by NMR:

A first structural identification.

Firstly, the five peptides have been studied using NMR, which allows an initial characterization.

And the possible structure displayed for the peptides can be stablished.

• 1D and 2D NMR: peptide assignment

For an initial and rapid characterization of the possible structure present in the peptides, a series of equivalent NMR experiments were performed for each of them. The numbering used in this study corresponds to the one used in Table 5.1.

Peptide 4 (SSWHTLFTA)

As example of the NMR study carried out for each one of the peptides, here is shown the assignment of the peptide 4. The analysis starts by recording a 1D 1 H, Figure 5.5. By itself this experiment does not give us a lot of information about the peptide structure and it has to be complemented by a series of 2D experiments. A series of TOCSY and ROESY homonuclear experiments were recorded.

As a result of these experiments the 1 H assignment Figures 5.5 of the peptide 4 was performed. Together with these results, no NOE signal was obtained.

DMSO influence

In the peptides study, all samples were prepared with 10% of dimethyl sulfoxide (DMSO) in order to have to control experiments with the same % of DMSO that we use afterwards to solubilize small molecules for future interactions studies peptide with small molecules.

It is well known in chemistry, sometimes forgotten in biology, that DMSO is an efficient mild oxidant for disulfide bridge formation in peptides containing a cysteine [Tam 1991]. Indeed, in peptide 2 there is a Cys present in the amino acid sequence (KELCKAVSVSM).

Chapter 5. Biophysical characterization of a high conserved peptide from the N-terminal Domain of the Androgen Receptor

This was the starting point for a kinetics study. This study aims to follow the signal disappearance of peptide 2, upon the addition of different % of DMSO. Different kinetics were followed by 1D 1 H NMR after adding 1%, 5% and 10% of DMSO to a final solution with 0.5 mM of peptide 2 in phosphate buffer 20 mM pH=6.4 . Figure 5.9 shows the differences in the kinetics rates for the different % of DMSO, the signal disappearance is faster when increasing the % DMSO, the reaction rates are nearly proportional to the concentration of DMSO (see [Asencio-Hernández 2014]). In the absence of DMSO, slow aggregation kinetics is also observed, but in an irreproducible manner, due to no control of the presence of oxygen in the air.

In all cases, the signal intensity decays to a plateau at around 0.1 mM, and the initial part of the curve shows a characteristic second-order kinetics, characterized by a hyperbolic decay (Eq. 5.1).

[P ](t) =

[P ] o 1 + 2[P ] o kt (5.1)
Fit of the second-order kinetics equation was performed by a linear analysis of the inverse of the concentration vs time.

1 [P ] (t) = 1 [P ] o + 2kt (5.2)
Chapter 5. Biophysical characterization of a high conserved peptide from the N-terminal Domain of the Androgen Receptor

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Peptide 6 (KELSKAVSVSM), with a cysteine mutated to a serine, is used as a control to prove the implication of the cysteine in the oxidative process and the further NMR disappearance. This peptide 6, with a hydroxyl in place of the thiol group, is perfectly stable in solution (Figure 5.9) after the addition of DMSO.

Finally, after all these experiments we conclude that the cause of the NMR signal disappearance is the DMSO, in other words, an oxidation process within the peptide, with a most than probably, dimerization of the peptide through a disulfide bride formation. For this reason, Putting it all together, the previous results show that it is not only a matter of oxidation, or disulfide bridge formation in the peptide 2. The dimerization by itself should not be enough to justify the signal disappearance from the spectrum, and specially the broadening of the water signal observed in Figure 5.6 is a signature of the appearing of soluble mesoscale objects in the sample. Moreover, a slight opalescence and eventually a light precipitate was appearing in the NMR tube, characteristic of oligomerization process.

A special attention deserves the fact that the second-order kinetics data suggest that the initial step of the oligomerization is the formation of a peptide dimer, by the presence of DMSO acting as oxidant, although more complex mechanism might also be present, as reported in literature [Morris 2009]. The dimer further aggregates into supramolecular structures, and thus disappears from the liquid-state NMR spectrum. This hypothesis is supported by the observation that the peptide with Cys mutated to Ser did not display any oligomerization under the same conditions.

All these results together put us on the track that as larger objects, aggregates, were appearing in solution, the nature of which could be amyloid fibers.

Amyloid fibers characterization

Amyloid fibers have been introduced in Chapter 1 and present a particular biophysical signature.

In order to classify an object as amyloid or amyloidlike fibers a detailed study of the structure and morphology of the objects have to be performed. Amyloid fibrils should have a fibrillar morphology with a presence of -sheet secondary structure. They have a positive response for the Thioflavin assay or Congo Red birefringence assay [Nilsson 2004]. Here we present a detailed study of the peptide 2 aggregation, in order to determine the formation of amyloid fibers in solution.

Mass Spectrometry

With all these informations and with the aim to characterize if the objects appearing in solutions could be defined as amyloid fibrils, we decided to perform a first mass spectrometry (MS) analysis to determine if the peptide dimer was present.

In this purpose, the precipitate from the NMR tube was dissolved in 1:1 (v/v) Acetonitrile-Water with 2% formic acid and analyzed by MS. The result of this analysis is shown in Figure 5.11, where the main specie is the dimer assemble by disulfide bridge formation. The mass is calculated using the odd m/z (red circles), to avoid miscalculations with the monomeric form.

Thioflavin fluorescence

The thioflavin T (ThT) test [Nilsson 2004], is a simple test for detecting the presence of amyloid fibers. An increase in fluorescence intensity is observed when the amyloid-specific dye

ThT binds to the aggregate, thus indicating amyloid fibril formation.

The results obtained are shown in Figure 5.12, a clear increase of the fluorescence intensity is displayed for peptide 2 after the binding of ThT whereas no increase is observed for peptide The aggregation process was also monitored by small-angle X-ray scattering (SAXS). Figure 5.16 show the evolution of the SAXS curves over time indicating that large objects accumulate in the sample during the experiment. The curves present a typical pattern for an elongated cylinder as indicated by the q 1 slope in the intermediate q range. Figure 5.16: Fibril formation kinetics followed by SAXS on a 1 mg/ml peptide solution after 5% DMSO addition. Two hours exposures were collected sequentially during 24 hours and the solvent background was subtracted.

Data were analyzed using the program package PRIMUS [Konarev 2003]. The radius of gyration (R g ) and the cross-section radius of gyration (R XC ) were evaluated using the Guinier approximation, see table 5.2 and Figure 5.17. Proper range in q for the R g determination could not be used because of low signal to noise and the size of the considered objects. The cross section R XC can be estimated in the intermediate q region, the evolution of this value is given in the inset. The cross section radius of gyration of a homogeneous cylinder of radius r is p 2 2 r, in consequence, the measured value R XC = 2.26 ± 0.1 nm indicates a cylinder of a diameter 6.4 ± 0.3 nm in agreement with EM measurements considering the precision provided by the picture analysis. These results show unequivocally that the peptides generated from this conserved sequence of the NTD-AR undergo reversible amyloid formation, whereas the free peptides are mostly random. Aggregation is triggered by oxidative formation of a disulfide dimer, thus dimerization of peptides through a disulfide bond is the key event for further fibril formation.

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Influence of the oxidation conditions to the kinetics aggregation

It is important to study the effect caused on the kinetics rate of the aggregation by using different oxidant conditions. For this purpose, two different conditions were tested, the first N-terminal Domain of the Androgen Receptor one changing the pH to pH = 8, and the second one also at pH 8.0 but using H 2 O 2 + NaI. as oxidant. The aim of the pH increasing is to favor the thiolate formation for the Cys residue.

P SH pH8 ! P S -
A thiol with pK a 10 presents 0.1% thiolate form at pH 7, whereas 1% of thiol is in thiolate form at pH 8 [Singh 1993]. The thiolate is a stronger nucleophile than the thiol group and While looking into the kinetics we don't observe big differences with the standard conditions used and described above. However, the appearance of the cystine H , circled in red in Figure 5.18, is remarkable. This proton is shifted when the disulfide bridge is formed for the peptide dimerization. On the other hand the kinetics does not fit perfectly to a second-order kinetics.

A nucleation step can be also observed at the beginning of the curve. In this case, we can conclude that the increasing of the pH affects the kinetics behavior even while no effect is shown on the global duration of the aggregation. The differences in the kinetics are also emphasized with the fact that the dimer formation is observed by NMR, meaning that the dimerization is faster here allowing to see the dimer appearing before a later disappearance after aggregation. Looking into the NMR spectra, apart from a immediate dimer appearance, the oxidation of the Met can also be observed with the appearing of a 1 H signal at 2.65 ppm (circled in red in Figure 5.19 a). This oxidative conditions appear to be too strong for the peptide fibrillation.

Other constructs studied

After the first results on the kinetics aggregation for peptide 2, and looking into the conservation study performed in the N-terminal domain of AR shown in Figure 5.4. It was considered appropriate to study in detail the influence of the sequence length for the aggregation process, we wondered if there is a peptide shorter than peptide 2 that could also aggregates under oxidative conditions or if on the opposite, there is a maximum on the length of the native conserved region that could not further aggregate.

For this reason, four peptides with different lengths around the residue C240 (from the highest conserved region in the NTD-AR), where chosen to study their behavior by NMR Chapter 5. Biophysical characterization of a high conserved peptide from the N-terminal Domain of the Androgen Receptor under oxidative conditions. All peptides shorter than peptide 2 did not show any aggregation, whereas all longer peptides exhibited aggregation, with kinetics equivalent to the one studied for peptide 2. The mutated sequence 6 Cys to Ser, didn't show any effect as expected where removing the cysteine and no disulfide bridge can be formed. The shortest peptides, 8 and 9, only dimerized in the presence of DMSO, and the dimer remained stable in solution after more than 24 hours.

Conclusions

The results described in this chapter show unequivocally that the peptides generated from this conserved sequence of the NTD-AR undergo reversible amyloid formation. Peptide aggregation is triggered by the oxidative conditions, where the peptide dimerization, through a disulfide bridge formation, is the key point for the fibrils formation.

Chemical triggered fibril self-assembly has already been reported, either by changing the hydrophobic behavior [Abul-Haija 2013] or by using a template strategy [Rubinov 2012], but to our knowledge, not by oxidation. Aggregations of fiber structure, in response to disulfide formation, are known in the literature [Rubinov 2009, Carnall 2010], however the mechanism involved here seems different. The primary sequence (KELCKAVSVSM), alternates hydrophobic and hydrophilic residues, which is common in proteins prone to fibril formation. Looking into the extended primary sequence of peptide 10 (TISDNAKELCKAVSVSMGLGVEALEHLS),the hydrophobic-hydrophilic alternance continues. It is probably the position of an active site. N-terminal Domain of the Androgen Receptor

It was shown that the mutation of some hydrophobic residues within this sequence have a dramatic effect on the receptor activity [Betney 2003].

The kinetics displays a second-order behavior with respect to peptide concentration suggesting that dimerization is the limiting step. However, pseudo second-order kinetics are also known in sorption processes not involving dimerisation [Ho 1999], and a more complex fibrillation mechanism cannot be ruled out as disulfide bridge self-assembling systems are known to display complex evolution patterns [Carnall 2010]. The mechanism of proteins aggregation into amyloid fibrils usually involves a "lag phase" or nucleation step before the aggregation process starts. However the absence of a "lag phase" can be observed due to the presence of pre-formed fibrils [Nilsson 2004]. Additionally, the decay levels-off to a plateau around 0.1 mM suggests a possible equilibrium between the fibril and the free dimer.

The results obtained for peptides 8 and 9, where only a dimerization process occurs, suggest that the presence of the Methionine in peptide 2, could have an important role in the aggregation mechanism. The precise molecular structure of the dimer and the fibril is not yet determined and is currently under investigation and is included in the perspective work for this project.

The NTD of AR plays the central role for the activity of the receptor. It contains the activation domain AF1, which is necessary for full in vivo transcriptional activity of the receptor [Lavery 2008a]. As for many transcription factors, it has been shown to be in an intrinsically disordered conformation [Lavery 2008b], and to undergo allosteric disorder/order transition through its interactions with specific coregulatory proteins [Kumar 2012, McEwan 2012].

In humans, a PolyQ longer than 40 residues leads to androgen insensitivity and Spinal Bulbar Muscular Atrophy (SBMA); while a PolyQ shorter than 20 residues increases the risk of prostate cancer [Kumar 2011]. The PolyQ is known to be involved in AR aggregates [Palazzolo 2008].

Nevertheless, this study open new possibilities and the hypothesis propose here is that this conserved sequence could regulate the activity of the androgen receptor by redox control.

Presenting a reduced active formed, and an oxidate less active

On the other hand, this conserved motif from the NTD-AR has been studied previously and it is involved on the interaction with the heat-shock protein HSP70 [He 2004]. Finally, AR has already been reported to form disulfide dimers in cells, and to be responsive to redox treatment [Liao 1999]. N-terminal domain of the Androgen Receptor

Protein-ligand interactions: ligand based experiments

As in the case of protein based experiments, the ligand-based methods are established taking into account that upon binding to a protein, the individual tumbling rates of ligands in solutions will be altered. Small molecules display slow relaxations (T 1 , T 2 ) and fast diffusion. Upon binding to a protein, this properties dramatically change and decrease. These changes in the ligand properties can be observed in the NMR signals by different methods.

Relaxation experiments

One of the most used experiments for NMR binding assays is the comparison of the ligand's relaxation rate, in the absence and the presence of the protein target. Relaxation, that implies the movement of the bulk nuclear magnetization towards equilibrium, can occur through two different mechanisms (Figure 6.2). Thermal equilibrium, is the mechanism of the recovery of the nuclear spin exchanges energy with its lattice (environment) to return to its basal state. In that case the relaxation rate mechanism R 1 (longitudinal relaxation rate) occurs at a similar rate for small and large molecules. On the other hand, the selective R 1 occurs when a restricted set of protons is saturated or inverted using a selective frequency (as in the STD experiment).

In this case, R 1 present a !⌧ c dependence and is a sensitive probe of binding.

The second mechanism, depends on the size of the molecule such that relaxation becomes more rapidly with the increasing size of the molecule. The relaxation rate via a spin-spin mechanism is called R 2 (transverse relaxation rate) and occurs faster for large molecules (slowly N-terminal domain of the Androgen Receptor tumbling) [Skinner 2008]. Figure 6.2 shows that for small molecules R 1 and R 2 have similar values, whereas for large molecules, the transverse relaxation becomes larger and the longitudinal relaxation decreases. The shape of the Free Induction Decay (FID), is controlled by the transverse relaxation, a large R 2 results in a FID that decays rapidly. Consequently, faster relaxing species produce broader NMR signals, less resolved peaks appear in the spectrum. This is the effect that can be observed when a small molecule binds to a protein target, the small molecule adopt the NMR properties of the large molecule, assumes fast transverse relaxation rates and the consequence is the spectral line broadening of the small molecule signal [Pellecchia 2002a].

Diffusion experiments

The diffusion coefficient can be measured by NMR using DOSY experiments (see Chapter 4).

This measurement can be a convenient way for the study of a ligand-protein interaction [Skinner 2008].

When recording a DOSY experiment for small molecule alone and after adding the target protein, notable differences are observed. The ligand bound to the protein presents a slower diffusion coefficient and their NMR signals intensities are less attenuated in the DOSY experiment for high intensity gradients. In the case of strong binding, ligand and protein signals present the same apparent diffusion coefficient after binding. By selecting a suitable gradient N-terminal domain of the Androgen Receptor strength, it is possible to filter out the unbound ligands, because of their fast diffusion, and the bound ligands will be selectively detected from the mixture. However, fast R 2 makes this approach difficult to implement. In the case of weak binding, because of the equilibrium between the free and the bound species, the diffusion of the ligand is modified, and the diffusion coefficient reflects the protein diffusion, in proportion to the amount of bound ligands.

Diffusion experiments follow the same basic principles as relaxation experiments but rely on differences in translational instead of rotational motions.

Exchange Transferred NOEs

The The ligand protons undergo additional dipole-dipole interaction with protein's protons, upon binding to a large molecule. As said before, the ligand adopts the tumbling properties of the large molecule and here the binding is detected by the NOEs developed intra ligand upon interaction, when a strong dipole-dipole interaction occurs. The negative NOE cross peaks characteristic of small molecules become positive, indicating the ligand binding with the protein target [Skinner 2008].

Saturation transfer difference (STD)

The STD experiment has its basis in the intermolecular magnetization transfer between the ligand and the large molecule through the NOEs as occurs in the NOE experiment. In the STD experiments the protein target resonances are saturated selectively, the protein is saturated with radio frequency pulses (to reach a saturated steady state). At that point, ligand spins that are close to the saturated protein, receive part of this saturation through intermolecular 1 H-1 H cross relaxation pathways, and the ligand signal intensity decrease in the 1D NMR spectrum [START_REF] Mayer | [END_REF]] probing the ligand-protein binding.

As shown in Figure 6.3, a selected 1 H spectral region of the protein is saturated in the "on" resonance experiment (methyl region near 0 ppm). After that, a second region far from the protein 1 H spectral range is saturated as "off" resonance experiment. The difference between the resulting spectra shows the magnetization transfer from protein to ligand protons.

The optimal conditions for the STD experiment consists in a complex with a k of f on the same order of magnitude as the intermolecular saturation transfer rate, and to optimize the Water-Ligand Observation via Gradient SpectroscopY (WaterLOGSY)

The WaterLOGSY experiment is an adaptation of the STD method. In both experiments the objective is to observe the transfer magnetization to the bound ligand and to compare the differences with the spectrum of the unbound ligand. In the case of the WaterLOGSY experiment [Dalvit 2000, Dalvit 2001], the transfer occurs indirectly through the excitation of the bulk water magnetization. The excited water molecules interact with the ligand-protein complex and then transfer the magnetization. This magnetization will be selectively retained by the free ligand, after dissociation (Figure 6.5 a). In the WaterLOGSY experiment the determination of an optimal "on" resonance is less important than in the STD experiment [Antanasijevic 2014].

An alternative important mechanism for explaining magnetization transfer from water to the complex, is the transfer by the labile groups (-NH and -OH) through chemical exchange.

However, in both cases the pathway for the transfer magnetization conserves the same sign of the bulk water, and the non-bound ligands will appear with the opposite sign compared to the water signal (Figure 6.5 b). For all these reasons, the strategy is to show that the amyloid fibers, formed upon oxidation of peptide 2, can be a target site for all these new molecules. Moreover, the fibers analyzed in this work could present a biological role, for this reason some other related hormone involve in the AR activity are studied. As well as, some polyphenols due to their antioxidants properties and their effects in the androgen receptor activity and expression [Ren 2000[START_REF] Ferruelo | Effects of resveratrol and other wine polyphenols on the proliferation, apoptosis and Bibliography androgen receptor expression in LNCaP cells[END_REF]].

123

Chapter 6. Small molecules interactions study with a high conserved peptide of the N-terminal domain of the Androgen Receptor 6.2 Fibers-molecules interactions

Molecules influence on the kinetics aggregation

A first step of the interaction study is to characterize the influence of the BPA derivates molecules, in the kinetics of the fibril formation. In order to check if the presence of the small molecules had an impact in the aggregation, inhibiting the fibril formation or accelerating this N-terminal domain of the Androgen Receptor phenomenon, the NMR signal of the mixture (peptide 2 + small molecule) was monitored during 70 h. The reactions were performed in presence of 5% DMSO.

Four different molecules were tested, Bisphenol A, EPI-001, EPI-056 and EPI-sym. As it can be observed in Figure 6.9, in all cases the presence of a small molecule alters the aggregation rate. The kinetics were compared with a peptide aggregation kinetics without the presence of molecules in solution (Figure 6.9 black dots). It is remarkable that, not only the signal disappearance occurs faster when adding the molecules, but also the aggregation does not fit well a second-order kinetics anymore. 127 Chapter 6. Small molecules interactions study with a high conserved peptide of the N-terminal domain of the Androgen Receptor

WaterLOGSY (WL)

The WaterLOGSY (WL) is the alternative to the STD to find interactions between the fibers and different small molecules that could have an important role with the androgen receptor regulation and prostate cancer new therapies. We can organize them in three groups: BPA derivates, hormones and polyphenols.

The first step was to perform a WL control-study of the molecules (See Appendix C). The results of these experiments show that all molecules alone in solution (with 5% DMSO) exhibit a negative (-) response (or 0), as expected, except for EPI-001 that shows a positive (+) response in the WL spectrum. This "false" positive could be associated with the low solubility of the molecule in water and the formation of colloids in the solution can induce to misleadings.

A decrease in the concentration of this molecule lead to a spectrum with 0 response proving the hypothesis above (See Figure 6.14).

In a second step, a study was performed by adding the different molecules to a solution with the peptide after oxidation. All the molecules tested displayed a (+) response in the WL spectrum except Chloramphenicol (-) (see Figure 6.13). Chloramphenicol is an aromatic antibiotic that was chosen as negative control for this interaction study, and the results confirmed that.

Figure 6.13: Peptide 2 after oxidation + chloramphenicol 1 H spectrum (black) and WL spectrum (blue).

Chapter 6. Small molecules interactions study with a high conserved peptide of the N-terminal domain of the Androgen Receptor

As EPI-001 is the molecule of interest in our research project due to its role as potential new therapeutic drug for prostate cancer. Here we show the main results proving the interaction and affinity of the molecule with the fibers formed in solution.

Figure 6.14 shows the control study of the molecule EPI-001 alone in solution.

In Figure 6.15, the WL response of the molecule is shown once in solution with the fibers formed after peptide oxidation (24 h). In this case we obtain a (+) signal, indicating the interaction between fibrils and molecule. After that, the sample was recovered from the NMR In Table 6.1 are summarized the results obtained for all the molecules tested in this study.

The results are compared between the control experiment with the different molecules alone in solution or in the presence of amyloid fibers from peptide 2. Is remarkable the positive response of all molecules in the presence of fibrils in solution, with the exception of chloramphenicol and DMSO. For this reason DMSO is used in all the samples as a internal control. This situation indicates that more (-) response molecules are needed.

Chloramphenicol (-) (-) EPI-001 (0) (+) EPI-056 (0) (+) EPIsym (-) (+) BPA (-) (+) Catechin (-) (+) EGCG (-) (+) Resveratrol (-) (+) DHT (-) (+) Testosterone (-) (+) Estradiol (0) (+)
Chapter 6. Small molecules interactions study with a high conserved peptide of the N-terminal domain of the Androgen Receptor

EPI-001 + KELCKAVSVSM: covalent bond formation

A different strategy can be used to study the possibles interactions between the new CRPC drugs and the highly conserved peptide from the NTD-AR. As has been proposed in the literature [Myung 2013], EPI-001 probably interacts with the NTD-AR through a covalent interaction. The mechanism proposed involves a first fast reversible interaction between EPI-001 and the AF1 region of AR to place the secondary alcohol of the molecule close to a basic site in the NTD-AR. In a second step, the base can remove the proton of the secondary alcohol of the chlorohydrin with the consequently epoxide formation, through the loss of a chloride.

The highly reactive epoxide reacts with a nucleophilic site on an amino acid side chain in the AF1 to form an irreversible covalent bond.

In order to characterize this interaction and to search for a possible adduct formation between the peptide 2 and EPI-001, a coupled LC/MS/NMR experiment was thought as an effective strategy to characterize the reaction.

LC/MS/NMR

The use of an integrated LC/MS/NMR system can provide additional information and structural identity of the mixture we are analyzing. LC-SPE NMR and mass spectroscopy go especially well together, provide the advantages of each one of the techniques and furthermore it is a closed system. LC/MS/NMR coupled system allows an ultra-sensitive screening in complex mixtures, followed with an NMR structural characterization. The SPE (solid phase extraction) interfaced between LC and NMR allows the usage of completely non-deuterated solvents for the elution of the chromatic fractions collected into the NMR capillary. This is a good system to avoid the pollution or the loss of sample.

This technique has a wide range of applications but is mainly used in pharmaceutical and biotechnology industries for the study of natural product extracts, combinatorial peptides mixtures, food extracts or polymers.

We applied this method to search and to characterize the covalent interaction between EPI-001 and peptide 2. The sample was prepared in basic conditions, pH = 8.0, to favor the thiolate formation and to accelerate the covalent bound formation. The hypothesis is that the peptide and the molecule can form an adduct as shown in Figure 6. For a complete characterization, as a final step the sample was collected in the SPE cartridge (solid phase extraction). The cartridge was dried and posteriorly it was eluted to the NMR spectrometer capillary with acetonitrile-d 3 . Unfortunately, the NMR information could not be obtained due to the low concentration of the adduct in solution and the sensibility limitations of the equipment. Nevertheless, an additional experiment was performed by using the 700 MHz cryo-probe TXI. The sample from the NMR capillary was recovered and used on the 700 MHz. To prove the covalent interaction we need to find a correlation peak between the cystine-H and the C of the EPI-001 directly attached to the cysteine, see Figure 6.16 a) marked in green. The NMR experiment required to find this correlation, is the HMBC experiment (Figure 6.17), that gives the information of long range heteronuclear correlation.

However, it is a low sensitivity method and together with the low adduct concentration, make that the starting conditions are not the ideal to perform the experiment. The HMBC spectrum did not show any peak at cystine-H frequency. Chapter 6. Small molecules interactions study with a high conserved peptide of the N-terminal domain of the Androgen Receptor

HMBC

Conclusions

Endocrine disruptors alters androgen receptor function [Luccio-Camelo 2011]. This study aimed to study the influence of small molecules in the amyloid fibril formation of peptide 2 and their possible interactions. EPI-001, the new potential drug for prostate cancer, is a derivate of the well known endocrine disruptor Bisphenol A (BPA). Here we have shown that the BPA derivates family of small molecules accelerates the kinetics aggregation of the amyloid fibers. Furthermore, BPA have been reported in literature to speed-up the toxic amyloid formation [Gong 2013]. This result goes in the same direction than the study presented here and can open new lines of research for controlling amyloid aggregation.

WaterLOGSY is a higher sensitivity method compared with STD [Antanasijevic 2014]. We present a system with special difficulties compared to standard globular proteins. Specially with the absence of an aromatic moiety in the fibers (KELCKAVSVSM), where the optimal saturation frequency is not easy to determine. Using the WaterLOGSY experiment we show that the amyloid fibers formed after oxidation of the peptide 2, interact with three different categories of molecules: hormones, polyphenols, and EPIs, the new potential drugs for the prostate cancer.

These latter molecules result as derivates of a well known endocrine disruptor, Bisphenol A, which also display a positive response as result of the interaction with the fibrils.

Finally, the mechanism of action of the EPI-001 within the NTD-AR, is proven in part with this study. A covalent interaction is characterized by HPLC/MS. The covalent interaction, formed through the Cys and the EPI-001, was not characterized by NMR. The low sensitivity of the HMBC experiment together with the low concentration of the adduct precluded its characterization. A perspective on this study is to carry out new experiments, such as MS fragmentation, to complete the characterization of the adduct formed between the peptide 2 and the EPI-001.

All together, in this chapter has been shown that, the high conserved sequence from the NTD-AR does not only aggregates into amyloid fibers under oxidative conditions, this could also be a target site for the new potential drugs.

Chapter 7

Amyloid fibers formation followed by p-DOSY Fibrillation in Amyloid-diseases have been widely studied. Inhibiting amyloid fibril formation is the primary therapeutic strategy for amyloid-related diseases such as Alzheimer [Estrada 2007, Peng 2015].

Fibrillation seems to occur via prefibrillar conformers. Two different nature of these intermediates have been proposed, fibrillation from denatured proteins state [Hamley 2007] or partially folded intermediates (usually rich in -sheet conformation) [START_REF] Vladimir | Conformational constraints for amyloid fibrillation: the importance of being unfolded[END_REF], Gerum 2009].

The fibers formation process that has been proposed, commonly for most of amyloidsystems, is fibrillation after a lag phase. This mechanism suggest a nucleation step followed by a rapid growth process. On the other hand, this fibrillation kinetics can be modified with the addition of seed. This action can eliminate the lag time in the fiber formation process as seen in Figure 7.1.

Chapter 7. Amyloid fibers formation followed by p-DOSY Many other factors, such as pH, temperature, stirring or initial monomeric concentration may affect the fibrillation kinetics. It has been shown that agitation and sonication can affect, not only the kinetics of the fibers formation, but also to its morphology and its toxicity [Petkova 2005, Lee 2007b, Knowles 2014].

The prefibrillar aggregates are soluble oligomer that appear to be the major toxic agents in several degenerative disorders [Lee 2007b]. The structural plasticity associated with amyloidproteins could lead the appearance of different oligomer structures [Glabe 2008]. This inherently misfolded nature could be the origin of its toxicity, as they display on different chemical surfaces that under normal physiological conditions [Campioni 2010], that can cause undesired interactions with new partners. Specially, their highly hydrophobic surfaces can induce aberrant interactions with other cellular components with its consequence damage. As aggregation produces an array of different oligomers, various types of toxic species can be expected [Knowles 2014].

Aggregation kinetics followed by p-DOSY

Previously, in Chapter 5 the kinetics aggregation of the peptide KELCKAVSVSM followed by 1D 1 H NMR has been characterized. In that case, the signal disappearance from the 1D spectrum was measured. The structural information that was obtained from that study was the dimerization of the peptide through a disulfide bridge formation triggering the formation of amyloid fiber.

In order to better characterize the aggregation phenomenon and to study the possible presence of larger oligomers in solution before the aggregation, and further disappearance from the NMR the kinetics of oligomerization was followed by p-DOSY. This experiment, presented in Chapter 4 allows the precise determination of diffusion coefficients for out-of-equilibrium systems. This experiment allows the detection and characterization of the appearance of the dimer and different oligomers in solutions, with different diffusion coefficient.

The use of the p-DOSY experiment instead of traditional DOSY is to avoid possible artifacts or bias in the diffusion coefficient due to the concentration variation of the monomeric peptide form while acquiring the experiment, and as consequent misinterpretation of the results (as seen in Chapter 4).

The kinetics was monitored during 50 hours, with 2.5 h p-DOSY experiments alternated with 1D 1 H spectra zgpr.

The results of the evolution on the peptide diffusion coefficient (D) during the kinetics aggregations are shown in Figure 7.2. A decreasing of the apparent diffusion coefficient is monitored during the firsts 40 hours. This result indicates that new bigger species are appearing in solution.

Looking into the spectra, a difference on D can be easily observed for the Cys residue.

While all protons signals evolve with the same rate and with the same diffusion, the peaks at 2.86 ppm and 3.15 ppm evolve in a different manner. It can be observed in Figure 7.2, where the signal marked in dashed green, corresponds to the Cys-H of the monomer and the signal marked in dashed orange refers to the Cys-H of the dimer. This shows that the monomer and the dimer are stable during the kinetics, and do not form complexes of intermediate size.

The other signals from the peptide are showing a varying D, it comes from the fact that they are measured as the superimposition of the signals of the monomer and the dimer. Due to this superposition, and the small difference between the D of both species, the apparent diffusion coefficient which is measured on this superposition is a weighted sum of the abundance of both species, and thus "weights" the ratio monomer to dimer.

Analysis and fitting of the Diffusion coefficient (D) evolution

The diffusion coefficient of an objet is related to its molecular mass. D / M 1/↵ where ↵ is the fractal dimension [Augé 2009]:

D 1 D 2 = ✓ M 2 M 1 ◆ 1/↵ (7.1)
Where D 1 and D 2 are the different diffusion coefficient of the molecules compared and M 1 and M 2 , their respective molecular masses. This eq 7.1 is related to the Flory theory for polymers where the gyration radius, R g = M and is the inverse of the fractal dimension.

Flexible random chains have an alpha comprised between 3 (compact chain), and 5/3 (largest possible extension of a random walk), with 2 for a purely gaussian random walk.

In the absence of structural information, an alpha around 2 is usually chosen. The fractal dimension can be comprised between: 5/3 < ↵ < 3.

To analyze the variation of the apparent diffusion coefficient it is important to consider a correction for viscosity variation due to the appearance of fibrils in the solution. For this reason, a correction of D is performed regarding the diffusion coefficient of DMSO. DMSO is experiencing the same viscosity changes in solution nevertheless it is not experiencing any other interaction. From the analysis of the D evolution by time, a 30% modification of the peptide diffusion between the first and last point of the kinetics is found. This effect was analyzed to estimate the difference in size of the specie in solution. And the result is that a dimer is appearing in solution. This corresponds to a mass increment of 1.7 for ↵ = 2 (1.7 (1/2) = 1.3)

which is not feasible. The formation of the dimer corresponds to ↵=2.6 which is a bit high, but corresponds nicely to the value found for structured proteins [Augé 2009]. In any case, the formation of a larger soluble oligomer can be fully ruled out.

The kinetics curve (Figure 7.3) obtained for D is fitted with an exponential law, as follow:

D(t) = D mono exp( k oligo t) + D oligo
The results of the fit are shown in These results put in evidence that the kinetics aggregation recorded by p-DOSY (1st order kinetics) and the kinetics aggregation followed by standard 1D 1 H (2nd order kinetics) does not display the same behavior.

Peptide vs Cysteine kinetics

In order to complete the characterization of the different kinetics laws. The 1D spectra recorded after each p-DOSY experiment were analyzed. From them was extracted the kinetics for the peptide concentration disappearance by time (using the methyls integrals as in Chapter 5 and 6). But also the kinetics of the disappearance of the Cys-H signal (Figure 7.5).

In Figure 7.6 is shown the evolution of the soluble forms of the peptide concentration during the 50 hours of kinetics. The curve follows a second-order law and the kinetics does not follow an exponential law. These results are equivalent to the ones shown in Chapter 5.

Nevertheless, Figure 7.5 shows the evolution of the cysteine protons, close to the disulfide bridge formation, during the kinetics. This time, the curve does not follow a second-order kinetics and fits perfectly to a first-order reaction with an exponential law.

The results of the fit are shown in Figures 7.5

Conclusions

This chapter put in evidence the coexistence of two independent mechanisms. The fact that the p-DOSY experiment, where is followed the appearance of bigger objects in solution, displayed a exponential kinetics. Together with the same behavior found for the Cys signal in the 1 H 1D experiment, where the concentration of the peptide is followed by time. These two results

enhance the existence of a different mechanism for they dimerization step where the cysteine is involved through the disulfide bridge formation. Whereas the aggregation of the monomeric form into fibers, follow the second-order kinetics described until now in this study. Finally, the evolution of the diffusion coefficient indicates that the bigger object that is formed in solution before aggregation is the dimer and no soluble large oligomers are detectable by NMR. This means that either there are none, or that there are large and rigid oligomers, with T 2 too short to be detectable by DOSY/NMR. The DOSY sequence, with the spin echoes, acts as a T 2 filter, filtering out the larger lines, so linewidths (and corresponding T 2 ) of a few dozen Hz will be enough to give vanishing small signals in DOSY. For an observation at 700MHz, these linewidths correspond to molecular systems in the 10-20kD range and larger, excluding tetramer and larger soluble oligomers. This give new crucial information for the development of a model for the fibrillation of this peptide. Within these large multiple-component systems, many parts interact in a non-linear manner and the weak interactions between their parts are crucial for the development and the emergence of new properties.

In this hierarchic of molecules organization we focus now on a simple organization in chemistry, such as solvents.

These, a priori, simple systems can develop and adopt different complex conformations under different conditions that could affect to further analysis of experimental results. For this reason, we investigate here the acetonitrile-water mixture, which represents the most used mixture of solvents in chemistry and displays a non-well known behavior at low temperature, nowadays, still difficult to interpret.

Introduction

Acetonitrile is one of the most important solvents for all the chromatographic methods and specially in pharmaceutical industry. So much so that its recovery from waste has been investigated [McConvey 2012]. It is perfectly miscible with water and this mixture is commonly used at ambient temperature. This systems is supposed to be well known and well biophysically characterized for its wide used in chemistry, nevertheless it displays a strange and special behavior at low temperature.

Running NMR experiment in a deuterated acetonitrile-water mixture, one of us noticed that temperature variations below circa 10 C could lead to the loss of the deuterium lock and to strong spectral artifacts. This strange phenomenon could be attributed to a known anomaly of the acetonitrile-water mixture at low temperature. The acetonitrile-water mixture has been described to undergo a phase transition around 0 C, for a range of acetonitrile mole fraction

x AN from 0.2 to 0.6, characterized by a spontaneous phase separation below an upper critical solution temperature (UCST). UCST was shown to raise by several degrees in deuterated solvents and the complete phase diagram has been determined [START_REF] Szydłowski | Isotope effect on miscibility of acetonitrile and water[END_REF]].

This transition has been investigated by Small Angle X-Ray and Neutron Scattering [Takamuku 1998, Takamuku 2001, Takamuku 2007], spectroscopic techniques, [Bertie 1997] and computer modeling [Mountain 1999] (see [START_REF] Marcus | The structure of and interactions in binary acetonitrile + water mixtures[END_REF]] for a comprehensive review).

However, none of this studies showed an effect as massive as the one observed by NMR, for this reason, we decided to study further this behavior using NMR spectroscopy.

In order to characterize this phase transition and the possible structure of the mixture at low temperature a series of different NMR experiments are acquired.

Results

1D 1 H experiments and Isotopic effect

In order to characterize this phase transition and the possible structure of the mixture at low temperature a series of different NMR experiments have been acquired.

Above the transition temperature, the acetonitrile-water mixture presents a very simple NMR spectrum composed of two singlets, with the water signal located around 4 ppm and the acetonitrile signal around 2 ppm, the details of the spectrum depending on the molar ratio and on the temperature at which the experiment is recorded. The 1 H spectrum of the deuterated species shows the residual protonated species, and the acetonitrile displays a 1-2-3-2-1 coupling pattern, typical of the coupling of the proton with 2 deuterons.

When gradually lowering the temperature, at the transition temperature, a large modification of the spectrum appears, with a splitting of the two solvent lines and patterns appearing, reminiscent to solid-state powder patterns. The experiment was recorded for the mixture of the protonated and the deuterated solvents, and are shown in Figure 8.1. These figures present the 1 H spectra, but the 2 D spectra recorded in the same conditions are equivalent.

The splitting of the signal shows that the system is separated in at least 2 independent phases. The powder pattern observed for these lines is the signature of an orientational anisotropy. There are presented with opposite forms, and the width of the pattern was observed to extend up to about 250 Hz for the lower temperature. The fact that both water and acetonitrile present the same patterns could indicate the system is a liquid-liquid phase separation, where each liquid is a mixture of water and of acetonitrile.

The patterns obtained are not fully reproducible, and depend not only on the molar ratio but also on the spectrometer, the tube diameter and the speed at which the temperature is cooled down. It is probably related to the homogeneity of the temperature over the sample volumes.

After several trials, the best results were obtain on 3 mm NMR tubes, in a regular TXI 5 mm probe, operated on a 500 MHz instrument. When varying the temperature several time below and above the transition, it was observed that the system could retain at high temperature some memory of the low temperature details. This memory could easily be destroyed by pulling the sample tube out of the spectrometer and shaking it before putting it back.

Phase diagram

The transition observed in the NMR spectra is very characteristic and can be followed carefully. AcCN-water 75%-25% 3mm tube 500MHz

DOSY

The DOSY experiment is used for measuring diffusion coefficients of the species in solution.

The experiment is not very easy to perform on broad lines, nevertheless three components can be observed in the DOSY, with the same pattern in the water and acetonitrile lines.

Figure 8.5 shows the DOSY spectrum obtained for the acetonitrile-water mixture (65% v -35% v ). We can distinguish three different behaviors, one narrow line with a large diffusion coefficient, comparable to the free fluid; and two different coefficients for the left and right "horns" of the powder pattern for both water and acetonitrile, with values corresponding to much more viscous fluids.

We could not detect signs of non-exponential decay in this experiment, which you hint to diffusion taking place in a volume restricted to the mean displacement path explored by this experiment, on the order of 5 µm for the slow coefficients and 10 µm. This indicates that the phase domains are quite smaller than this order of magnitude.

With the display of these three different diffusion coefficients, this experiment tends to proves that three different liquids are present in the sample, two complex mixed phases, and a free bulk isotropic phase. Again, the exchange between the three media is slow, as the diffusion coefficients, measured here over a diffusion delay of = 50 msec are not blurred by exchange 165 Chapter 8. NMR study of spontaneous Acetonitrile-Water demixing over this period.

• two di erent coe cients for the left and right "horns" of both water and acetonitrile , corresponding to relatively viscous fluids. Looking to the DOSY acquisition we noticed a strange behaviour, associated to the gradient strength.

It is known that in a structured heterogeneous sample, the e ect of dipolar field created my the induced magnetization through the sample does not reduces to zero. This so-called distant dipolar field (DDF) creates non-linear e ect through the sample, which are very sensitive to local organization of matter. These e ects are sometimes called intermolecular multiple-quantum coherences (iMQC).

This has been studied, in a very polemic context, in particular by W.S.Warren since 1990, who has developed the CRAZED (COSY revamped by asymmetric Z-gradient) approach. It can for instance be used as a source of contrast in MRI. It has also been studied by D.Gruker here in Strasbourg (see [?]).

We investigated this aspect by running a strange sequence, that should have no e ect on a regular sample (Figure 5). This sequence is slightly di erent from the CRAZED. This sequence, on a homogeneous sample, should produce a complete signal extinction as soon as the gradients are strong enough. Here, when varying the gradient intensity, even to high values, we obtained strong modulation of the line shape. Figure 6. This modulation is very di erent from what is described in the literature for the CRAZED e ect, and presents much more structures. However, we believe that it is nevertheless related.

CRAZED

It is known that in a structured heterogeneous sample, the effect of dipolar field created my the induced magnetization through the sample does not reduces to zero. This so-called distant dipolar field (DDF) creates non-linear effect through the sample, which are very sensitive to local organization of matter. These effects can lead to additional echoes and are sometimes called intermolecular multiple-quantum coherences (iMQC). This has been studied, in particular by W.S.Warren since 1990, who has developed the CRAZED (COSY revamped by asymmetric Z-gradient) approach, and the full understanding of this effect is still under discussion. It has been used as a source of contrast in MRI ( [Richter 2000, Branca 2009]) and can lead to diffraction-like patterns in the NMR experiments (see [de Sousa 2004]). CRAZED experiment was performed as detailed in Figure 8.6.

In the CRAZED experiment, multi-spin states, coupled through space by DDF create multiple-order n-order quantum resonance after the first P 90 pulse. The second P 90 pulse converts the multi-order states to detectable single quantum states. The detection being sensitive only to 1 spin-order, the ratio of the two gradients selects which coherences are sampled during the t 1 delay. This delay is regularly incremented, and the Fourier transform allows measuring the frequencies of the otherwise undetectable multiple order states. the line ! 1 = +2! 2 . corresponding to 2-spin order. Surprisingly, signals are also observed on the other diagonals. In the case of the experiment with a gradient ratio G 2 /G 1 of -2, only signals located on the line ! 1 = 2! 2 can be observed. The experiment with a gradient ratio G 2 /G 1 of 3 is similar to the one with a ratio of 2, but the larger peaks are now located on the ! 1 = 3! 2 line. The experiment performed with both gradient inverted for the same ratio, are equivalent to the one presented here.

These spectra are the signature of multiple spin order created through the DDF effect, are Looking to this picture, several striking features appear. In this spectrum, the structure of the powder pattern in both massifs is much easier to decipher. The splitting for water and acetonitrile appear equivalent, as well as the shape present in the STRANGE spectra, with simply an inversion of the position. The system is very regular and organized, and the linewiths are very narrow, for instance, the acetonitrile coupling pattern is fully visible every where -whereas the 1D spectrum is indistinctly broad.

There are also non modulated signals (the only one that would appear in an homogeneous sample) pointed with an arrow symbol in the figure. This homogeneous medium seems to appear only in one of the two phases.

It seems to show that there are several superposed structures, and the same features, that we we call "trajectories" can be found similar on both water and acetonitrile. The same tree different "trajectories" on the left pattern of water and right for the acetonitrile can be isolated. Also, two different "trajectories" on the right pattern of water and left for the acetonitrile are seen, and a possible additional signal around 4.05 ppm for the water (1.90 ppm for the acetonitrile) On the right (left) pattern of water (acetonitrile) it seems to be two additional patterns: i) the homogeneous line ii) a kind of "comma". In contrast with the other features, these two additional patterns appear unchanged in the positive and negative gradient experiments (see below).

We do not have yet any explanation for the pattern appearing in the STRANGE experiment. However, if the chemical shift (horizontal axis) is modulated by some angle, and if the STRANGE effect (vertical) is modulated by the local structure, then this experiment contains information on the structure of the phases of the mixtures.

The inversion of the coding gradient modifies completely the pattern (Figure 8.11), as if we were looking at two faces of the same object. On the inverted gradient experiment, three narrow lines appear at a negative frequency in the water region (nothing in the acetonitrile) (pointed with the single arrow in Figure 8.11)

Changing the second pulse of the STRANGE experiment from 180 to 90 does not modify the shape of the spectrum, but only lowers the overall intensities. Complete suppression of this second pulse and one of the gradients, results in an empty spectrum, where the STRANGE effect disappears. On the other hand, pulsing on the deuterium channel, in any manner, has no effect on the STRANGE spectra.

Unsuccessful experiments

Several other experiments were tested, but produced no result.

Conclusion

This work presents the analysis by NMR of a peculiar behavior of a simple liquid-liquid mixture under near room-conditions. While the anomaly of the acetonitrile-water mixture at low temperature was already known and qualified, its study by the mean of the NMR spectroscopy had not been undertaken yet. The particular structure of the liquid-liquid phase separation which takes place in this system leads to large perturbations in the 1D NMR spectra, indicating strong anisotropies in the liquid-liquid interphase. The other NMR experiments performed (DOSY, EXSY) show that the structured micro-domains are certainly long-lived, with very different physical properties (strong contrast in macroscopic diffusion coefficients). The CRAZED experiment produces spectra which show that many long-range spin-order are present in the system, leading to many intermolecular multiple quantum peaks. Moreover the STRANGE experiment, first introduced in this study, present striking features, yet unexplained. When tested on the SDS-water mixture, well known to form well characterized micelles, the same features were observed, with a much smaller amplitude.

The STRANGE experiment provide beautiful patterns, which have still to be interpreted.

These patterns are certainly due to couplings between the orientation of intermolecular vectors with respect to the magnetic field, and the chemical shift anisotropy tensor, the high resolution of the spectra showing that the local structure are very regular. The interpretation of this coupling might provide information on the local micro-structure present in the liquid. However the full interpretation of this effect requires the complete modeling of the quantum dynamic

  ) par moyennage. Cette approche, que nous avons dénommé p-DOSY ne nécessite pas de changements dans les séquences d'impulsions, ni dans le logiciel de traitement, et restaure complètement la précision totale de la mesure. Cette technique est illustrée sur le suivit de la réaction d'anomérisation de -en -glucose. Elle est parfaitement adaptée pour l'analyse des réactions chimiques et des systèmes hors d'équilibre et peut être utilisée pour surveiller le taux de la cinétique de réaction, pour caractériser les espèces transitoires in-operando et mesurer leur coefficient de diffusion, ou pour l'étude de phénomènes d'organisation moléculaires.

Figure 1 -Figure 2

 12 Figure 1 -Superposition de la DOSY standard (couleur bleue) et de la p-DOSY (couleur verte), acquises dans la période hors d'équilibre (0,00 à 25,00 minutes). On voit le biais de la mesure de DOSY entre les formes et pour la DOSY standard, corrigé par la mesure en p-DOSY.

Figure 3 -

 3 Figure 3 -Representation des differentes domains du récepteur des androgènes et la conservation de la séquence chez tous les vertébrés. Zoom sur la séquence du NTD parfaitement conservée.

Figure 4 -

 4 Figure 4 -A) Cinétique d'agrégation des fibrilles suivie par RMN. B) Image obtenu par microscopie électronique de les fibres amyloïdes avec la distribution de le diamètre de le fibrilles obtenu d'après l'analyse des images. C) Cinétique d'agrégation des fibrilles suivie par SAXS avec le radius de les fibres calculé.

Figure 6 -

 6 Figure 6 -Variation de la concentration de peptide suivie par RMN, en présence de BPA (jaune), EPI-001 (rouge), EPI-056 (bleu) et EPI-sym (vert). En noir la cinétique de le peptide sans molécules, comme contrôle, avec une cinétique de second ordre (ligne pointillée).

Figure 7 -Figure 8 -

 78 Figure 7 -Spectre de RMN 1D 1 H du mélange acétonitrile-eau à 6 C

[

  Robinson-Rechavi 2001]. They play a crucial role in eukaryotic differentiation, development and metabolic homeostasis[Ribeiro M D 1995]. The nuclear receptor proteins are composed as a single polypeptide chain with five different domains. A disordered N-terminal domain (NTD), which contains the activation function 1 (AF1) whose action is independent of the presence of ligand. A highly conserved DNA-binding domain (DBD) followed by a flexible hinge. The ligand binding domain (LBD) which contains the activation function 2 (AF2) and finally the C-terminal domain[Huang 2010]. Nuclear receptors according to their families, can form interactions with DNA as a monomer, homo-or heterodimer.

Chapter 2 .

 2 Figure 2.1: NTD-AR organization, presenting the location of the tryptophanes and of the homoresidues regions Q21, Q6, Q5, P8, Q5 and G24. L4 not shown here is positioned just Nter of Q21 (Figure from [Davies 2008]).

[

  McEwan 2011, Kumar 2011] In a study reported in the literature,[Reid 2002] it was shown by circular dichroism (CD) and controlled proteolysis, that some partial structure is present in the NTD-AR and is enhanced by the presence of osmolyte such as TFE or TMAO. The same work showed by fluorescence that the environment of the tryptophan residues located in the 400-530 region are affected by the length of the polyQ located in the 60-80 region, thus more than 300 residues away.The DNA binding domainThe DNA binding domain (DBD), is the central region of the AR, a cysteine-rich region from residue 556 to 623. This domain is highly conserved among the nuclear receptors family. DBD function is the recognition of response elements (REs), DNA regulation sites present in the promoter of target genes[Pawlak 2012]. The DBD mediates the AR-DNA binding as a dimer,

Figure 2 . 2 :

 22 Figure 2.2: Structural representation of AR agonists. Testosterone and Dihydrotestosterone (DHT).

Figure 2 . 3 :

 23 Figure 2.3: Structural representation of antiandrogens. Nilutamide and flutamide, both toluidide derivates. Enzalutamide a second-generation of antiandrogens.

[Fig. 2 .

 2 Fig.2. Mechanism of AR action. In classical AR signaling, in the absence of hormone, AR is bound by chaperone heat shock proteins (Hsps). In the prostate, testosterone is converted to 5α-DHT, which is the high affinity ligand for AR. Upon hormone binding, Hsp dissociates from AR allowing hormone-bound AR to dimerize, translocate to the nucleus, and regulate gene transcription in multiple ways. (1) AR binds to AREs (androgen response elements) on the DNA and recruits different co-activator complexes (i.e. SRC/p160, CBP/p300, etc.) that remodel the chromatin allowing general transcription factors and RNA Pol II to begin transcription. (2) AR, through a poorly defined mechanism that may include recruitment of proteins such as corepressors to AR at AREs, also can inhibit transcription. (3) AR also regulates transcription through a tethering mechanism by binding to other transcription factors (TFs) and recruiting additional coactivators to target genes. (4) In addition to classical AR signaling, AR can initiate extranuclear signaling. Activated, hormone-bound AR can interact with kinases (i.e. AKT, SRC) resulting in activation of a kinase cascade. The signaling cascade can activate other TFs in the absence of direct AR binding to the gene.

  , McEwan 2011, Myung 2013]. Furthermore, EPI-001 is a derivate of Bisphenol-A (BPA) molecule which is a well-known endocrine disruptor. A recent study [Delfosse 2012] shows that BPA act as partial agonists of estrogen receptors and also present an antiandrogen activity [Paris 2002]. The NTD-AR has long been known to have an important role in the transcription activity, and was shown to interact with the AR natural action, when over-expressed as a decoy protein in cancer cells and present an antitumor activity.

Figure 2 . 5 :

 25 Figure 2.5: Chemical structure of molecules EPI-001 and EPI-056. Molecules reported as new potential drugs for prostate cancer (See [Sadar 2011])

  on the tertiary structure[SYu 1994]. The signals obtained in the 250-300 nm region are due to the absorption, dipole orientation and the nature of the surrounding environment of the phenylalanine, tyrosine, cysteine (or S-S disulfide bridges) and tryptophan amino acids.

Figure 3

 3 Figure 3.1: Far UV CD spectra of different secondary structure patterns. ↵-helix (yellow), -sheet (blue); and random coil (red).

  3). And finally in the same Figure 3.3 is shown how the Pair distance distribution function provides information about the shape of the object.

Figure 3

 3 Figure 3.3: Different information domains of a particle size and shape from a SAXS plot.

Figure 3

 3 Figure 3.4: NMR sequence of the 1 H 1D.

  Figure 3.5: 1 H 1D spectrum of a peptide. The characteristics for the different H are highlighted in the plot spectrum.

1

  H-1 H 2D experiments

Chapter 3 .Figure 3

 33 Figure 3.6: NMR sequence for the TOCSY experiment.

Figure 3

 3 Figure 3.7: A) Nuclear Overhauser Enhancement (NOE) B) Graphical representation of the NOE as function of ⌧ c . Figure from [Kieffer 2011]

  Figure 3.8: Difference between the information obtained with TOCSY and ROESY experiments.

  2)This provides the basis for further measurements of D. Considering the pulse sequence proposed byStejskal and[START_REF] Stejskal | Spin Diffusion Measurements: Spin Echoes in the Presence of a Time-Dependent Field Gradient[END_REF]] represented in Figure4.1 a). A series of spin echoes with a increasing gradient field strength is measured. The mean molecule translational diffusion resulting from the Brownian motion, is acquired at the end of the second delay. A pulse gradient of duration and magnitude G is applied between the first 90 and the 180 pulses, it causes an additional dephasing of the magnetization that is now proportional to , G, and dependent on the z spatial position of each spin. Then the magnetization is inverted by the 180 pulse at time ⌧ , and a second pulse gradient, identical to the first one, is applied. If we have an hypothetic static system, that does not display diffusion, a complete refocusing of the magnetization is obtained. Nevertheless, in a real sample, spins move during the delay between the two gradient pulses ( ), as consequence of the self-diffusion. The molecular movement along the helix will scramble the magnetization if the mean path is larger than the helix pitch. This situation leads to an incomplete refocusing, and an attenuation of the signals is observed depending on the diffusion rate of the molecules. It can be described by an exponential law (eq. 4.3 for STE sequence -Figure4.1 b):

Figure 4

 4 Figure 4.1: DOSY NMR sequences, figure used from [Gilard 2011] publication. a) The original Spin Echo (SE) sequence b) The Stimulated Echo pulse sequence (STE) c) The bipolar pulse pair-stimulated echo-longitudinal eddy current delay (BPP-STE-LED) d) The OneShot experiment.

  Figure 4.1b) differs from the SE experiment by the the modification of the 180 pulse into two 90 pulses. Here, the second 90pulse is applied directly after the coding gradient and it builds a spatial modulation of the longitudinal magnetization along the sample z-axis rather than a transverse modulation as in SE. Being on the z-axis, this modulation does not evolve any further, except for diffusion and T 1 decay. The final 90 pulse restores along the y-axis the magnetization, which then produces a stimulated echo once refocused by the second PFG. The advantages of the STE sequence are that spins relaxation depends mainly on T 1 instead of T 2 , on the other hand the sensitivity is reduce by a factor of 2.4.1.3 Bipolar pulse Pair-Stimulated Echo-Longitudinal Eddy current delay (BPP-STE-LED)The bipolar pulse pair-stimulated echo-longitudinal eddy current delay (BPP-STE-LED) experiment (Figure4.1 c) is one of the most common DOSY experiment applied nowadays. Here, the STE experiment is further optimized with different improvements. The PFG are made bipolar, that means that they are applied in two opposite pulses, sandwiching a 180 pulse.

  Figure 4.1 d) brings further improvements to the standard STE pattern. The additional selection gradients allow the reduction of the phase program. In consequence, it presents a better stability against the experimental fluctuations and allows a simplification of the measure. Less signal averaging is required permitting a faster measure when the S/N ratio is not a limiting factor. Up to this point, the classical NMR sequences for DOSY experiments have been summarized, nevertheless new experiments have been developed to improve resolution. One of the main problems of a DOSY experiment is to extract the correct diffusion coefficient when signals overlap, and this commonly occurs in the study of complex mixtures.

Figure 4

 4 Figure 4.2: DOSY-HMQC spectrum, figure used from [Barjat 1998] showing the result of a 3D DOSY-HMQC experiment with the diffusion separation of the different components of a quinine mixture.

Figure 4

 4 Figure 4.3: 2DJ-IDOSY sequence, figure used from [Nilsson 2004] showing radio-frequency (RF) and PFG pulses, with vertical arrows indicating the gradient levels changed to vary the diffusion encoding; a delay, ⌧ , allowed for gradient stabilization after each gradient pulse.

Figure 4 . 4 :

 44 Figure 4.4: Pure shift proton DOSY sequence, figure used from [Nilsson 2007] showing radiofrequency (RF) and PFG pulses.

Figure 4 . 5 :

 45 Figure 4.5: Anomerization of ↵-Glucose to -glucose with proton numbering

Figure 4 . 6 :

 46 Figure 4.6: Proton assignment of a mixture of ↵, -D-glucose (42.7% ↵-D-glucose and 57.4% of -D-glucose) at equilibrium.

Figure 4

 4 Figure 4.7: 1D 1 H experiments from 0.00-6.00 hours, it means from 96.6% to 44.6% of ↵-glucose.

Figure 4 . 8 :

 48 Figure 4.8: Overlay of two standard DOSY experiments, acquired between: a) out-ofequilibrium (0.00-25.00 minutes) (dark blue) and b) at equilibrium (5.41-6.05 hours) (light blue).

Figure 4 . 9 :

 49 Figure 4.9: Overlay of two p-DOSY experiments, acquired between: a) out-of-equilibrium (0.00-25.00 minutes) (dark green) and b) at equilibrium (5.37-6.00 hours) (light green).

Figure 4 .

 4 Figure 4.10: Overlay of the standard DOSY (blue color) and the p-DOSY (green color) experiments, acquired both at out-of-equilibrium stage (0.00-25.00 minutes).

  Figure 4.11 by the evolution of the error bars on the p-DOSY determined diffusion coefficients. The error bars present a somewhat larger spreading in the beginning of the kinetic and converge toward a minimal value.

Figure 4

 4 Figure 4.11: a) concentration evolution of ↵, -glucose over experimental time, measured as the intensity of the anomeric proton peak based on 1D experiments interleaved during the p-DOSY experiment series; b) evolution of the apparent diffusion coefficients of ↵ and -glucose over experimental time based on a series of sequential conventional DOSY measurements; c) same as b, obtained with the p-DOSY experiment. In b) and c) the horizontal doted line is located at the diffusion coefficient of ↵-glucose, measured as the mean value of p-DOSY value over the whole kinetics. 71

  analysis of the NTD-AR . . . . . . . . . . . . . . . . . . . 82 5.2 Biophysical characterization of different peptides from the NTD-AR . . 86 5.2.1 Peptides study by NMR: A first structural identification. . . . . . . . . 86 5.3 Amyloid fibers characterization . . . . . . . . . . . . . . . . . . . . . . . 93 5.3.1 Influence of the oxidation conditions to the kinetics aggregation . . . . 97 5.3.2 Other constructs studied . . . . . . . . . . . . . . . . . . . . . . . . . 99 5.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 5.5 Publication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103

  Figure 5.2: Results obtained with MeDor analysis. The figure shows the different secondary structure predicted along the NTD-AR domain and it shows in the top of the sequence tracks with higher consensus to adopt a -sheet (blue arrow) or helix (red helix) conformation. 83

Figure 5

 5 Figure 5.3: Androgen Receptor showing the NTD, DBD, a hinge (gray) and LBD. Numbering is for human AR. Below is a quantitative representation of the primary sequence conservation among vertebrates. The DBD, the LBD, and a short region in the NTD show a high level of conservation, nearly 100%.

Figure 5 . 4 :

 54 Figure 5.4: Zoom in the highest conserved region of the NTD-AR. Twelve vertebrates species used for the phylogenetic study.

Figure 5

 5 Figure 5.5: The 1D 1 H spectrum of peptide 4 using a zgpr sequence in shown on the top of the 2D TOCSY spectrum. A zoom on the NH region shows the peptide assignment.

Figure 5

 5 Figure 5.6: NMR spectra obtained during the kinetics with 10% DMSO, time 0.5 h (top), 6 h and 23 h (bottom).

Figure 5

 5 Figure 5.7: Kinetics with 1% , 5% , and 10% DMSO, A) second order kinetics fit. For the fit we excluded the last points of the kinetics, where the peptide concentration remains constant; B) peptide concentration disappearance monitored by NMR with the result of the second-order kinetics fit as a dashed line. " %!" %(" &!"

Figure 5 . 8 :

 58 Figure 5.8: Exponential and second-order reaction fitting for the 5% DMSO conditions with the comparison of a fit of the kinetic with a second-order (dashed line) and a first-order kinetic as the exponential (solid line).

Figure 5 . 9 :

 59 Figure 5.9: Evolution of NMR signal intensities for peptide 2 and 6 under various oxidation conditions. 2+1% DMSO (yellow), 2+5% DMSO (orange), 2+10% DMSO (red), 2+TCEP

a

  Figure 5.10: Reaction reversibility after the addition of the reducing agent TCEP.

Figure 5 .

 5 Figure 5.11: The main component (A) corresponds to the molecular mass of the peptide dimer: measured mass 2385.25 ± 0.010 g/mol (expected mass, 2385.2442 g/mol).

Chapter 5 .

 5 Biophysical characterization of a high conserved peptide from the N-terminal Domain of the Androgen Receptor 6, with the Cys to Ser mutation, under the same conditions, where the peptides 2 and 6 incubated during 1 day with 10% DMSO to induce the fibril formation.

Figure 5 .

 5 Figure 5.12: Time evolution of the fluorescent signal after substraction of the buffer signal, for peptide 2 and peptide 6.

Figure 5 Figure 5

 55 Figure 5.13: A) CD spectra of peptides 2, 6 and of peptide 2 under reducing conditions; B) Secondary Structure deconvolution for the CD spectra. All experiments measured at 25 C in water, at neutral pH.

Figure 5 .

 5 Figure 5.15: Additional EM views. left, wider view showing fiber length; center, fibers obtained after shaking; right, image at higher resolution

Chapter 5 .

 5 Biophysical characterization of a high conserved peptide from the N-terminal Domain of the Androgen Receptor

Figure 5

 5 Figure 5.18: a) 1D 1 H spectrum at 0, 1.5, 3 and 24 h after adding 10% DMSO and pH 8.0 b) Kinetics representations of the signal disappearance from the NMR spectrum and the second-order fit.

Chapter 5 .Figure 5

 55 Figure 5.19: a) 1D 1 H spectrum at 15 min, 1, and 30 h after adding H 2 O 2 . b) Kinetics representations of the signal disappearance from the NMR spectrum and the second-order fit.

Figure 5 .

 5 Figure 5.19 shows clearly the difference in this kinetics study. A faster kinetics rate is observed, in around 5 h the peptide concentration has reached the plateau of 0.1 mM (Figure 5.19 b). Looking into the NMR spectra, apart from a immediate dimer appearance, the

Figure 6

 6 Figure 6.1: Simulation of the spectrum for slow exchange with separate signals for bound and free states, intermediate exchange and fast exchange showing only one signal as a weighted average frequency of both states.

Figure 6 . 2 :

 62 Figure 6.2: Values of R 1 and R 2 as function of motional rotational correlation times. Selective R 1 , represents when only one proton is perturbed and the other remains at equilibrium. Figure from [Kieffer 2011].

  nuclear Overhauser effect (NOE) has been introduced in Chapter 3 The use of the NOEs depends on the ability of the ligand to adopt the relaxation properties of the large molecule. The 1D and 2D exchange transferred NOE experiments (etNOE) are used to determine the specific conformation of weak to medium affinity ligands when bound to a protein target [Post 2003].

  Figure 6.3: a) Mechanism of saturation transfer difference (STD). In the "on"-resonance spectrum, the protein resonances are saturated at a frequency where no ligand resonates (methyls or aromatics protons of the protein). This saturation is transferred to the ligand when it binds to the protein. Thus protons show an enhanced signal in the STD spectrum. In the "off"resonance spectrum, the selective radio frequency is selected where neither protein nor ligand resonates, resulting in a normal NMR 1D 1 H spectrum. b) NMR spectra resulting of the STD experiment.

Figure 6

 6 Figure 6.4: Pulse sequence diagrams for the STD NMR experiments with water suppression by WATERGATE method. The solid bars and boxes represent hard 90 and 180 pulses, respectively. For STD after the initial relaxation delay, proton magnetization is saturated either on or off resonance by a train of Gauss pulses (green shaped pulse). The last 180 pulse between two shaped pulses, represents the WATERGATE, canceling the water signal, because of the selective pulses on the water signal.

Chapter 6 .

 6 Figure 6.5: a) Mechanism of WaterLOGSY. The bulk water (blue dots) is excited by r.f. (green arrow) and by different magnetization transfer pathways (black arrows) is transferred to the rest of the water molecules in the buried cavities or in the binding site. This magnetization is transferred to the ligand through the active binding site. The ligand is shown in the bound and free states. b) NMR spectra resulting of the WaterLOGSY experiment.

Figure 6

 6 Figure 6.7: Different EPI molecules, all derivates of Bisphenol A.

Figure 6 . 8 :

 68 Figure 6.8: Hormones and polyphenols used in this study.

Figure 6 . 9 :

 69 Figure6.9: Peptide concentration variation followed by NMR, in the presence of BPA (yellow), EPI-001 (red), EPI-056 (blue) and EPI-sym (green). In black the kinetics of the peptide without molecules, as a control. The dashed line shows the second-order kinetics fitting for the control.

Figure 6 .

 6 Figure6.12: NMR spectra resulting of the STD experiment, when the 0ppm region is saturated (red arrow). Off-resonance spectrum (black), On-resonance spectrum (blue) and STD spectrum (difference between Off-On spectra) in light-blue.

  tube and centrifuged at 6000 G during 20 min, this step was performed twice. The supernatant was put back into the tube and the WaterLOGSY experiment was performed, this time without the presence of the fibers in solution. The WL signal of the molecule became again 0, indicating that no interaction was occurring now in solution.

Figure 6 .

 6 Figure 6.14: Molecule EPI-001 in solution, 1 H spectrum (black), WL spectrum (blue), WL spectrum after dilution (1/10) (green).

Figure 6 .

 6 Figure 6.15: WL spectrum of the mixture peptide 2 + EPI-001 (blue) and WL after removing the fibers by centrifugation (red). Some of the peaks corresponding to the molecule (methyls and aromatics 1 H are marked by dashed lines).

  Figure 6.16: a) Covalent bond formation between EPI-001 + peptide 2. b) HPLC chromatogram resulting of the mixture separation. c) MS spectrum of the adduct corresponding fraction.

Figure 6 .

 6 Figure 6.17: Simplified representation of the HMBC (Heteronuclear Multiple Bond Correlation) sequence.

Figure 7 . 1 :

 71 Figure 7.1: Seeding can eliminate the lag phase in the fibrillation kinetics.

Figure 7

 7 Figure 7.2: p-DOSY spectra monitoring peptide 2 kinetics. Zoom of the Cys-H protons, difference between monomeric and dimeric forms in and D.

FigureD

  mono = 242.7 µm 2 s 1 D olig0 = 189.7 µm 2 s 1

Figure 7 . 3 :

 73 Figure 7.3: Evolution of the diffusion coefficient of the peptide by time. The green line shows the diffusion coefficient value measured and the blue line shows the diffusion coefficient corrected with the solvent diffusion value.

Figure 7 . 4 :

 74 Figure 7.4: Evolution of the diffusion coefficient of the peptide by time. The blue line shows the diffusion coefficient corrected with the solvent diffusion value. The dashed line shows the exponential fit of the curve.

[

  Conc] 0 = 0.98 mM These results demonstrate that the phenomenon characterized with the p-DOSY experiment is the same that the one displayed by the Cys peak in the 1D 1 H experiment. Both kinetics display an exponential profile with the same constant rate k = 0.088. Indicating that we observe the dimerization process by p-DOSY and with the disappearance of the Cys signal.

Figure 7 . 5 :

 75 Figure 7.5: Evolution of the Cys-H concentration by time. The blue line shows the diffusion coefficient corrected with the solvent diffusion value. The dashed red line shows the exponential fit and the dashed black line shows the second-order fit of the curve.

Figure 7 . 6 :

 76 Figure 7.6: Evolution of the peptide concentration by time. The blue line shows the diffusion coefficient corrected with the solvent diffusion value. The dashed red line shows the exponential fit and the dashed black line shows the second-order fit of the curve.

Figure 8

 8 Figure 8.1: 1D 1 H spectra of the acetonitrile-water mixture; left: protonated acetonitrile-water 70% -30% vv at 0 C; right: deuterated acetonitrile-water 70% -30% vv at 6 C.

Figure 8 .

 8 Figure 8.2 presents the variation of the 1 H spectrum when varying slowly the temperature, and crossing the transition temperature for a deuterated acetonitrile-water mixture. Above the transition, the water signal is shifted to the left, and present some small distortions, probably due to slight temperature variation in the sample tube. At the transition, both water and acetonitrile (not visible on this figure) present a splitting which then increase sharply for lower temperatures.

Figure 8

 8 Figure 8.2: Evolution of the NMR 1D 1 H spectrum of the acetonitrile-water mixture (x AN = 0.45) from 293 K down to 273 K performed in a 5 mm tube. Water signal is on the left, acetonitrile is on the right (notice the difference in horizontal scale). The instrument is locked on the acetonitrile signal. The stable coupling pattern of the deuterated acetonitrile is indicating a stable shim condition.

Figure 8 .

 8 Figure 8.3 shows the position of the different NMR signals over temperature. The pattern is characteristic of a phase transition, and the temperature transition seems rather independent on the ratio of solvents used.

Figure 8

 8 Figure 8.3: Left, evolution of the position (in ppm) of the water line with the temperature (in K), for the 65%-35% (v/v) deuterated acetonitrile-water mixture; the 4 points correspond to the 4 characteristics of the water lines: extremities of the patterns (green and yellow dots) and internal sharp lines (red and blue dots). Right, observed transition temperature for various acetonitrile-water ratios.

Figure 8

 8 Figure 8.4: The EXSY spectrum of the acetonitrile-water mixture (65%-35% v/v) , here run with a 1 sec mixing time, showing a exchange peak between the singularities of the powder patterns of the two phases

Figure 5 :

 5 Figure 4: DOSY spectrum, showing the rapid (⇣), medium fast and medium slow ( ) components. Notice the inverted pattern between water and acetonitrile . The same patterns were observed in the sample where progesterone was dissoled (data not shown).imaging with the strange sequence

  4

Figure 8

 8 Figure 8.5: DOSY spectrum, showing the rapid (⇣, D AcCN = 1797.7µm 2 s 1 D H 2 O = 2255µm 2 s 1 ), medium fast (!, D AcCN = 701.8µm 2 s 1 D H 2 O = 644.9µm 2 s 1 ) and medium slow (), D AcCN = 483.2µm 2 s 1 D H 2 O = 443.8µm 2 s 1 ) components. Notice the inverted pattern between water and acetonitrile .

Figure 8

 8 Figure8.6: NMR pulse sequence for the CRAZED experiment. The t 1 delai is regularly incremented, and a Fourier transform is applied along the F 1 axis. Pulse phases are for bothP 90 pulses : {X X X X Y Y Ȳ Ȳ}, Rec : {X X X X Y Y Ȳ Ȳ}Gradients are fixed, with ratio presented in table 8.1.

Figure 8

 8 Figure 8.7: spectrum obtained for the CRAZED experiments. The experiments a-c correspond to the conditions listed in the table 8.1. On each spectra, the position of the ! 1 = 0, ! 1 = ±! 2 , and ! 1 = ±2! 2 , have been noted. On c), we noted also ! 1 = +3! 2

  Figure 8.10: STRANGE spectrum, obtained with gradients varying linearly from 0 to ⇡ 11 G/cm, in 250 points applied during 2 ⇥ 1 msec. Inset shows a zoom on the left "horn" of the acetonitrile pattern, showing the underlying 1-2-3-2-1 pattern of the deuterated acetonitrile. Top-inset shows the 1D extract in front of the arrow. The ) and ( symbols point to the non modulated signals. Again, notice the inverted pattern between water and acetonitrile.

Figure 8 .

 8 Figure 8.13: Two different regions from the SDS STRANGE spectrum that show the same pattern than the water-acetonitrile mixture.

  1.1 Complex Systems and their features . . . . . . . . . . . . . . . . . . . . 13 1.2 Molecular Complex systems . . . . . . . . . . . . . . . . . . . . . . . . . 14 1.2.1 Self-assembly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

1.2.2 Proteins structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 1.2.3 Intrinsically Disordered Proteins (IDPs) . . . . . . . . . . . . . . . . . 17 1.2.4 Amyloids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 1.3 Novel approaches for the biophysics study of complex systems . . . . 19 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

  2.1 Androgen Receptor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 2.2 Androgen Receptor Ligands . . . . . . . . . . . . . . . . . . . . . . . . .

		29
	2.3 Androgen Receptor mode of action . . . . . . . . . . . . . . . . . . . .	31
	2.4 Androgen Receptor and different related pathologies . . . . . . . . . .	32
	2.5 Androgen Receptor's role in prostate cancer . . . . . . . . . . . . . . .	33
	2.6 New strategies to target the Androgen Receptor . . . . . . . . . . . . .	34
	Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .	37
	A good example of complexity is the nuclear receptors (NR) super family. Nuclear receptors
	form a superfamily of phylogenetically related proteins, there are 48 NR in the human genome

Table 5 .

 5 1: Secondary structure prediction. A selection of five peptides is presented in this table, with the human-AR numbering, the residues sequence, the secondary structure prediction for the different methods: H (helix), ( -sheet) and C (coil).

	Position	Peptide	MeDor NPS@ PAT	Remarks/Rational
	1 [179-194] ADLKDILSEASTMQLL	H	H	H	L194R K182R	LxxLL
	2 [237-247]	KELCKAVSVSM	H/	H/	H
	3 [339-355] LELPSTLSLYKSGALDE	H	H	H	S 3 4 3 ⇤	P342L
	4 [433-441]	SSWHTLFTA	C	H	H /	W	W435L WxxLF
	5 [526-537]	PWMDSYSGPYGD	C	C	C	W

Table 5 .

 5

	%,	(,	!%,	!(,	"%,	"(,
	.'/01'		.'/01'
	'8,#,.9	72*6'8,#,.9

2: I o , R g and R XC values obtained for SAXS analysis. qR g and qR XC limits used for the Guinier determination are indicated.

Figure

5

.17: I o evolution (a.u.) vs time and R XC vs time , as determined from the Guinier analysis presented in table 5.2.

Table 5 .

 5 3: Aggregation study of different length sequences from the highest conserved residues of the N-terminal domain of the Androgen Receptor.

		Peptide	Dimerization Aggregation
	2	KELCKAVSVSM	X
	6	KELSKAVSVSM
	7	KELCKAVSVSMGLGVEALEHLS	X
	8	KELCKAV	X
	9	KELCKAVSV	X
	10 TISDNAKELCKAVSVSMGLGVEALEHLS	X

Table 5 .

 5 3 summarizes the results obtained for the different peptides chosen for this study, into dimerization or aggregation, depending of the behavior displayed for the different amino acids sequences. The classification into aggregation also implies dimerization through disulfide bridge formation.

Table 6 .

 6

	Molecule	control +fibers
	DMSO	(-)	(-)

1: WaterLOGSY results. (+) positive response,(-) negative response or (0).

  Aggregation kinetics followed by p-DOSY . . . . . . . . . . . . . . . . 149 7.3 Analysis and fitting of the Diffusion coefficient (D) evolution . . . . . . 150 7.4 Peptide vs Cysteine kinetics . . . . . . . . . . . . . . . . . . . . . . . . 153 7.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157

	7.1 Amyloid fibers formation: kinetics and soluble oligomers intermediates 147
	7.2 7.1 Amyloid fibers formation: kinetics and soluble oligomers
	intermediates
	Amyloid fibers formation requires the ordering of the monomeric peptides into oligomers that
	later organize into fibrils. This ordering implies the formation of -sheets secondary structures.

  Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 8.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 8.2.1 1D 1 H experiments and Isotopic effect . . . . . . . . . . . . . . . . . . 161 8.2.2 Phase diagram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 8.2.3 EXSY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164This chapter marks a turning point in this thesis. This study started as a collaboration with Jean-Marie Lehn who brought us the opportunity to characterize the special behavior that presents the mixture acetonitrile-water at low temperature. This different topic, represents in a perfect way what a complex system is, and how from an apparent simple system we can observe interesting and difficult results. I decided to include this work as a final chapter of my thesis, not only because we have invested a lot of time on it, but also because it has been a passionate work the fact of searching new ideas, hypotheses or experiments that could elucidate or model the phenomenon we are observing. Along this three years we have asked experts from different area to collaborate and to help us to figure out the phenomenon we were observing. Hervé Desvaux, Daniel Gruker, François Xavier Courdet and Marc-André Delsuc, Chapter 8. NMR study of spontaneous Acetonitrile-Water demixing Up to this point, in the thesis we have been focused in complex systems by a biological point of view. As has been discussed in Chapter 1, complex systems are present all around us.

	Chapter 8
	NMR study of spontaneous Acetonitrile-Water
	demixing
	8.1

8.2.4 DOSY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 8.2.5 CRAZED . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166 8.2.6 STRANGE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168 8.2.7 Unsuccessful experiments . . . . . . . . . . . . . . . . . . . . . . . . . 171 8.2.8 SDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 8.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 8.4 Materials & Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177

whom have contributed with ideas, solutions or mathematical descriptions and together with we present this results as a manuscript for a future publication.

AcCN-water 65%-35% 3mm tube 500MHz

	T (K)	Position /ppm						Distance (Hz)
		water1	water2 step1	step2	AcCN	AcCN2 step 4	water peaks AcCN peaks
	293	3.665				1.971
	288	3.943				1.971
	286	3.975				1.971
	284	4.009				1.971
	282	4.043				1.971
	281	4.064				1.971
	280	4.015				1.971
	279.5	4.262 3.994			1.971
	279	4.241 3.956	4.29 3.779 1.971
	278	4.271 3.925			1.971
	277	4.279 3.863			1.971
	276	4.295 3.837 4.818 3.377 1.971
	AcCN-water 70%-30% 3mm tube 500MHz
	T (K)	Position /ppm						Distance (Hz)
	T (K)	water1	water2 step1	step2	AcCN	AcCN2 step 4	water peaks AcCN peaks
	293	3.958				1.971
	288	4.036				1.971
	284	4.104				1.971
	282	4.139				1.971
	281.5	4.147				1.972
	281	4.156				1.972
	280.5	4.088				1.972
	280	4.31 4.037	4.6	3.74 1.972		1.68
	279.5	4.36 3.997	4.69	3.7 1.972	1.75	1.68
	279	4.35 3.965	4.75	3.65 1.972	1.74	1.68
	277	4.37 3.874	4.92	3.53 1.972	1.74	1.64
	275	4.39 3.798	5.01	3.43 1.972	1.71	1.62
	T (K)	Position /ppm						Distance (Hz)
	T (K)	water1	water2 step1	step2	AcCN2 AcCN1 step 4	water peaks AcCN peaks
	293	4.063				1.971
	288	4.12
	284	4.18
	282	4.239				1.972
	281	4.273	4.12 4.408 4.007 1.972 1.854	76.7	60.2
	280.5	4.287 4.085 4.569 3.847 1.972 1.829	105.1	71.3
	280	4.296 4.031 4.647 3.756 1.972 1.801	138.3	85.3
	279.5	4.299 3.907 4.675 3.679 1.972 1.746	201.7	113

Table 8

 8

	.1: Gradient intensities used for the CRAZED experiments
	exp. label	G 1	G 2	G 2 /G 1
	a)	15% 30%	2
	b)	-15% 30%	-2
	c)	10% 30%	3

a point mutation where a single nucleotide is changed to cause substitution of a different amino acid

a point mutation in a sequence of DNA that results in a premature stop codon resulting in aberrant splicing of AR mRNA

Acknowledgments

Publication

The work presented in this chapter resulted in a publication in ChemBioChem, Volume 15, Issue 16, pages 2370 -2373 , November 3, 2014. .

List of Abbreviations

The nuclear hormone receptro gene superfamily. Annu. Rev. Med., vol. 46, no. 1, pages 443-453, February 1995. (Cited on page 25.)

A.1 Molecules, solvents and sample preparation

Crystalized ↵-D-glucose (anhydrous, 96% purity) was purchased to Sigma-Aldrich (USA).

Deuterated solvents DMSO-d6 (99.96%) and D 2 O (99.9%) were purchased to Euriso-Top (France). All samples were measured in 5.0 mm tubes. A stock solution of 100.0 mM ↵-Dglucose in DMSO was prepared. 100 µL of the glucose stock solution were added in 900 µL D 2 O resulting in final concentration of 10.0 mM .

A.2 NMR experiments

DOSY NMR measurements were carried out on a Bruker 500 Avance I NMR spectrometer, operating at 500.137 MHz for 1 H, equipped with a 5 mm TXI probe. The pulse sequence used was a longitudinal eddy current delay bipolar gradient pulse (ledbpgp2s) An exponential gradient list of 32 values was created by using the standard AU program dosy. For the p-DOSY experiment, the list was permutated by an ad-hoc python script, and the permutated list was used for acquisition and processing. Experiments were acquired with 8 scans, /2 of 3.0 ms and of 150 ms, for an overall time of 23:09 min. A series of 15 spectra was acquired at a temperature of 300 K for a total duration of 6.0 hours. Before and after every DOSY spectrum, an 8 scans proton spectrum was recorded. The whole experiment was duplicated once with regularly increasing series of gradients, and once with a permutated series.

The DOSY spectra acquired on Bruker were processed with the NMRnotebook program, using the DOSY MaxEnt implementation (version 2.7, NMRTEC France). No modification had to be made to the computation protocol despite the permutated entries in the DOSY file.

The final diffusion coefficients were calculated from the average position of the anomeric signal for each species. Error bars were estimated as the standard deviation along the diffusion axis of the different signals. by averaging the values measured for all major peaks in each proton signal. Minor viscosity variations were compensated by normalizing all measurements to the DMSO diffusion coefficient.

A.3 Permute script

Here is presented the "Permute" script to permutate the Difframp and difflist for acquisition and processing the p-DOSY experiments. The original Difframp, created by TopSpin when a DOSY experiment is launched, has to be replaced by the permutated Difframp before running the p-DOSY experiment. The same procedure has to been followed for the difflist before processing the spectrum. [ Rubinov 2009] Boris Rubinov, Nathaniel Wagner, Hanna Rapaport and Gonen Ashkenasy.

Self-Replicating Amphiphilic -Sheet Peptides. Angew. Chem. Int. Ed., vol. 48, no. 36, pages 6683-6686, August 2009 Soc., vol. 113, no. 17, pages 6657-6662, 1991. (Cited on page 88.)

B.1 Bioinformatic study

Disorder and Secondary Structure prediction

Here are described the different bioinformatic programs that were used for the disorder and secondary structure analysis.

• metaPrDOS meta Protein DisOrder prediction System, metaPrDOS is a meta server to predict natively disordered regions of a protein chain from its amino acid sequence [Ishida 2008]. metaPrDOS returns disorder tendency of each residue as prediction results.

metaPrDOS does not predict disordered regions from amino acid sequence directly, but predicts disordered regions by integrating the results of different prediction methods, using eight prediction systems to predict disordered regions:

PrDOS [Ishida 2007] DISOPRED2 [Ward 2004]

DisEMBL TM [START_REF] Linding | Protein disorder prediction: Implications for structural proteomics[END_REF]] DISPROT (VSL2) [Peng 2006]

DISpro [Cheng 2005]

• NPS@ Network Protein Sequence @nalysis, NPS@ is an interactive Web server dedicated to protein sequence analysis that can be used for secondary structure prediction.

• MeDor MeDor [Lieutaud 2008] provides, among other things, Hydrophobic Cluster Analysis (HCA). MeDor is conceived to provide a global overview of various predictions, and to speed up the disorder prediction.

Alignment

The Androgen Receptor protein sequence alignment was obtained using Jalview [Waterhouse 2009 The peptides were desalted with H 2 O using a GF Superdex 10/300 column in an AKTA system, to remove the TFA (trifluoroacetic acid) coming from the purification process and lyophilized after that.

The peptides were stored as lyophilized powder at -20 C. Stock solutions were prepared with a final concentration of 5 mM with H 2 O Milli Q and 1 mM of NaN 3 .

NMR experiments

All NMR studies (except the TCEP recovery) were performed on a Bruker Avance III 700 MHz spectrometer equipped with a Z-gradient cryoprobe at 25 C. The spectra were processed and analyzed using NMR-notebook R (NMRTEC Illkirch France). 1 H 1D spectrum, TOCSY and ROESY 2D experiments were performed in order to assign the peptide spectrum. A series of 1 H spectra were recorded after the addition of 1%, 5%, and 10% dimethyl sulfoxide (DMSO)

to the NMR solution. The sample consisted of 180µl of 0.5 mM peptide in 20 mM phosphate buffer pH = 6.4 with 10% D 2 O in 3 mm tubes. Concentration of the soluble peptide forms during the kinetics was measured by the integration of the methyl region ([0.8ppm 1.0ppm])

of the NMR spectrum. The TCEP spectra were performed on a Bruker Avance III operating at 500 MHz, using a TBI probe.

The sequence used for the 1D 1 H spectra was zgpr. The sequence used for 2D 1 H-1 H TOCSY spectra was dipsi2phpr with a mixing time of 80 ms at 12.3 dB. The sequence used for 2D 1 H-1 H ROESY spectra was croesyphpr with a mixing time of 300 ms at 20 dB.

The 90 pulse for all the experiments presented in Chapter 5 is comprised between 8-11 µs at 3.2 dB.

The peptide quantification was performed using the Tryptophan concentration as reference as explained in [START_REF] Wider | Measuring Protein Concentrations by NMR Spectroscopy[END_REF]]. The concentration of the stocksolution of Tryptophan is 6.3 mM, dissolved in water, it was measured by optical density (" 280(T RP ) = 5600 cm 1 M 1 at 298 K).

The experiments were conducted at 298K, on 3mm tubes filled with 180 µl of sample and inserted in a 700 MHz Bruker spectrometer equipped with a TXI cryo-probe. The sample was prepared in water with 10% D 2 O. The concentration of Tryptophan in the solution was again checked by DO, resulting at 1.2 mM. The 1D proton experiment employed used a D1 relaxation delay of 5 s (T1 of tryptophan = 3 s) and a 90 pulse of 9.75 µs at 3.2 dB.

Mass Spectrometry

The precipitate from the NMR tube was dissolved in 1:1 (v/v) Acetonitrile-Water with 2% formic acid and analyzed by Mass Spectrometry (ESI/TOF micrOTOF II Bruker).

Circular Dichroism

Far UV Circular Dichroism (CD) experiments were recorded on a Jasco J-815 spectropolarimeter (Easton, MD) equipped with an automatic 6-position Peltier thermostated cell holder. The instrument was calibrated with 10-camphorsulphonic acid. CD data were collected in the 180-260 nm range, by 0.5 nm steps using a 0.1 mm path-length cell (Quartz-Suprasil, Hellma UK Ltd) at 25.0 ± 0.1 C. Spectra were acquired using a continuous scan rate of 100 nm/min and are presented as an average of 10 successive scans. The response time and the bandwidth were 1.0 sec and 1 nm, respectively. All samples were studied in pure water, at a concentration of 1 mM. As DMSO cannot be used in CD experiments, all samples were incubated for 24 hours at 37 C. The spectra were corrected by subtracting the solvent spectrum obtained under identical conditions. The signal is expressed in mean residue ellipticity (deg cm 2 dmol 1 ).

Secondary structure content was estimated with the CDPro suite [Sreerama 2000] using the CONTIN/LL method. CONTIN/LL fits the CD spectra by comparison to a linear combination of the spectra of a large database of proteins with known conformations. Several databases were tested, and the SDP48 database was chosen, as it provided the smaller RMSD.

Thioflavin fluorescence

The experiments were recorded on a Fluorolog Jobin Yvon spectrofluorometer, without shaking, with excitation at 440 nm and emission at 482 nm. The samples for peptide 2 and 6 were prepared with the same conditions than the for the CD analysis. The measurements were performed during 600 s.

Electron Microscopy

The same samples used for the NMR studies were analyzed under the Electron Microscope.

5 µl were deposited onto a glow-discharged, carbon-coated copper electron microscopy grid, stained with 1% uranyl acetate and observed under a Philips CM120 transmission electron microscope equipped with a LaB6 filament and operating at 100 kV.

Small Angle X-ray Scattering

Small Angle X-ray Scattering (SAXS) data were collected on a BioSAXS-1000 system (Rigaku) coupled to a MicroMax-007HF X-ray generator (Rigaku) using Cu K ↵ radiation with = 1.5418 Å and a Pilatus 100 K detector (Dectris). 30 µl of water with 5% DMSO were injected into a sample holder fitted with a 0.1 mm thin wall quartz capillary and a two hour long exposure was collected. DMSO was added to the peptide at 1 mg/ml and 30 µl were injected into the same sample holder and twelve exposures were collected sequentially.

Chapter 6

Small molecules interactions study with a high conserved peptide of the N-terminal domain of the Androgen Receptor Nuclear magnetic resonance (NMR) has been widely used for the study of molecular structure, dynamics and protein-ligand interactions [Pellecchia 2002b, Maurer 2005, Markwick 2008].

Specially, for monitoring ligand interactions new NMR approaches has been developed and studied by pharmaceutical industry in drug discovery and screening [Wishart 2005, Carlomagno 2005, Harner 2013].

In order to detect ligand-protein interactions, two basic different approaches have been developed. NMR can be used to observe changes in the ligand side (small molecules) when it binds to the protein, or to observe changes in the protein side up to binding.

Chapter 6. Small molecules interactions study with a high conserved peptide of the N-terminal domain of the Androgen Receptor

Protein-ligand interactions: protein based experiments

The binding of the ligand to a protein results in a local environmental effect on the binding surface, but also in the protein's structure and dynamics. These changes will be displayed as alterations in the NMR properties as chemical shifts, relaxations rates and line-shapes. For that reason, these parameters can be used as indicator of ligand-protein interactions.

Chemical shift perturbation

The chemical shift perturbation (CSP) experiment, also known as chemical shift mapping, is one of the most widely used in this domain to probe ligand-protein interactions [Williamson 2013].

The aim of this experiment is to follow the changes in the chemical shifts ( 1 H, 15 N or 13 C) of a protein during a ligand titration. The amino acid residues that show a progressive shift in ppm can be located in the binding surface or in the domain that suffers a structural change.

The dissociation constant (K d ) can be calculated from this experiment, derived from chemicalshifts variations as function of the ligand concentration. A good example of the application of the CSP experiment are [START_REF] Quinternet | Unraveling complex small-molecule binding mechanisms by using simple NMR spectroscopy[END_REF]] and [START_REF] Köhler | [END_REF]].

Protein dynamics

Dynamics have an important role for understanding protein function and for structure-based drug design [Sapienza 2010]. Ligand binding can lead to changes in the protein three dimensional structure, and these modifications imply changes to its dynamics. NMR relaxation methods are extremely powerful for the characterization of protein motions with atomic resolution over a different times scales. These approaches can be used to study the fast (ps-ns) and slow (µs-ms) time-scale dynamics [Ertekin 2007]. Other approaches as non covalent grafting of proteins is used to study protein-ligand interactions using the HR-MAS (High Resolution Magic Angle Spinning) technology [START_REF] Viéville | A new NMR technique to probe protein-ligand interaction[END_REF]]. When the nuclear environments are modified slowly regarding the NMR timescale, the spectrum will show two different resonances for the free and bound state. Whereas if the nuclear environment changes rapidly will produce a single resonance as an average of the chemical shifts for the free and bound species. N-terminal domain of the Androgen Receptor

Saturation transfer difference (STD)

We aim to show interaction between the small molecule EPI-001 and the fibrils formed in solution. The STD experiment was only tested with the molecule EPI-001. As explained in the introduction, this method presents less sensitivity than the WaterLOGSY experiment [Antanasijevic 2014] and requires a precise "on" resonance. The difficulty of using the STD experiment in this system comes from the fact that we are not dealing with a standard globular and structured protein. It lacks the aromatic moiety which produces large shifts in the spectrum.

We do not observe the fibrils in the NMR spectrum, for this reason the frequencies of the soluble peptide are used as reference. Nevertheless, the methyl groups presented in peptide 2 appear at 0.85 ppm, no so far of the methyl groups of the EPI-001, making it difficult to find an optimal "on" resonance.

Figure 6.10: NMR spectra resulting of the STD experiment, when the NH region is saturated (red arrow). Off-resonance spectrum (black), On-resonance spectrum (blue) and STD spectrum (difference between On-Off spectra) in light-blue.

We could not obtain any clear result after performing the experiment (Figure 6.10, 6.11 and 6.12). We performed the experiment by saturating three different regions, the NH region (Figure 6.10), the methyl region (Figure 6.11) and finally an offset region at 0ppm (Figure 6.12). An effect is observed on the two first experiments. Nevertheless, when we apply the saturation to the fibrils we are also irradiating the molecule, by proximity. This leads to an unclear result from which no conclusion can be drawn.

C.1 LC/MS/NMR system

The sample for the LC/MS/NMR experiments was prepared in H 2 O pH = 8.0, with a final concentration of peptide 2 of 3 mM and 5 mM of EPI-001 dissolved previously in Tetrahydrofuran (THF) in a 100 mM stock. We did not use DMSO in this experiment due to difficulties that involve its use for the mass spectrometry analysis.

10 µL of the sample were injected into a C18 ProntoSIL eurobond 125x4 mm (5.0 µm), in a HPLC Agilent 1200. The sample was analyzed after the HPLC column on a Mass spectrometer Bruker HCT IonTrap, ESI source. 10 runs were performed, different fractions from the HPLC chromatogram were selected and collected in a SPE (solid phase extraction) cartridge (GP and HLB). The cartridges were dried over night using N 2 . After that, the sample was eluted from the SPE, using deuterated Acetonitrile directly to the 30 µL capillary in a 500 MHz Bruker LC-SEI.

The chromatographic method used for the HPLC analysis was:

A: H2O 90% (0 min) 31.8% (15 min) 0% (20 min) B: AcCN Chapter 8. NMR study of spontaneous Acetonitrile-Water demixing

The position of the transition temperature has been carefully measured, and is reported in Figure 8.3. The values obtained are very close to the values reported by Szydiowski et al [START_REF] Szydłowski | Isotope effect on miscibility of acetonitrile and water[END_REF]]. In this study, the authors measured the phase diagram of the transition for protonated and deuterated samples, and showed that the deuterated liquids present a transition temperature quite higher than the protonated ones. We recovered the same results.

EXSY

The EXSY (EXchange SpectroscopY) experiment is a 2D NMR experiment which measures the presence of chemical exchange in a system. The sequence is very similar to the NOESY experiment, and contains a mixing period over which the chemical exchange is sampled.

Only one peak could be clearly seen on the EXSY spectrum Figure 8.4, connecting the two longitudinal singularities of the water patterns.

The absence of signal around the powder pattern indicates that there is no reorientation of the cause of the spectral anisotropy for a time period on the order of the second. This rules out the possibility of short range anisotropy, and indicate that the anisotropies are probably on long range distance, which are not perturbed by the (slow) convection found in a 3 mm tube at low temperature. This correlates well with the memory effect, mentioned in the first paragraph.

However, in this context, the exchange peak is difficult to explain, without even a simple molecular model of the two phases, and of their interphase.

RDC

Suspecting a structured bi-phasic liquid mixture, we tried to investigate the presence of a partial orientation of the system. For that, we tried to measure Residual Dipolar Coupling (RDC) of progesterone molecule dissolved in the acetonitrile-water mixture. The residual dipolar coupling between two spins in a molecule occurs if the molecules in solution exhibit a partial alignment leading to an incomplete averaging of spatially anisotropic dipolar couplings. No RDC values were found, this could be due to the weakness of the coupling or because is only chemical shift anisotropy.

Moment law

We tried to extract a more precise phase diagram by crossing the transition temperatures with the intensities of the NMR signal, applying the moment law. The precision of the NMR integrals, measured on the wide powder patterns, was not sufficient to perform this analysis in a satisfactory manner.

SDS

To test whether the STRANGE effect could be observed on another structured solution, we decided to test it on a high concentration of SDS in water. Sodium dodecyl sulfate (SDS CH 3 (CH 2 ) 11 OSO 3 Na), is an anionic surfactant used in many cleaning and hygiene products.

It readily adopts a micelle organization in water, above the critical micellar concentration (cmc), which is on the order of 8 mM. SDS micelles are organized with the sulfate group on the outside, and the alkyl chain packed in the interior of the micelle. This results in two independent liquid phases, the intermicellar volume, mostly constituted of water, and the intramicellar volume which can be considered as a oily liquid. SDS micelles are known to be quite monodisperse, constituted of about 50 molecules, for a large part independent on the global SDS concentration. In consequence, a high concentration of SDS in water may constitute a medium in which the effect as observed on the acetonitrile-water mixture may appear. For this reason, we are going to use a 30% solution of SDS in water as a control for the CRAZED and STRANGE experiments. Figures 8.12 and 8.13 show the results of such experiments.

The same effects can be observed on the sample, albeit weaker. In particular the solidstate pattern observed in the 1D spectrum of the acetonitrile-water mixture cannot be observed directly in the 1D spectrum. However, the STRANGE spectrum presents kind of trajectories, on the ↵-methylene (noted 1) and on the !-methyl (noted 4).

Materials & Methods

Solvents

Acetonitrile-d 3 and deuterated water were purchased to Euriso-Top (France).

NMR experiments

The The experiments were carried out on a 500 MHz Bruker spectrometer equipped with a 5mm TXI probe. All 1 H 1D experiment were performed using 16 scans, with a 90 of 9 µs at 0 dB. A period of 30 min for temperature stabilization was stablished after reaching each temperature step. In most cases, the instrument was locked on the acetonitrile deuterium signal.

Experiments were performed either using 3 mm tubes or 5 mm tubes. 3 mm tubes allowed a better temperature equilibration over the sample volume, and presented well characterized spectra and sharper transitions. 5 mm tubes lead to less spectral reproducibility, but allowed higher signal-to-noise ratio, often necessary when working on the deuterated samples, considering the width of the observed spectral patterns.

Chapter 9

General Conclusions

My thesis project have been a collaboration between the NMRTEC company and the Biomolecular NMR team at the IGBMC (Institut de génétique et de biologie moléculaire et cellulaire)

under the supervision of Marc-André DELSUC. This work was supported by the NMRTEC society, conducted as part of the European project ITN-ReAd. This European project brings together ten laboratories, and two companies, on the study of complex chemical systems, such as self-replicating systems, or the development of new sensors. In this network, the role of the company is to develop new approaches for the analysis of complex systems.

In this context, my project was focused on the development of methodologies for the analysis of complex systems and the biophysical characterization of these systems. This include the study of self-assembly systems, protein-ligand interaction, disordered biological systems and solvents mixtures. A wide range of biophysical methods were used for this purpose. Mostly, Nuclear Magnetic Resonance (NMR) but also other techniques such as mass spectrometry, circular dichroism (CD), electron microscopy (EM) and small angle X-ray scattering (SAXS).

In a first part of my thesis, an out-of-equilibrium system (↵-to -glucose anomerization)

is studied using NMR. The evolution of the concentration during the DOSY acquisition let a bias in the diffusion coefficient value than can lead to misinterpretations. We show that a random permutation of the intensities of the gradients used for the DOSY experiment allows to eliminate this bias. This approach, that we named p-DOSY requires no changes in the NMR sequence and improve the accuracy of the measurement.

In a second part of my thesis, the N-terminal Domain of the Androgen Receptor is studied as example of a complex system. This region plays an important role in receptor activity, specially when the castration resistance prostate cancer (CRPC) is developed. And it is also described as being intrinsically disordered. In the N-terminal domain of AR (AR-NTD), there is a short primary sequence that is unique to this protein in all the human genome and which is perfectly conserved in all vertebrates. This sequence contains a cysteine residue and appears perfectly soluble and non structured in its native state. Upon the oxidation of the thiol group by DMSO, a covalent dimer is formed. This dimer spontaneously self-assembles into amyloid fibers with a diameter of 6 nm. Kinetic analysis of this phenomenon was followed by NMR In a third part, a study of the acetonitrile-water mixture was performed. This common used mixture of solvents presents an anomaly behavior at low temperature which had not been yet explored by NMR. The particular structure of the liquid-liquid phase separation which takes place in this system leads to large perturbations in the 1D NMR spectra, indicating strong anisotropies in the liquid-liquid interphase. Other NMR experiments have been performed on the mixture, showing the presence of structured micro-domains. However the full interpretation of this effect requires the complete modeling of the quantum dynamic of a very large spin system, a task which is beyond the scope of this work.

Finally, these three different projects have in common the way of scientific and experimental approaches have been developed. A priori simple systems, can adopt or develop a non expected complex behavior. This situation illustrates the fact that no assumption can ever be done about the complexity of a system, increasing the difficulty of the scientific approach. From an unclear result or behavior, you build small hypothesis that become evidences and allow you step by step to draw and to understand (not always) a complete story.

The general conclusion, of the work performed during these three years, is that scientific research is amazing, surprising and not always easy but it is worth it.

1 Caballero Martinez 2003, Arch. Esp. Urol., vol. 56, no. 4, pages 431-434, May 2003.

Novel approaches in NMR and biophysics for the study of complex systems.

Abstract

My PhD project was focused on the development of methods for the analysis of complex systems and their biophysical characterization. This includes the study of large chemical libraries, selfassembly systems, protein-ligand interaction studies and disordered biological systems. A wide range of biophysical methods were used for this purpose. Specially, Nuclear Magnetic Resonance (NMR) but also other techniques such as mass spectrometry, circular dichroism (CD), electron microscopy (EM) and small angle X-ray scattering (SAXS). The N-terminal Domain of the Androgen Receptor is studied as an example of a complex system. This region plays an important role in receptor activity, and is also described as being intrinsically disordered. The results obtained during my thesis shown a short conserved region involved in the amyloid fibers formation under oxidative conditions. These results open new possibilities to understand the mechanism of the AR activity.