Damien Bosc

Virgyl Camberlein

Ronan Gealageas

Omar Castillo-Aguilera

Benoit Deprez

Rebecca Deprez-Poulain
email: rebecca.deprez@univ-lille.fr

Kinetic Target-Guided Synthesis: reaching the age of maturity

Keywords: KTGS, triazole, fragment, in situ click chemistry, hit-to-lead, lead-optimization

Kinetic target-guided synthesis (KTGS) is an original discovery strategy allowing a target to catalyze the irreversible synthesis of its own ligands from a pool of reagents. Though pioneered almost two decades ago, it only recently proved its usefulness in medicinal chemistry, as exemplified by the increasing number of protein targets used, the wider range of target and pocket types, and the diversity of therapeutic areas explored. In recent years, two new leads for in vivo studies were released. Amidations and multicomponent reactions expanded the armamentarium of reactions beyond triazole formation and two new examples of in cellulo KTGS were also disclosed. Herein, we analyze the origins and the chemical space of both KTGS ligands and warhead-bearing reagents. We review the KTGS timeline focusing on recent cases in order to give medicinal chemists the full scope of this strategy which has great potential for hit discovery and hit or lead optimization.

INTRODUCTION

Definitions and terminology

Protein-templated synthesis (PTS) or Target-guided synthesis (TGS) of ligands use the protein of interest as a template to form its own ligands (Figure 1) [START_REF] Jaegle | Protein-Templated Fragment Ligations-from Molecular Recognition to Drug Discovery[END_REF][START_REF] Bosc | Kinetic Target-Guided Synthesis in Drug Discovery and Chemical Biology: A Comprehensive Facts and Figures Survey[END_REF] . Although proteintemplated synthesis of a ligand has been unexpectedly observed by some biochemists in the past, it is a rather novel concept that has gained a real interest in drug discovery labs in the past decade. As a consequence, it has been highlighted as part of bioorthogonal chemistryinspired advances in medicinal chemistry. [START_REF] Wu | Overview of Recent Strategic Advances in Medicinal Chemistry[END_REF] Prior to analyzing the recent achievements in the field of Kinetic-Target Guided Synthesis (KTGS), one of the protein-templated strategies for ligand discovery, the terminology for these strategies will briefly be reviewed. The different approaches for PTS are classified as thermodynamically or kinetically controlled synthesis. [START_REF] Cheeseman | Receptor-Assisted Combinatorial Chemistry: Thermodynamics and Kinetics in Drug Discovery[END_REF] Kinetic target guided synthesis (KTGS) and dynamic combinatorial chemistry (DCC) (Figure 1A) stand respectively for the protein-templated synthesis of ligands by irreversible or reversible reactions. In DCC, there is a continuous interconversion between the reagents and the final products (dynamic combinatorial library, Figure 1A). The target shifts the thermodynamic equilibrium between products and reagents towards ligands that have the highest affinity for the target. [START_REF] Hartman | Protein-Templated Dynamic Combinatorial Chemistry: Brief Overview and Experimental Protocol[END_REF][START_REF] Frei | Dynamic Combinatorial Chemistry: A New Methodology Comes of Age[END_REF] These ligands are produced in significantly high amounts in the presence of the protein. In KTGS, the targets bring in close proximity with theright orientation, affine reagents, so that they react irreversibly. [START_REF] Bosc | Kinetic Target-Guided Synthesis in Drug Discovery and Chemical Biology: A Comprehensive Facts and Figures Survey[END_REF][START_REF] Hu | Kinetic Target-Guided Synthesis[END_REF][START_REF] Oueis | New Insights into the Kinetic Target-Guided Synthesis of Protein Ligands[END_REF] In situ click chemistry, first disclosed for the discovery of acetylcholinesterase (AChE) inhibitors, is the most popular kinetic target-guided synthesis. It allows protein-templated triazole synthesis from biocompatible alkynes and azides. [START_REF] Lewis | Click Chemistry in Situ: Acetylcholinesterase as a Reaction Vessel for the Selective Assembly of a Femtomolar Inhibitor from an Array of Building Blocks[END_REF] A review of the literature shows that the term "target-guided synthesis" (TGS) has sometimes been replaced with synonyms like "receptor-based"-, "receptor-assisted"or "protein-templated"-synthesis (Figure 1B). Several groups used "combinatorial chemistry", in the original sense of mixing arrays of reagents with the same reactivity, without mentioning the type of protein-templated reaction. We recommend using "combinatorial chemistry" along with "kinetic" or "dynamic" terms where appropriate. Three different set ups for KTGS reactions are reported and have been defined earlier 2 : a binary format, a multicomponent format where clusters of reagents are used as mixtures or an orthogonal multicomponent format.

Recent discussions question whether target-guided strategies belong to fragmentbased drug discovery (FBDD) techniques. Indeed, the term "fragment" is sometimes used to describe biocompatible reagents for protein-templated reactions (Figure 1B). Fragments were initially defined as small compounds that comply to the rule-of-three (Ro3). [START_REF] Congreve | A 'Rule of Three' for Fragment-Based Lead Discovery?[END_REF] This Ro3 was later adjusted. Some reports showed that it should be applied in a context-dependent manner, more specifically according to to hydrogen bond donors and acceptors thresholds. [START_REF] Köster | A Small Nonrule of 3 Compatible Fragment Library Provides High Hit Rate of Endothiapepsin Crystal Structures with Various Fragment Chemotypes[END_REF] FBDD is based on the identification of weakly bound fragments which are further optimized into final ligands upon linking or growing. Conversely, TGS is based on the identification of high-affinityligands (ie final compounds) from in situ ligations. We thus recommend to use "fragment" when reagents for KTGS are discovered by fragment screening. The term "reagents" can be used to describe the chemical precursors for KTGS and "warhead-bearing reagents" can be used for precursors that help to drive the final ligand within a protein pocket (either previously known or new).

Several teams have paved the way to target-guided synthesis in cells. To include these, we propose to add the "in cellulo" prefix to target-guided or to protein templated synthesis, and to avoid the phrase "in cellulo click chemistry" that cannot sufficiently distinguish between the protein labelling using click chemistry for chemical biology purposes, and the genuine KTGS in cells. The main events in the timeline of Kinetic Target-Guided Synthesis strategies are presented in Figure 2. The first, although unexpected, example of a KTGS reaction was disclosed in 1991 by Inglese et al: an inhibitor of glycinamide ribonucleotide transformylase (GARTfase) was templated from β-glycinamide ribonucleotide substrate and N10-(bromoacetyl)-DDF an affinity label inspired by the enzyme cofactor. [START_REF] Inglese | Multisubstrate Adduct Inhibitors of Glycinamide Ribonucleotide Transformylase: Synthetic and Enzyme-Assembled[END_REF] Similarly, several drugs can be considered as KTGS precursors as they react with co-factors within their target enzyme to provide an adduct that is the active species. Examples include: carbidopa, that reacts with pyridoxal phosphate to inhibit DOPA decarboxylase and selegilin that reacts with FAD to block MAO-B and isoniazid reacts with NAD to inhibit MtB catalase. [START_REF] Potashman | Covalent Modifiers: An Orthogonal Approach to Drug Design[END_REF] Ataluren (PTC-124), a recent drug used for its nonsense codon suppression activity in the treatment of Duchenne's disease, was initially a false positive in a reporter gene assay that used firefly luciferase (FLuc). It was shown later that FLuc acts as a template for the formation of its own strong inhibitor PTC124-AMP (IC50 = 10 nM) from ataluren and ATP. [START_REF] Auld | Molecular Basis for the High-Affinity Binding and Stabilization of Firefly Luciferase by PTC124[END_REF] The first use of KTGS for medicinal chemistry was disclosed by Huc et al in 2001. They describe the thiol alkylation using various halides in the presence of human carbonic anhydrase II (hCAII). [START_REF] Nguyen | Using an Enzyme's Active Site to Template Inhibitors[END_REF] In 2002, following the disclosure of copper catalyzed click reactions by both Sharpless' and Meldal's teams [START_REF] Rostovtsev | A Stepwise Huisgen Cycloaddition Process: Copper(I)-Catalyzed Regioselective "Ligation" of Azides and Terminal Alkynes[END_REF][START_REF] Tornøe | Peptidotriazoles on Solid Phase: [1,2,3]-Triazoles by Regiospecific Copper(I)-Catalyzed 1,3-Dipolar Cycloadditions of Terminal Alkynes to Azides[END_REF] , "in situ click-chemistry" was coined and was applied for the first time to the model protein acetylcholinesterase. [START_REF] Lewis | Click Chemistry in Situ: Acetylcholinesterase as a Reaction Vessel for the Selective Assembly of a Femtomolar Inhibitor from an Array of Building Blocks[END_REF] Since then, enzymes but also other target families like transcriptional factors [START_REF] Willand | Exploring Drug Target Flexibility Using in Situ Click Chemistry: Application to a Mycobacterial Transcriptional Regulator[END_REF][START_REF] Wong | The Transcription Factor Stat5 Catalyzes Mannich Ligation Reactions Yielding Inhibitors of Leukemic Cell Proliferation[END_REF] , channels [START_REF] Grimster | Generation of Candidate Ligands for Nicotinic Acetylcholine Receptors Via in Situ Click Chemistry with a Soluble Acetylcholine Binding Protein Template[END_REF] or protein-protein interactions [START_REF] Kulkarni | Screening of Protein-Protein Interaction Modulators Via Sulfo-Click Kinetic Target-Guided Synthesis[END_REF] , have been explored using KTGS (Suppl. Table 1). The drugability of the KTGS protein pockets has also been recently studied. [START_REF] Unver | Druggability Assessment of Targets Used in Kinetic Target-Guided Synthesis[END_REF] The format of KTGS experiments itself evolved from binary to multicomponent approaches that were further completed within the orthogonal multicomponent setting 2 . As well, the set of KTGS compatible chemical reactions has been greatly expanded with the identification of reactions like the sulfoclick reaction by Manetsch's team [START_REF] Kulkarni | Screening of Protein-Protein Interaction Modulators Via Sulfo-Click Kinetic Target-Guided Synthesis[END_REF] , the hydrolysis/thio-Michael coupling by Renard's team [START_REF] Oueis | First Enzymatic Hydrolysis/Thio-Michael Addition Cascade Route to Synthesis of AChE Inhibitors[END_REF] , the amidation reaction [START_REF] Jaegle | Protein-Templated Formation of an Inhibitor of the Blood Coagulation Factor Xa through a Background-Free Amidation Reaction[END_REF] and the Mannich reaction [START_REF] Wong | The Transcription Factor Stat5 Catalyzes Mannich Ligation Reactions Yielding Inhibitors of Leukemic Cell Proliferation[END_REF] both by Rademann's team (Suppl. Table 2). In 2017, Wang et al. combined the covalent binding of a KTGS bifunctional precursor to the target with subsequent in situ click chemistry to discover new ligands for transferase [START_REF] Wang | Discovery of Cell-Permeable O-Glcnac Transferase Inhibitors Via Tethering in Situ Click Chemistry[END_REF] . Besides the increasing diversity of reactions, targeted protein types and KTGS formats, the biological characterization of templated ligands has also evolved. It now includes not only the in vitro activity on isolated targets but also cellular activities and more recently in vivo pharmacodynamics for imaging or therapy.

History and recent achievements

Efficient medicinal chemistry requires an optimal interplay between diversity generation and selection of structures with the best properties. KTGS has demonstrated in the past few years its potential to combine both. We review here the recent development and successful case studies, and provide an analysis of KTGS warhead-bearing reagents and ligands, to bring the medicinal chemists the full view of this promising drug discovery strategy and its added value over other diversity/selection methods.

KTGS DESIGN AND PRACTICAL ASPECTS

Our analysis of the literature points out that the main practical issues for KTGS, are the type of reactions, the detection methods and the choice of a good warhead-bearing reagent (Suppl. Table 2). 2 Most KTGS reactions are Huisgen 1,3-dipolar cycloaddition between azides and alkynes, i.e. in situ click-chemistry. This reaction accounts for 76% of the target-guided synthesis experiments (Figure 3) and the proportion of KTGS ligands obtained by in situ clickchemistry is 81% of all templated ligands. This high proportion is directly linked to the biocompatibility of alkynes and azides and their commercial and synthetic availability. Factor Xa inhibitor. [START_REF] Jaegle | Protein-Templated Formation of an Inhibitor of the Blood Coagulation Factor Xa through a Background-Free Amidation Reaction[END_REF] An activated carboxylic acid promotes the templated reaction (Figure 4A).

Chemical reactions

In particular, a -OCH2CF3 ester seems a better activated species as it does not produce any adduct with the amine in the absence of Factor Xa, even with increased temperature or reaction time. [START_REF] Jaegle | Protein-Templated Formation of an Inhibitor of the Blood Coagulation Factor Xa through a Background-Free Amidation Reaction[END_REF] This reaction could be widely used, as amide formation is still the most popular reaction in drug discovery [START_REF] Boström | Expanding the Medicinal Chemistry Synthetic Toolbox[END_REF] . Earlier, Gelin et al. had also described the KTGS templated formation of a dinucleoside inhibitor of the NADkinase from L.monocytogenes (LmNADK1), via an amide bond formation observed directly in X-ray co-crystals (Figure 4B and4C). [START_REF] Gelin | Screening and in Situ Synthesis Using Crystals of a NAD Kinase Lead to a Potent Antistaphylococcal Compound[END_REF] The first example of multicomponent reaction (MCR), previously published by Weber et al., used the Ugi reaction to identify inhibitors of thrombin (Figure 5A). 29 Another published example of KTGS using MCR is the Mannich ligation between formaldehyde, an amine and some aza-heterocycles, which led to the discovery of STAT5 inhibitors (Figure 5B). Noteworthy, Renard et al reported in 2014 an elegant strategy that uses the enzymatic activity of the target itself to generate at the catalytic site, thiol reagents from S-acylated precursors that further react in a KTGS "in situ thio-Michael reaction" with acrylamides. [START_REF] Oueis | First Enzymatic Hydrolysis/Thio-Michael Addition Cascade Route to Synthesis of AChE Inhibitors[END_REF] The selection and/or design of warhead-bearing reagents is crucial for the success of KTGS. An analysis of the published warhead-bearing reagents that led to KTGS ligands (Supp Table 1, Figure 6) shows that the main source of inspiration is known SAR or previously described inhibitors or modulators (62.5%). For example, KTGS use a benzylsulfonamide warhead to target COX-2, 30 a hydroxamate warhead to target metalloproteases, [START_REF] Deprez-Poulain | Catalytic Site Inhibition of Insulin-Degrading Enzyme by a Small Molecule Induces Glucose Intolerance in Mice[END_REF] a guanidine warhead to target Factor Xa [START_REF] Jaegle | Protein-Templated Formation of an Inhibitor of the Blood Coagulation Factor Xa through a Background-Free Amidation Reaction[END_REF] . Two different cognate ligands can also be used to produce bivalent ligands. For example, AChE inhibitors were discovered from derivatives of tacrine or huprine, that are catalytic site ligands, coupled to derivatives of phenanthridinium and 1,2,3,4tetrahydroisoquinolines, that are peripheral site ligands. [START_REF] Krasiński | In Situ Selection of Lead Compounds by Click Chemistry: Target-Guided Optimization of Acetylcholinesterase Inhibitors[END_REF][START_REF] Oueis | Reaction Site-Driven Regioselective Synthesis of AChE Inhibitors[END_REF] More than 12% of warhead-bearing reagents for enzyme-templated KTGS are inspired by the substrate or co-factor, like biotin [START_REF] Paparella | A Template Guided Approach to Generating Cell Permeable Inhibitors of Staphylococcus Aureus Biotin Protein Ligase[END_REF][START_REF] Tieu | Optimising in Situ Click Chemistry: The Screening and Identification of Biotin Protein Ligase Inhibitors[END_REF] or NAD [START_REF] Gelin | Screening and in Situ Synthesis Using Crystals of a NAD Kinase Lead to a Potent Antistaphylococcal Compound[END_REF] . A few warhead-bearing reagents were directly derived from drugs (9.4%) that are exclusively natural compounds: kanamycin 36 and solithromycin [START_REF] Jin | Ribosome-Templated Azide-Alkyne Cycloadditions Using Resistant Bacteria as Reaction Vessels: In Cellulo Click Chemistry[END_REF] . Among the reagents inspired by previous SAR (62.5%) some were highly inspired by drugs or clinical candidates like celecoxib [START_REF] Bhardwaj | In Situ Click Chemistry Generation of Cyclooxygenase-2 Inhibitors[END_REF] for COX2 inhibitors, rupintrivir (AG7088) [START_REF] Fu | Target-Guided Screening of Fragments (TGSOF) in the Discovery of Inhibitors against Ev-A71 3c Protease[END_REF] for enteroviral protease inhibitors or navitoclax (ABT-263) [START_REF] Kulkarni | Screening of Protein-Protein Interaction Modulators Via Sulfo-Click Kinetic Target-Guided Synthesis[END_REF] for Bcl inhibitors. More than 15% of KTGS ligands come from reagents that were identified by fragment screening, such as endothiapepsin inhibitors, [START_REF] Mondal | Fragment-Based Drug Design Facilitated by Protein-Templated Click Chemistry: Fragment Linking and Optimization of Inhibitors of the Aspartic Protease Endothiapepsin[END_REF] O-GlcNAc transferase inhibitors, [START_REF] Wang | Discovery of Cell-Permeable O-Glcnac Transferase Inhibitors Via Tethering in Situ Click Chemistry[END_REF] myelin-associated glycoprotein ligands [START_REF] Shelke | A Fragment-Based in Situ Combinatorial Approach to Identify High-Affinity Ligands for Unknown Binding Sites[END_REF] or STAT5 inhibitors [START_REF] Wong | The Transcription Factor Stat5 Catalyzes Mannich Ligation Reactions Yielding Inhibitors of Leukemic Cell Proliferation[END_REF] . Out of all templated ligands, 23.5% derive from nature-inspired warhead-bearing reagents (Figure 6B). A few teams designed genuine covalent inhibitors (4.8%, Figure 6C) by targeting cysteines during KTGS, discovering thus potent inhibitors of enteroviral protease [START_REF] Fu | Target-Guided Screening of Fragments (TGSOF) in the Discovery of Inhibitors against Ev-A71 3c Protease[END_REF] or O-GlcNAc transferase [START_REF] Wang | Discovery of Cell-Permeable O-Glcnac Transferase Inhibitors Via Tethering in Situ Click Chemistry[END_REF] . In this context, the warhead-bearing reagents must be bifunctional.

Warhead-bearing reagents

KTGS and other protein-templated reactions have sometimes been classified as an extension of fragment linking strategies. We thus analyzed both the distribution of the calculated parameters and structural features of reagents used for KTGS and compared these distribution with those of fragments (Figure 7 and8). First, most of the reagents used for KTGS, and warhead-bearing reagents in particular, do not comply to the Rule of 3 (Ro3) for fragments (Figure 7). For example, more than 75% display a number of HBD <=3, and 70% a cLogP <3, and 62% have a molecular weight higher than 300 g/mol (Figure 7 A, B andC). This is especially true for warhead-bearing reagents inspired from drugs and substrates. As it has been pointed out before, HBA is the most affected parameter. [START_REF] Köster | A Small Nonrule of 3 Compatible Fragment Library Provides High Hit Rate of Endothiapepsin Crystal Structures with Various Fragment Chemotypes[END_REF] Indeed, only 29% of these reagents display a number of HBA<=3, and they are exclusively non-azide (Figure 7 D and E respectively). In all, 82% of warhead-bearing reagents used in KTGS violate the Ro3. Examination of structural features shows that about 82% of warhead-bearing reagents contain between 10 and 30 heavy atoms (Figure 8A). Extreme values are displayed by natural compounds like aminoglycosides [START_REF] Rzuczek | A Toxic RNA Catalyzes the in Cellulo Synthesis of Its Own Inhibitor[END_REF] , ketolides [START_REF] Jin | Ribosome-Templated Azide-Alkyne Cycloadditions Using Resistant Bacteria as Reaction Vessels: In Cellulo Click Chemistry[END_REF] , cyclopeptides [START_REF] Hirose | Chitinase Inhibitors: Extraction of the Active Framework from Natural Argifin and Use of in Situ Click Chemistry[END_REF] or substrates adducts. In comparison, 81% of fragments, for which a fragment-protein complex is available in the PDB, display a number of heavy atoms between 10 and 16. [START_REF] Giordanetto | Fragment Hits: What Do They Look Like and How Do They Bind?[END_REF] About 90% of warhead-bearing reagents have a limited fraction of sp3-hybridized carbon atoms (Fsp3 < 0.6, Figure 8B) like fragments (90% with Fsp3 < 0.5). [START_REF] Giordanetto | Fragment Hits: What Do They Look Like and How Do They Bind?[END_REF] Half of warhead-bearing reagents display of a higher rotatable bonds number (53% between 2 and 6, Figure 8C) and more rings (50% have more than 2 rings, Figure 8D), than fragments. [START_REF] Giordanetto | Fragment Hits: What Do They Look Like and How Do They Bind?[END_REF] Their distribution of molecular shape index (spherical < 0.5 < linear) is centered at 0.55± 0.05 (41.1%, Figure 8E). Half of the reagents have a formal charge of 0, 32% are positively charged, only 8% display negative charges and 3% are zwitterionic (Figure 8F). In contrast, Shaw et al. showed a higher proportion of neutral compounds (68%), and twice more abundant negatively charged (22%) than positively charged compounds (11%) within a set of 462 fragments. [START_REF] Giordanetto | Fragment Hits: What Do They Look Like and How Do They Bind?[END_REF] Finally, reagents for KTGS usually display a potency or binding equal or below 500 µM while fragments usually bind the target at a millimolar concentration. KTGS is not thus exclusively a fragment linking strategy as it requires at least one reagent binding in an affinity range beyond the one of classical fragments. Three different types of formats for KTGS exist: either binary, multicomponent or orthogonal multicomponent. [START_REF] Bosc | Kinetic Target-Guided Synthesis in Drug Discovery and Chemical Biology: A Comprehensive Facts and Figures Survey[END_REF] A high majority of the KTGS publications report binary formats (67%, Figure 9 A) and a small library size of potential ligands. The multicomponent format (not to be mistaken for multi-component reactions) uses clusters of reagents instead of pairs of reagents and thus allows to access a larger number of putative ligands, exploiting the full potential of a kinetically driven competition between a large number of reagents. 14% of KTGS examples describe the exploration of more than 100 putative ligands (Figure 9 B). At last, in situ click-chemistry may produce 2 different regio-isomers (1,4-or 1,5-triazoles) with very different binding capabilities, from the same set of reagents. This thus doubles the number of possible ligands. There are differences in the size of KTGS experiments, expressed as the number of possible ligands. As a result, hit-rates range from 0.2% to 100%. Since many KTGS experiments have a limited size (less than 10 possible ligands for 46% of the examples Figure 9B) and are inspired from previously known SAR, some show a 100% hit-rate. Among the KTGS experiments with a minimum size of 30 possible ligands, 50% show a hit rate comparable to random screening (hit rate = 1-5%) (Figure 9C). Usually, for larger KTGS, the diversity is carried by only one type of reagents (not the warhead-bearing reagent). For example, Kwarcinski et al. disclosed a KTGS with c-Src, a nonreceptor tyrosine kinase from one thiol and 110 commercial acrylamide fragments resulting in 4% hit rate (110 possible ligands). [START_REF] Kwarcinski | Discovery of Bivalent Kinase Inhibitors Via Enzyme-Templated Fragment Elaboration[END_REF] IDE inhibitors were discovered from 90 diverse alkynes and 2 azides (360 putative ligands, 18.3% hit rate). [START_REF] Deprez-Poulain | Catalytic Site Inhibition of Insulin-Degrading Enzyme by a Small Molecule Induces Glucose Intolerance in Mice[END_REF] hDAO inhibitors were obtained from 1 alkyne and 250 diverse azides (500 putative ligands and 0.2% hit rate). 44 Mass-spectrometry-based protocols account for 85% of detection methods (Figure 10).

Formats, sizes, detection methods and hit rates

In recent years, several teams have described the use of high-resolution MS to confirm the molecular formula of KTGS ligands and to increase the signal/noise ratio. Other surrogate methods can be used, including the coupling of an activity assay to KTGS, or thermal shift assay. [START_REF] Wong | The Transcription Factor Stat5 Catalyzes Mannich Ligation Reactions Yielding Inhibitors of Leukemic Cell Proliferation[END_REF][START_REF] Kwarcinski | Discovery of Bivalent Kinase Inhibitors Via Enzyme-Templated Fragment Elaboration[END_REF] Several detection methods can even be used in parallel to confirm the formation of the KTGS ligands independently. [START_REF] Wong | The Transcription Factor Stat5 Catalyzes Mannich Ligation Reactions Yielding Inhibitors of Leukemic Cell Proliferation[END_REF] Unlike in FBDD, X-ray crystallography is not used as a generic method to detect ligand formation in KTGS. In the past however, X-ray crystallography allowed to discover unexpected ligands, like compound-substrate KTGS adducts for example.28 Thermodynamic and kinetic studies can also be performed to optimize KTGS experimental conditions before setting up larger experiments. For example Rademan et al.

measured the rate of the catalyzed amidation by a kinetic enzymatic assay to select the best reagents. 24 To select the best time range for the KTGS experiment, they analyzed the autoinhibition of the protein as a function of the ligand formation by HPLC-MS. Finally, the proteinligand complex was crystallized and its analysis evidenced a pattern of H-bonds between the protein and the reactive fragments, resulting in their activation. This evidenced how the binding mode of the reactive fragments impacts the mechanism of the protein-templated reaction.

In cellulo KTGS

So far, one of the limitations of KTGS is the need for high concentration, and therefore high quantities, of purified proteins. Though this drawback is attenuated by the use of multicomponent formats and may be overcome in the future by the generalization of microfluidics [START_REF] Wang | An Integrated Microfluidic Device for Large-Scale in Situ Click Chemistry Screening[END_REF] , it is partly responsible for the limited number of examples reported in the literature. Another consequence is that KTGS has also been only described for soluble protein targets. Hopefully, recently reported KTGS experiments performed directly in cells prove that it is possible to avoid target purification and to possibly expand the scope of KTGS to nonsoluble proteins. Disney et al. used in cellulo in situ-click chemistry to synthesize an inhibitor that rescued defect splicing in the myotonic dystrophy disease. [START_REF] Rzuczek | A Toxic RNA Catalyzes the in Cellulo Synthesis of Its Own Inhibitor[END_REF] Sellstedt et al, described the KTGS of a carbonic anhydrase II (CAII) inhibitor directly on cells (Figure 11A). [START_REF] Antti | Cell-Based Kinetic Target-Guided Synthesis of an Enzyme Inhibitor[END_REF] Andrade et al.

published the first ribosome-templated in cellulo in situ-click chemistry for the identification of solithromycin 1,4-triazole analogues, which activity was measured on a solithromycin resistant S.aureus stain (Figure 11B). [START_REF] Jin | Ribosome-Templated Azide-Alkyne Cycloadditions Using Resistant Bacteria as Reaction Vessels: In Cellulo Click Chemistry[END_REF] In 2015, Ohkanda et al., disclosed a diterpene-peptide conjugate that was templated in cells by protein 14-3-3 via a stable oxime formation. [START_REF] Parvatkar | Intracellular Generation of a Diterpene-Peptide Conjugate That Inhibits 14-3-3-Mediated Interactions[END_REF] This in cellulo KTGS format provides a huge advantage over KTGS using a purified target, specifically in the infectious diseases or oncology areas where the isolation of each single target protein mutant can require tremendous efforts. In the very near future, the in cellulo format will place KTGS as a target-engagement methodology by comparing KTGS outputs on wt-cells and ko-cells, or cells with/without a ligand.

CASE STUDIES Recent in vitro examples.

Inhibitors of endothiapepsin were recently obtained by Hirsch et al (Figure 12). [START_REF] Mondal | Fragment-Based Drug Design Facilitated by Protein-Templated Click Chemistry: Fragment Linking and Optimization of Inhibitors of the Aspartic Protease Endothiapepsin[END_REF] They derive from hydrazide (7a) and an S-alkylated isothiourea (7b), that were previously identified by screening of a library of fragments that did not all comply the Ro3 criteria (39% Ro3, 61% non Ro3). [START_REF] Köster | A Small Nonrule of 3 Compatible Fragment Library Provides High Hit Rate of Endothiapepsin Crystal Structures with Various Fragment Chemotypes[END_REF] By superimposing the X-ray structures of endothiapepsin-fragments complexes, and by linking fragments, authors modeled a potential triazole ligand. Four alkynes and nine azides were selected to perform an in situ click reaction that produced 4 hits (5.5% hit rate, out of 72 possible anti-or syn-1,2,3 triazoles). The identified ligands were shown to display anticonfiguration as predicted by earlier molecular modeling studies. This work produced a nonclassical inhibitor of an aspartyl protease. Docking of ligand 7 in endothiapepsin showed that 1,2,3-triazole ring are in close proximity to the catalytic dyad (Asp35, Asp219). These residues are thought to change the triazole pKa value and promote protonation of the heterocycle and further hydrogen bond with Asp35. 39 A recent paper by Kwarcinski et al., disclosed the discovery of bivalent c-SRC inhibitors via a thiol-acrylamide KTGS. [START_REF] Kwarcinski | Discovery of Bivalent Kinase Inhibitors Via Enzyme-Templated Fragment Elaboration[END_REF] The initial warhead-bearing reagent 8a is an aminopyrazole derivative (Figure 13A). To perform the KTGS, an enzyme where three cysteines were mutated into serines (3M-c-SRC: C277S, C483S, C496S), was produced and used to avoid side reactions of acrylamides derivatives with the enzyme. The KTGS was performed as a binary experiment between one thiol 8b and 110 acrylamides (Figure 13B) and provided 4 ligands (3.6% hit rate). Best final adduct 8 was 5-log more potent than the acrylamide precursor 8c (Figure 13C, Ki = 160 µM) or thiol precursor 8b (Ki = 200 µM). Adduct 8 displays a higher ligand-efficiency than 8a, and it is selective towards a panel of kinases thanks to the allosteric moiety brought by the acrylamide precursor. This allows 8 to bind both at the ATP binding site (hinge region) and to the P-loop, explaining selectivity (Figure 13D). [START_REF] Kwarcinski | Discovery of Bivalent Kinase Inhibitors Via Enzyme-Templated Fragment Elaboration[END_REF][START_REF] Statsuk | Tuning a Three-Component Reaction for Trapping Kinase Substrate Complexes[END_REF] KTGS was successful to identify potent inhibitors of s-SRC kinase while all previously identified P-loop binding inhibitors had been discovered by structure-based drug design. KTGS was also used for the discovery of covalent inhibitors of 3C cysteine protease of the enterovirus A71. [START_REF] Fu | Target-Guided Screening of Fragments (TGSOF) in the Discovery of Inhibitors against Ev-A71 3c Protease[END_REF] For this, authors used the bifunctional reagent 9a that bears Michael acceptor group as the covalent warhead to tether it to the catalytic Cys141, and a ketoaldehyde group to further react with 28 different ketones via aldol KTGS. Two pyridine-based covalent irreversible inhibitors were then detected by mass-spectrometry analysis of the whole protein (Figure 14A). Binding analysis of templated ligand 9b, showed that its pyridine group fits in the P3 pocket of the enzyme (Figure 14B). Further replacement of the α,β-unsaturated ester of 9b by an aldehyde provided a sub-micromolar reversible inhibitor 9 (IC50 = 0.15 µM), ten-fold more potent than rupintrivir, a rhinovirus 3C-protease inhibitor under development for the treatment of rhinovirus infections, or twice more potent than reference inhibitor NK1.8k (IC50 = 0.32 µM). 49 Ribosome is the biological target of ketolides like solithromycin and telithromycin (Figure 15A). A recent report describes the obtention of analogues of solithromycin using KTGS. [START_REF] Glassford | Ribosome-Templated Azide-Alkyne Cycloadditions: Synthesis of Potent Macrolide Antibiotics by in Situ Click Chemistry[END_REF] This fluoroketolide displays a substituted triazole that binds a third region in the bacterial ribosome as compared to other ketolides. The multicomponent experiment allowed a rapid screening of analogues. Both syn-and anti-triazoles were detected and compound 10 displayed similar therapeutic activity as solithromycin (Figure 15B). The transfer of N-acetylglucosamine from UDP-N-acetylglucosamine (UDP-GlcNAc) to proteins is ensured by the enzyme O-GlcNAc transferase (OGT). These post-translational events are key in the control of pathways that can be disregulated in diseases such as metabolic diseases. Wang et al. disclosed an original "mixed" tethered / multicomponent KTGS strategy to discover inhibitors of this enzyme that were further used to explore the regulation of N-acetylglucosamination in cells (Figure 17A). [START_REF] Wang | Discovery of Cell-Permeable O-Glcnac Transferase Inhibitors Via Tethering in Situ Click Chemistry[END_REF] A bifunctional covalent warhead-bearing reagent (iodo-acetamide azide) 12a reacted first with OGT cysteines, then mixtures of alkynes were added (Figure 17A). Fourteen hits were identified. Then, the electrophilic group of best compound 12b was removed to provide the cell-permeable, non-cytotoxic, non-competitive, non-covalent inhibitor 12 (Figure 17B). Docking experiments allowed to propose a binding mode within the enzyme (Figure 17B). 12 was tested in COS-7 cells and showed to reduce the quantity of O-GlcNAcase, a protein that catalyzes the opposite reaction and whose quantities are reduced when OGT is inhibited.

Recent in vivo examples.

In 2013, Kolb et al disclosed a PET-scan probe targeting carbonic anhydrase II (CAII), from a 19 F-containing fragment library and the 4-ethynyl benzenesulfonamide (Kd = 37nM) as a warhead binding the catalytic Zn 2+ ion (Figure 18A). [START_REF] Mocharla | From in Situ to in Vivo: An in Situ Click-Chemistry-Derived Carbonic Anhydrase Ii Imaging Agent for Positron Emission Tomography[END_REF] The probe [ 18 F]-13 (Figure 18B) was then synthesized from the nitro-containing, dimethoxytrityl-sulfonamide protected analogue and then converted to the labeled derivative with [ 18 F]-fluoride, in the presence of crown-ether in acetonitrile, followed by deprotection and HPLC purification. The probe was directly administered to mice (Figure 18C) and its distribution was monitored over 1 hour. The probe distributed in some organs (heart, kidney), and tissues (blood) consistently with the expression and distribution of CAII. Authors checked that the probe mainly bind red blood cells (RBC) rather than plasma (90/10 ratio) in blood. No defluorination during the experiment was observed. In 2015, we disclosed the first insulin-degrading enzyme inhibitor discovered by KTGS which was active in vivo. [START_REF] Deprez-Poulain | Catalytic Site Inhibition of Insulin-Degrading Enzyme by a Small Molecule Induces Glucose Intolerance in Mice[END_REF] The experiment was run as an orthogonal multicomponent set up (Figure 19A). Best compound, 14 (BDM4478), displayed good ADME properties (Figure 19A).

In particular, its hydroxamic function was shown to be stable towards esterase hydrolysis. [START_REF] Hermant | Controlling Plasma Stability of Hydroxamic Acids: A Medchem Toolbox[END_REF] It interacts with the zinc ion of Insulin degrading enzyme and shifts the equilibrium towards the close conformation of IDE (Figure 19B). In an in vivo glucose tolerance test, 14 enhances glucose intolerance in an IDE-dependent manner (Figure 19C). This compound allowed us to invalidate this enzyme as a type-2-diabetes target.

Using KTGS, Kolb et al also identified several inhibitors of hCOX-2 that display the benzenesulfonamide warhead from celecoxib (Figure 20A). Inhibitor 15 was further labeled with [START_REF] Willand | Exploring Drug Target Flexibility Using in Situ Click Chemistry: Application to a Mycobacterial Transcriptional Regulator[END_REF] F to be used in vivo as a PET-scan probe. [START_REF] Kolb | A method for the preparation of imaging probes using click chemistry[END_REF] STAT5b inhibitors prevent dimerization of phosphorylated STAT5b, thus inhibiting transcription of genes implicated in cancer cells proliferation and survival (Figure 21A).

Rademann et al combined fragment screening and a Mannich-based KTGS (Figure 5B) to discover new STAT5b inhibitors from the 1,2,5-oxadiazole warhead-bearing reagent 4a (Figure 21B). [START_REF] Wong | The Transcription Factor Stat5 Catalyzes Mannich Ligation Reactions Yielding Inhibitors of Leukemic Cell Proliferation[END_REF] This is the first series of protein-templated inhibitors of STAT5b. Several hits (4x-z) displayed micromolar-range inhibition of a phosphopeptide-STAT5b interaction. In particular compound 4x (1.4 µM) was shown to engage the target in cells (CETSA ΔTm = 8°C) with an in cell target occupancy concentration (OC50) of 28 µM (Figure 21C) evaluated by ITDRF (Isothermal dose-response fingerprint). Its methyl ester prodrug 4z inhibits proliferation of cancer cells with an IC50 of 25µM. A more lipophilic analogue of 4x, compound 4y, induces tumor regression at 200 mg/kg (Figure 21C). KTGS has already been applied to 26 different targets from various classes (Figure 23A). 73% of these targets are enzymes, 8% protein-protein interactions, and 8% transcriptional receptors and 4% channels (allosteric site). Among these targets, 38% have already yielded to clinical compounds or marketed drugs and 62% are either new targets or druggable targets for which some preclinical ligands have been disclosed showing that KTGS is used in very early phases of drug-discovery (Figure 23B). This shows that KTGS can be successfully applied to "old" and new targets. For enzymes, all subclasses have been explored, hydrolases and transferases being the most popular ones (Figure 23C). As mentioned above, all these targets are soluble: enzymes, protein-protein interaction partners, transcriptional receptor. The ligand-gated ion channel example reported in the literature is acetylcholine binding protein (AChBP), a soluble extracellular domain, homologue of nicotinic acetylcholine receptors (nAChRs) allosteric site that is secreted by mollusks. [START_REF] Grimster | Generation of Candidate Ligands for Nicotinic Acetylcholine Receptors Via in Situ Click Chemistry with a Soluble Acetylcholine Binding Protein Template[END_REF] In the past years, new families of targets have been tackled by KTGS such as transferases (ribosome and glycosyltransferase) and the four classes of proteases: metalloproteases (IDE), serine proteases (factor Xa), aspartylproteases (endothiapepsine), cysteine proteases (enteroviral EV Cys protease).

Other preliminary disclosures, and thus not included in this study, mention KTGS experiments on new proteins to discover inhibitors of the isomerase MIF (macrophage migration inhibitory factor) in autoimmune diseases & immuno-oncology, [START_REF] Marzinzik | Kinetic Target Guided Synthesis for the Identification of Macrophage Migration Inhibitory Factor Inhibitors (Mif)[END_REF] ligands of Mcl1, for protein-protein interactions in cancer, [START_REF] Manetsch | Target Binding Molecules Identified by Kinetic Target-Guided Synthesis[END_REF] or multitarget inhibitors of BACE-1 and kinases in Alzheimer's disease [START_REF] Palomo | in situ-click chemistry: an ideal target based approach for the generation of multitarget drugs[END_REF] .

Protein pockets and conformation

Hirsch and co-workers recently analyzed the geometry and the physicochemical properties of catalytic pockets of a set of 12 targets out of the 23 proteins used at the time of their paper (Table 1). [START_REF] Unver | Druggability Assessment of Targets Used in Kinetic Target-Guided Synthesis[END_REF] Since no targets for which KTGS failed are reported, the « negative » control of comparison was a set randomly chosen of 20 protein targets with an approved drug.

The different pockets were given a score considering their size, depth, enclosure, surface, and nature of amino acids. The parameters studied in this work showed a high variance due to the limited available data of the restricted number of reported targets successfully used in KTGS.

Although, the mean depth of KTGS pockets (Table 1) is very similar to the reference set (26 Å vs 26.5 Å), the former contain more polar amino acids, and are slightly wider (1445 Å 3 vs 1338 Å 3 ). Besides, enclosure score of the KTGS pockets (Table 1), considering simulated solvent exposure, resulted to be significantly different from the negative control (0.114 vs 0.077). This suggests that the KTGS pockets are less deep and more open. The authors speculate that the more exposed pockets in reported KTGS examples may allow a better diffusion of reagents within this pocket and contribute to the success of the templated-reaction. Still these results might be biased by the fact that the KTGS target set contained three PPI targets (among which Bcl-XL and 14-3-3 protein) that are typically larger and very shallow. However, no particular physico-chemical property let distinguish KTGS pockets from the reference set, suggesting that KTGS can have a large target scope, regardless the geometry and properties of the active sites. The authors also showed that the parameters measured for KTGS pockets qualify them as "druggable" pockets as defined by Vollkamer et al. [START_REF] Masini | Druggability of the Enzymes of the Non-Mevalonate-Pathway[END_REF] Supplementary Table 1 gathers all the binding pockets of KTGS ligands for each example fully disclosed in the literature. For enzymes, almost all ligands target the catalytic site. This is not surprising because warhead usually target specific features of this site. Still a few example report new binding pockets and/or new conformations. KTGS is indeed complementary to X-ray crystallography, NMR of proteins and molecular modeling as it can evidence unknown and less abundant protein conformations. For example, a new "open-gate" conformation, due to an unexpected flip of two phenylalanine residues, was discovered during the KTGS formation of the triazole ligand in TbEthR. It unveiled a new pocket within the protein.

This new conformation impacted the activity of this transcriptional repressor. [START_REF] Willand | Exploring Drug Target Flexibility Using in Situ Click Chemistry: Application to a Mycobacterial Transcriptional Regulator[END_REF] Inhibitor 14 of hIDE, interacts with the catalytic site formed by both IDE-N and IDE-C and impacts the dynamics of the door subdomain of the enzyme thus impacting its catalytic activity. [START_REF] Zhang | Ensemble Cryoem Elucidates the Mechanism of Insulin Capture and Degradation by Human Insulin Degrading Enzyme[END_REF] Bourne et al showed recently that the binding of one KTGS warhead-bearing reagent to AChE induces the motion of a histidine residue in the catalytic site, along with an unprecedented motion of a tyrosine residue in the gorge of the protein. These conformational changes within the protein result in the formation of the preferred KTGS 1,5-triazole ligand. 59 b The longest distance between solvent and buried part of the pocket. c Portion of the lid of the pocket compared to the hull. d Ratio between solvent-exposed to hull grid point.

Chemical space and ligand efficiency of KTGS ligands

The KTGS strategy offers the possibility to explore a chemical space wider than the Ro5 space. Most of the templated ligands do not observe the Lipinski-Veber rules for at least one (74%) or two (62%) molecular properties but significant proportions of the KTGS ligands comply the beyond the rule-of-5 (bRo5) rule, mainly around the frontier of the Ro5 chemical space. Therefore most of the KTGS ligands (82%) are in the « possible to be oral » chemical space (Figure 24) as defined by Doak et al. [START_REF] Doak | Oral Druggable Space Beyond the Rule of 5: Insights from Drugs and Clinical Candidates[END_REF] For example, while only 38% of KTGS ligands fulfill the Ro5 range for MW whereas 97% of them fulfill the Doak's MW range (ie. MW ≤ 1000). The physico-chemical and structural parameters of KTGS ligands were plotted against the ones of FDA approved drugs (Suppl. Fig. 1 &2). Except for the four KTGS ligands that contain sugar moieties, all compounds distribute well within the chemical space defined by FDA approved drugs (Suppl. Fig. 1). A one-to-one comparison for each parameter (Suppl. Fig. 2) via box plots shows that KTGS ligands display a larger size (MW), are more flexible (rotatable bonds) and more polar (PSA) compared to the FDA approved drugs. Regarding rotatable bonds, a high variance is observed for KTGS ligands and the histogram distribution shows two populations of ligands: one centered on nRot = 6-7 and one centered on nRot =12-13 (Suppl. Fig. 2). As stated earlier by Doak et al for oral drugs, the HBA parameter is largely conformations. [START_REF] Willand | Exploring Drug Target Flexibility Using in Situ Click Chemistry: Application to a Mycobacterial Transcriptional Regulator[END_REF][START_REF] Deprez-Poulain | Catalytic Site Inhibition of Insulin-Degrading Enzyme by a Small Molecule Induces Glucose Intolerance in Mice[END_REF] Target types range from enzymes to more "recent" RNA or protein-protein interactions. Binding sites span from catalytic pockets, allosteric sites, protein-interaction sites, to phosphate sites. In addition, already 4 examples of KTGS-discovered ligands have been tested in vivo for imaging or therapeutic intervention. The synthetic toolbox of KTGS has increased in the past couple of years to include multicomponent reactions and amidation, two favorite reactions of medicinal chemists. [START_REF] Boström | Expanding the Medicinal Chemistry Synthetic Toolbox[END_REF] It now encompasses 9 different types of reactions.

The ligands discovered by these newly developed KTGS reactions bear in their structure obvious disconnection points that facilitate their optimization.

A major current limitation of KTGS is the need for soluble protein at large amounts. As a consequence, several target types, like membrane bound receptors, have not been explored so far. Another drawback may be the need for biocompatible reagents as KTGS is performed in aqueous media. This explains why 1,3 cycloadddition from azide and alkynes is so popular as both azides and alkynes are biocompatible. Moreover, if one uses electrophile reagents like acrylamides, it may be necessary to produce a protein mutant deprived of cysteine residues to avoid side reactions. The success of KTGS greatly depends also on the type of warheadbearing reagent used to target pockets within the protein of interest. We evidenced that these warhead-bearing reagents come from either drugs, known SAR or new fragments. Finally one limitation is the detection of the templated ligand by mass-spectrometry. Still, this problem is not as critical for KTGS than for DCC where an enrichment in one compound within a dynamic library must be observed. The continuous improvement of MS sensitivity/selectivity will undoubtedly increase the usefulness and spread of KTGS in the future.

On-going opportunities for KTGS include the development of covalent inhibitors, the combination with FBDD, the in cellulo KTGS, the qualification of new MCR, detection methods and collaborative networks. Already 5% of KTGS ligands are covalent inhibitors. Future development could make use of warhead-bearing reagents that display alternative reactive groups to fine-tune binding kinetics of such inhibitors. [START_REF] Gehringer | Emerging and Re-Emerging Warheads for Targeted Covalent Inhibitors: Applications in Medicinal Chemistry and Chemical Biology[END_REF] Also, 15.6% of the reported examples started from a fragment screening. With the largely used fragment screening it is expected that more examples that combine these 2 strategies will emerge. In cellulo KTGS allows now to explore intra-cellular targets. Theoretically this decreases also the use of large amounts of protein to be isolated and gives access to a more relevant cellular context. However, the ligand formed by a protein-templated reaction between reagents that cross cell membrane, or bacterial walls, will not be necessarily as penetrant as its precursors. This should be taken into consideration. The multicomponent and orthogonal multicomponent formats should be widely used also to decrease the protein amounts required and take the full benefit of a kinetically driven competition between large sets of reagents. Regarding chemical reactions amenable for KTGS, the development of multicomponent reactions is highly desirable in the future. In the course of the writing of this review, Van der Veken's team reported a systematic study to develop a protein-templated version of a 3-component reaction (Groebke-Blackburn-Bienaymé) for the discovery of urokinase inhibitors. [START_REF] Gladysz | Efforts Towards an Version of the Groebke-Blackburn-Bienaymé (GBB) Reaction for Discovery of Druglike Urokinase (UPA) Inhibitors[END_REF] Such an exhaustive study of experimental parameters should be applied to all new KTGS reactions. As well, a systematic study of the stability and integrity of the target protein should be performed to "qualify" the target for KTGS. [START_REF] Hartman | Protein-Templated Dynamic Combinatorial Chemistry: Brief Overview and Experimental Protocol[END_REF] In the future, the use of several detection methods in parallel like massspectrometry and biochemical assay will help to expand the use of KTGS, and further technological development could include the use of [START_REF] Wong | The Transcription Factor Stat5 Catalyzes Mannich Ligation Reactions Yielding Inhibitors of Leukemic Cell Proliferation[END_REF] F-ligand-based NMR, already used for DCC, as a detection method. [START_REF] Ekström | Non-Invasive 19 F NMR Analysis of a Protein-Templated N-Acylhydrazone Dynamic Combinatorial Library[END_REF] Finally, as the success of KTGS depends also on the diversity sets of reagents used, there is a high opportunity for shared reagents libraries to expand KTGS use and the size of experiments. Precompetitive collaboration in this area is thus highly desirable.

In all, this review and the in-depth analysis of all published examples demonstrated the robustness and versatility of KTGS and its utility as a method combining in a single step diversity generation and selection method in the three stages of drug discovery: hit discovery, hit-to-lead and lead optimization.

Figure 1 :

 1 Figure 1: Principles and terminology for target-guided synthesis. a a preferred terms are checked. (A) i. Principle of Dynamic Combinatorial Chemistry (DCC) where the target shifts the equilibrium towards the most affine ligand. ii. Principle of Kinetic Target Guided synthesis (KTGS) where the target brings in close proximity the affine reagents so that they can irreversibly react to form the final ligand. (B) Wording for KTGS experiments in the literature and proposed terminology (checkbox).

Figure 2 :

 2 Figure 2 : Timeline for KTGS and in situ click chemistry development & use.

Figure 3 :

 3 Figure 3 : KTGS reactions. a a From published examples

Figure 4 :

 4 Figure 4 : Kinetic Target-guided Amide formation. a a (A) KTGS amidation using activated carboxylic acid reagents produced factor Xa inhibitor 1. 26 ; (B) KTGS amidation in LmNADK and subsequent synthetic optimization of ligand; (C) Binding of 2 (blue) in NAD pocket (orange) of LmNADK (PDB: 3v8p). Key warheads are highlighted in salmon.

19

 19

Figure 5 :

 5 Figure 5 : Multicomponent reactions in KTGS. a a (A) First example of an Ugi templated reaction by thrombin; (B) Mannich templated reaction by STAT5b from an amine fragment containing an amidine warhead. Warheads are highlighted in salmon. CLEC: crosslinked enzyme crystals.

Figure 6 :

 6 Figure 6 : Origin and nature of warhead-bearing reagents. a a (A) Previous SAR account for 62.5 % of warhead-bearing reagents origins; (B) More than 75% of warhead-bearing reagents are synthetic compounds. (C) Almost 5% of warhead-bearing reagents are bifunctional and thus lead to covalent KTGS ligands.

Figure 7 :

 7 Figure 7 : Counts of MW, cLogP, HBA, HBD for warhead-bearing reagents. a a In salmon, the proportion of warhead-bearing reagents that fulfil the Ro3 limit for a given count. (A) MW in g/mol, (B) cLogP, (C) HBD, (D) HBA, (E) HBA sorted by reactive chemical moiety, (F) Ro3 violations. In total only 18% of warhead-bearing reagents fulfill all the Ro3 critera. The most stringent parameter being HBA.

Figure 8 :

 8 Figure 8 : Structural features of warhead-bearing reagents. a a Distribution (N=34) of the (A) number of heavy atoms, (B) fraction of sp3 hybridized carbon atoms (FCsp3), (C) number of rotatable bonds, (D) number of rings, (E) shape index, (F) formal charges.

Figure 9 :

 9 Figure 9 : Format, size and hit rate of KTGS. a a (A) Format types of reported KTGS, (B) Size of the KTGS experiment expressed as the number of putative ligands. 25% of KTGS experiments size > 50 putative ligands. (C) Proportion of KTGS with a given hit rate, restricted to KTGS with a size > 30 putative ligands.

Figure 10 :

 10 Figure 10 : Templated ligand detection methods. a 85% of detection methods of ligand rely on mass spectrometry.

Figure 11 :

 11 Figure 11 : Examples of in cellulo KTGS. a a (A) Identification of templated bCAII ligand in red blood cells 46 ; (B) Identification of a ribosome ligand in a S.aureus strain resistant to erythromycin 37 ; Key pharmacophores are highlighted in salmon.

Figure 12 :

 12 Figure 12 : Combination of non Ro3 fragment-based & KTGS linking. aa FBDD identified fragments that bound the catalytic dyad of the aspartyl protease endothiapepsin. Azides and alkynes were derived from these fragments and KTGS allowed the identification of 4 ligands.

Figure 13 :

 13 Figure 13 : Discovery of c-SRC inhibitors. a a (A) Promiscuous kinase inhibitor 8a that inspired the warhead-bearing reagent 8b; (B) Protein templated reaction by kinase 3M-c-SRC protein, mutated on cysteines to avoid undesired side reactions with the pool of acrylamides; (C) activities of precursor 8c; (D) putative binding mode of final hit 8, that interacts with the hinge reagion through the aminopyrazole group and with the P-loop of SRC via the furanylpyrrolidine group. Aminopyrazole pharmacophore is highlighted in salmon. wt: c-Src wild type; 3M-c-SRC: mutated c-Src (C277S, C483S, C496S).

Figure 14 :

 14 Figure 14 : Discovery of enteroviral protease inhibitors. a a (A) The ligation of precursor 9a reacts with Cys141of EV-A71 3C pro via its Michael acceptor group. Then the aldol KTGS between α-ketoaldehyde moiety and ketones yields to covalent ligands detected by mass spectrometry of the protein. (B) Binding of best ligand 9b (orange bond: covalent bond with Cys141) and optimized reversible analogue 9, in which the α-β, unsaturated ester has been replaced by an aldehyde. Electrophilic warhead is highlighted in salmon.

Figure 15 :

 15 Figure 15 : Optimization of macrolides. a a (A) Binding pocket of telithromycin within ribosome 70S (from PDB 4v7z) and structure, binding affinity and activity of solithromycin; (B) 15-multicomponent KTGS between azide 10a and 10 diverse alkynes and structure of inhibitor 10 identified by KTGS with similar activities than solithromycin. The warhead is highlighted in salmon.

Figure 16 :

 16 Figure 16 : Fluorescent probes of BPL. a a KTGS probe synthesis via various Biotein Protein Ligases (PBL) and structure of the fluorescent probe 11. Biotin warhead is highlighted in salmon.

Figure 17 :

 17 Figure 17 : Cell-permeable O-GlcNAc transferase inhibitors. a a (A) Tethering-in situ click chemistry (TISCC) to discover inhibitors of O-GlcNAc transferase (OGT): iodinated azide reacts covalently with OGT protein (Tethering), then templated reaction of triazole from a pool of 61 azides allowed the identification of 14 hits ; (B) Non-competitive inhibitor 12 derived from covalent KTGS ligand 12b by removal of iodo-acetamide group. Putative binding site of 12 in OGT (grey, PDB code : 3PE4), peptidic inhibitor in blue, UDP in black, APNT binding residues in orange. Electrophilic warhead is highlighted in salmon.

Figure 18 :

 18 Figure 18 : Discovery of a PET-scan probe for carbonic anhydrase II. a a (A) KTGS of bCAII ligands from azides and benzylsulfonamide warhead. (B) structure of probe [ 18 F]-13, direct 18 Flabeled analogue of a KTGS-hit 13 and its stability and distribution measured by PET scan. RBC: red blood cells.

Figure 19 :

 19 Figure 19 : Inhibitor of Insulin-degrading enzyme. aa (A) KTGS by hIDE-CF using an orthogonal multicomponent strategy, from 2 azides bearing an hydroxamic acid warhead and 90 diverse alkynes; Best hIDE inhibitor 14 (BDM44768) and its ADME and selectivity properties; (B) 14 (orange sphere), shifts open/closed equilibrium of hIDE towards closed conformations, measured by Small Angle X-ray scattering (SAXS); (C) Inhibition of hIDE by 14 and effect on in vivo glucose tolerance as the ratio of glucose AUC treated/non treated. The effect is IDE dependent (wt vs IDE ko). ns: non significative; CF: cysteine-free.

  In 2017, Wuest et al designed a multicomponent experiment to identify 2 potent 1,4-triazole inhibitors of COX-2. The experiment involved 4 azides 16a-d and 11 alkynes 16e-o to give potentially 88 adducts (either 1,4 or 1,5triazoles). Two hits (16 and 16') were identified (2.2% hit rate), with an IC50 of 50 and 90 nM respectively, in the range of the IC50 of celecoxib (70 nM). The compounds were also active in a cellular assay on HCA-7 colorectal cancer cell lines. 16 and 16' were tested in an in vivo model of inflammation (carrageenan-induced rat paw edema) and were shown to be more potent than celecoxib in that model.

Figure 20 :

 20 Figure 20 : hCOX-2 inhibitors in vivo. a a (A) Structure of the drug celecoxib; and of the PET-scan probe 15, labeled analogue of a KTGS ligand inspired by celecoxib; (B) KTGS of COX-2 inhibitors from celecoxib -inspired azides 16a-d and 11 alkynes 16e-o and structures and activities of KTGS ligands 16-16' in an inflammation rodent model. Biaryle pharmacophore is circled with an orange dotted line; sulfonamide or sulfoxide warhead is highlighted in salmon.

Figure 21 :

 21 Figure 21 : Cellular and in vivo activity of STAT5b inhibitors discovered by KTGS. a a (A) Mode of action of STAT5b inhibitors; (B) FBDD allowed the identification of a fragment 17a and subsequent KTGS gave STAT5b inhibitors 4x-z; (C) in vitro and in vivo activities of KTGS ligands 17b-d. b measured by fluorescence polarization assay with labeled phosphotyrosine peptide and fused maltose-binding protein(MBP)-STATb-SH2; c measured in BaF3/FLT3-ITD cells; d quantified by western-blot after 6h; e measured by cellular thermal shift assay (CETSA) -ITDRF; f measured in BaF3/FTL3-ITD xenograft tumor model.RELEVANCE OF KTGS FOR MEDICINAL CHEMISTRY AND DRUG DISCOVERY

Figure 22 :

 22 Figure 22 : KTGS experiments sorted by therapeutic areas . a a Other: endothiapepsine is a model enzyme for aspartylproteases involved in different therapeutic areas. O-GlcNAc transferase was classified in metabolic diseases for its implications in insulin resistance, diabetic complications though it is also implicated in other areas also like cardiovascular diseases or Alzheimer's disease 25 .

Figure 23 :

 23 Figure 23 : Targets tackled by KTGS. a a (A) Proportion of KTGS examples by target types. Enzymes account for more than 70% of the cases. (B) Proportion of targets with approved drug or clinical candidates. (C) Number of KTGS examples by enzyme family, showing that almost all enzymes classes can be targeted by KTGS.

Figure 24 :

 24 Figure 24 : Structural features of KTGS ligands. a a Distribution of the (A) MW, (B) cLogP, (C) number of rotatable bonds, (D) number of HBA, (E) number of HBD, (F) PSA for KTGS ligands (1 example selected/KTGS experiment). 38% of KTGS ligand fulfill the classical druglike rules for all parameters but 82% fit within the Doak's possibly oral chemical space (MW ≤ 1000; -2 ≤ cLogP ≤ 10; HBD ≤ 6; HBA ≤ 15; PSA ≤ 250 Å 2 ; rotatable bonds ≤ 20). In salmon filled boxes: rule of 5/Veber compliant compounds; In orange open boxes: "possibly oral chemical space".

Table 1 :

 1 KTGS Pockets features a .

	volume
	(Å 3 )

depth (Å) b Enclosure c fraction of apolar amino acids d

	KTGS pockets	1445	26	0.114	0.42
	Reference set of drug pockets	1338	26.5	0.077	0.53

a Adapted from Hirsch et al.

awarded the joined French Medicinal Chemistry Society-Servier Prize (2009) and is a member of the Institut Universitaire de France (2015). Her team is part of the drug discovery lab INSERM U1177 (Univ Lille and Institut Pasteur de Lille). She has published more than 60 papers. Her recent research interests include the use of kinetic target guided synthesis to identify drug-like inhibitors of metalloenzymes.

ORCID #0000-0002-3318-5297

responsible for the increased PSA of high-molecular weight compounds. [START_REF] Doak | Oral Druggable Space Beyond the Rule of 5: Insights from Drugs and Clinical Candidates[END_REF] As well, the fact that KTGS ligands show higher PSA values in comparison with FDA drugs, could be correlated to the increase of HBA number. Out of the KTGS ligands, 72% have a lipophilic ligand efficiency (LLE) above 3 (Figure 25A), with a mean of 5.0 and a median of 4.9. This qualifies KTGS ligands as good starting points for medicinal chemistry efforts. Importantly, KTGS itself increases LLE (from warhead-bearing reagent to final ligand) (Figure 25B) up to 6 units, making it a valuable tool for ligand optimization.


Adrien Herledan
email: adrien.herledan@inserm.fr.

Marine Andres

Aurore Lejeune-Dodge

Florence Leroux

Alexandre Biela

Catherine Piveteau

Sandrine Warenghem

Cyril Couturier

Benoit Deprez

Rebecca Deprez-Poulain

Biela Alexandre

Drug Target Engagement using coupled Cellular Thermal Shift Assay -acoustic Reverse Phase Protein Array

Keywords: Target Engagement, CETSA, RPPA, Acoustic transfer, Drug Discovery, Nanovolume, Insulin-Degrading Enzyme

In the last five years, Cellular Thermal Shift Assay, a technology based on ligandinduced changes in protein thermal stability, has been increasingly used in drug discovery to address the fundamental question of whether drug candidates engage their intended target in a biologically relevant setting. To analyze lysates from cells submitted to increasing temperature, the detection and quantification of the remaining soluble protein can be achieved using quantitative mass spectrometry, Western blotting or AlphaScreen® techniques. Still, these approaches can be time-and cellconsuming. To cope with limitations of throughput and protein amount requirements, we developed a new coupled assay combining the advantages of nano-acoustic transfer system and reverse phase protein array technology within CETSA experiments. We validated the technology to assess engagement of inhibitors of Insulin Degrading Enzyme (IDE), an enzyme involved in diabetes and Alzheimer's disease. CETSA -acoustic Reverse Phase Protein Array (CETSA-aRPPA) allows simultaneous analysis of many conditions and drug-target engagement with small sample size, and in a rapid, cost-effective and biological material-saving manner.

Introduction

In the past few years, Cellular Thermal Shift Assay (CETSA) has emerged as an essential tool to explore target engagement and target validation in drug discovery, directly in the complex environment of intact cells. [START_REF] Comess | Emerging Approaches for the Identification of Protein Targets of Small Molecules -A Practitioners' Perspective[END_REF] It is increasingly used also to guide medicinal chemistry efforts and lead optimization. [START_REF] Lundgren | Focusing on Relevance: CETSA-Guided Medicinal Chemistry and Lead Generation[END_REF][START_REF] Shaw | Positioning High-Throughput CETSA in Early Drug Discovery through Screening against B-Raf and PARP1[END_REF] CETSA is based on the ligandinduced stabilization of the targeted protein (Fig. 1A).2 After lysis of cell samples previously incubated in the presence or absence of ligand and subsequently heated at various temperatures, aggregation protein profile is determined by measuring folded protein remaining in the cell lysate. The alteration of heat-induced aggregation by a small molecule binding to the protein, causes a shift (also referred to as thermal shift) in the aggregation temperature (Tagg). Along with the increasing use of CETSA, various detection methods have been developed,2 either based on homogeneous detection, [START_REF] Jafari | The Cellular Thermal Shift Assay for Evaluating Drug Target Interactions in Cells[END_REF][START_REF] Almqvist | CETSA Screening Identifies Known and Novel Thymidylate Synthase Inhibitors and Slow Intracellular Activation of 5-Fluorouracil[END_REF] high-resolution mass spectrometry, [START_REF] Savitski | Tracking Cancer Drugs in Living Cells by Thermal Profiling of the Proteome[END_REF][START_REF] Franken | Thermal Proteome Profiling for Unbiased Identification of Direct and Indirect Drug Targets Using Multiplexed Quantitative Mass Spectrometry[END_REF] or image analysis [START_REF] Axelsson | In Situ Target Engagement Studies in Adherent Cells[END_REF][START_REF] Massey | A High Content, High Throughput Cellular Thermal Stability Assay for Measuring Drug-Target Engagement in Living Cells[END_REF] (Fig. 1A).

To support decision making and compound selection in drug discovery, it is critical that the tools allows to test numerous compounds and thus the throughput of CETSA needs to be increased. In this context, CETSA has been successfully coupled with AlphaLISA® detection to screen androgen receptors ligands and to determine the agonist or antagonist binding mode of compounds. [START_REF] Shaw | Determining Direct Binders of the Androgen Receptor Using a High-Throughput Cellular Thermal Shift Assay[END_REF] Alternatively, enzyme fragment complementation (EFC), that are based on protein modification with a tag, allows detection of non-aggregated protein by addition of the enzyme acceptor (EA) fragment, in a high throughput manner. This technique has been applied for the discovery of SMYD3 inhibitors using β-galactosidase-derived fragment, or for the screening of CDK9 inhibitors using a fragment of NanoLuc (NLuc). [START_REF] Mcnulty | A High-Throughput Dose-Response Cellular Thermal Shift Assay for Rapid Screening of Drug Target Engagement in Living Cells, Exemplified Using SMYD3 and IDO1[END_REF][START_REF] Martinez | A Widely-Applicable High-Throughput Cellular Thermal Shift Assay (CETSA) Using Split Nano Luciferase[END_REF] These latest developments have greatly improved throughput but require nonetheless specific assay development.

Indeed, CETSA AlphaLISA® requires the availability and optimization of a pair of antibodies. As well, CETSA EFC requires the production of the tagged-target and the checking of the absence of alteration of TAgg of fused protein-tag compared to untagged protein. Also, it is based on the production of a tagged protein within cell which expression can dramatically differ from that of the native protein.

As a result, Western blot (WB) is still the most used readout to quantify folded protein target in CETSA protocols. However, this method leads to a large amount of data points to analyse, requires substantial cell amounts and is labour intensive when many compounds or parameters have to be tested. In this context, we propose to couple Reverse Phase Protein Array (RPPA) technology to CETSA (Fig. 1B). RPPA can be fully adapted to measure protein target signal at high throughput with minimal sample consumption. Thanks to the use of highly specific primary antibodies and automation allowing printing of replicates, the technique is both robust and quantitative. Also, we use the most recent developments in the field of the Acoustic Droplet Ejection Technology [START_REF] Colin | High-Throughput DNA Plasmid Transfection Using Acoustic Droplet Ejection Technology[END_REF] for microarraying. To validate this method, we explored target engagement of inhibitors of Insulin Degrading Enzyme (IDE). CETSA-aRPPA successfully provided insights into compound profiles and IDE target engagement in hepatocytes.

Material and Methods

Cell culture and compound treatments

HepG2 cells provided by Dr. Nathalie Hennuyer (Institut Pasteur de Lille, France) were cultured in gelatin (Sigma-Aldrich, G-1890, 1 mg/mL) pre-coated T75 flasks in MEM Alpha Medium (1X) + GlutaMax (Gibco, 32561-029) containing 10% heat-inactivated fetal calf serum (Life Technologies, 10270-106) and 5 µg/mL penicillin/streptomycin (Life Technologies, 15070-063), in 37 °C humidified incubator with 5% CO2 atmosphere. After the cells had grown to confluence, vehicle or compounds (1-2 inhouse compounds, 3 (6bK)) were added to 30 µM final concentration (0.3% final DMSO).

CETSA

Suspended HepG2 cells were washed in PBS and detached using trypsin/EDTA solution (Life Technologies, 25300054). Cells were transferred in medium in 15 mL falcon and centrifuged at 300 g during 4 min. Supernatant was then discarded and cells were washed in PBS (Gibco, DPBS (1X), 14190-094), counted and centrifuged at 300g during 4 min. After removing PBS, cells were suspended in Tris Buffered Saline 1X (TBS 10X, Euromedex, ET220-B) at the 10 million per mL and aliquoted in 10 PCR 0.2 mL microtubes (Thermo Scientific, AB-0622) for each condition with 50 µL. Tubes were then transiently heated to a range of temperature from 40 °C to 67 °C for 3 min using a SureCycler 8800 Thermal Cycler (Agilent Technologies), cooled at room temperature for 3 minutes and followed by three freeze/thaw cycles in liquid nitrogen.

Insoluble proteins were separated by centrifugation (20000 g, 20 min, 4 °C) and 35 µL of supernatant corresponding to soluble proteins were kept for Western blot or Reverse Phase Protein Array analysis. Three independent experiments were performed for each compound. For ITDRFCETSA-aRPPA see Supplementary Methods.

SDS PAGE Electrophoresis with CETSA samples

Each total protein sample (7 µL) were prepared and heated at 70 °C for 10 min with NuPAGE™ Sample Reducing Agent (10X) (Thermoficher Scientific, NP0004) and NuPAGE™ LDS Sample Buffer (4X) (Thermofisher Scientific, NP0007), loaded in NuPage 3-8% Polyacrylamide gel for migration (150V, 1 hour) and then transferred on nitrocellulose membrane (Amersham Protran supported 0.2 µm NC, 10600080) with iBlot™ 2 Gel Transfer Device (Thermofisher Scientific, IB21001).

Immobilization of CETSA samples and purified IDE on nitrocellulose by nanoacoustic transfer

Labcyte 384 LDV microplate (LP-0200) was loaded with CETSA protein samples and TBS BSA 1% solution with 50 and 100 ng/mL of IDE as controls, left at RT for 2 hours to perform the protein saturation of microplate plastic (Cyclic olefin copolymere) and centrifuged without seal at 1500 g for 2 min with medium deceleration velocity. Using acoustic liquid handling device (Labcyte, Echo 550) and Echo array Maker software, 20 nL lysate or protein sample was transferred on nitrocellulose membrane (Amersham Protran supported 0.2 µm NC, 10600080) fixed on a glass slide maintained on a slide holder (Tecan, 30065759). After 2 hours at RT, membranes were store at 4 °C until final disposal.

Immunoblotting for WB and RPPA

Blots and printed membranes were blocked in dry milk (5%) diluted in PBS for 1 hour at RT and washed 3 times of 10 min in PBS 0,1% Tween 20. Mouse monoclonal anti-IDE antibody (Santa Cruz Biotechnology, clone F-9, sc-393887) were used as primary antibody diluted at 1:1000 for WB or 1:2500 for RPPA in 2% BSA PBS 0,1% Tween20 solution and incubated respectively 1h30 for WB and 30 min for RPPA at RT. After 3 washes in 0.1% PBS Tween 20, Anti-Mouse IRDye 800 CW (Licor IRDye 800CW Goat anti-Mouse IgG, P/N 925-32210) was used as secondary antibody in 2% BSA PBS 0,1% Tween 20 solution at 1:20000 for 1h30 at RT and blots were washed 3 times in PBS Tween 0,1% before fluorescence intensities detection by Odyssey CLx Imaging System.

Data analysis and aggregation curve

The signal intensities (corresponding to sample fluorescence minus background fluorescence) of each protein band or spot on the Western blots or Reverse Phase Protein Arrays were quantified using Image Studio™ Lite Analysis Software (Licor).

Fold-changes were calculated in percentage of the lowest temperature. The relative signals were plotted against temperature using Graphpad (Prism) and a variable slope sigmoidal curve was fitted using the chemical denaturation theory equation.

  plateau e plateau T f b T a                 1 1 ) (
Initial values for top and bottom plateau were set at 100% and 0% respectively for curve fitting. Aggregation curves were expressed independently for each experiment or as means of multiple experiments (n = 3) +/-SEM. Thermal shifts were calculated using ΔTAgg50, as the difference in aggregation temperatures between the control and treatment, at which 50% signal intensity (protein denaturation) was observed.

Determination of IDE inhibition by compounds

Recombinant human IDE (IDE) was provided by Pr W.J. Tang (University of Chicago).

The enzymatic activity of IDE was assayed quantifying the amount of insulin (Actrapid®, Novo Nordisk) at the end of the incubation period.

D C x A B A y             10 1
A, minimum y value; B, maximum y value; C, LogIC50 value; D, slope factor.

Results and Discussion

Insulin-Degrading Enzyme (IDE) is a ubiquitous protease involved in the degradation of many peptides, like insulin, that share a propensity to be amyloidogenic.

IDE has an atypical structure that is able to undergo a large conformational shift from full closed to fully open states. CryoEM studies on IDE revealed recently how amyloidogenic peptides are captured and hydrolyzed by IDE. [START_REF] Zhang | Ensemble cryoEM elucidates the mechanism of insulin capture and degradation by human insulin degrading enzyme[END_REF] In the recent years, several exosite-binding inhibitors BDM43124 [START_REF] Charton | Imidazole-derived 2-[Ncarbamoylmethyl-alkylamino]acetic acids, substrate-dependent modulators of insulindegrading enzyme in amyloid-β hydrolysis[END_REF][START_REF] Charton | Structure-activity relationships of Imidazole-derived 2-[N-carbamoylmethyl-alkylamino]acetic acids, dual binders of human Insulin-Degrading Enzyme[END_REF] or 3 (6bK) a macrocyclic peptide, [START_REF] Maianti | activity of insulindegrading enzyme inhibitors mediated by multiple hormones[END_REF] or drug-like catalytic-binding 1 (BDM44768) discovered by in situ click chemistry strategy [START_REF] Deprez-Poulain | Catalytic site inhibition of insulin-degrading enzyme by a small molecule induces glucose intolerance in mice[END_REF] were disclosed. Surprisingly, 1 (BDM44768) and 3 (6bK) display different effects on glucose tolerance in vivo, suggesting the complex role of IDE in this phenotype. As well, Villa-Perez et al recently revisited, using liver-specific IDE ko mice, the role of IDE in hepatic insulin resistance. [START_REF] Villa-Perez | Liver-specific ablation of insulin-degrading enzyme causes hepatic insulin resistance and glucose intolerance, without affecting insulin clearance in mice[END_REF] Wishing to contribute to the understanding of the role of IDE in hepatocytes, we wanted to select the best chemical tool among published inhibitors. We thus turned ourselves to CETSA technique to select a compound that actually engages IDE in hepatocytes.

Design and validation of CETSA-aRPPA

In the described assay, we propose to analyze the soluble protein fraction obtained from CETSA experiments by RPPA approaches consisting in immobilization of samples on a nitrocellulose support and subsequent detection by immunoblotting with an antibody directed against the protein of interest. HepG2 cells have been treated during 2 hours with compounds 1-3 (30 µM) or DMSO. Cells were then heated at 10 different temperatures between 40 °C and 67 °C. Soluble protein lysates corresponding to each condition of treatment were printed on nitrocellulose membrane using acoustic nanodispensing (see below). RPPA pattern used purified IDE recombinant protein (50 ng/mL and 100 ng/mL) as positive control and buffer alone for negative control. Three independent biological replicates have been carried out using an RPPA pattern (Suppl. Fig. S1). A first series of experiments allowed us to measure the linearity of IDE detection using acoustic transfer and RPPA. Then of our CETSA-aRPPA tool versus WB comparing the aggregation curves and the determined aggregation temperature corresponding to 1-3 compounds. Furthermore, these CETSA protein extracts samples have been used to evaluate the precision of CETSA-aRPPA for three independent microarray patterns as well as permeability of compounds.

Linearity of IDE detection using acoustic transfer and RPPA technologies

Immobilization of protein samples or purified IDE on the array was set up using Echo acoustic liquid handling technology. [START_REF] Wong | Advancing Microarray Assembly with Acoustic Dispensing Technology[END_REF] Lysates were transferred by using sound energy achieved by transducer from source well of 384 low-dead-volume microplate to nitrocellulose membrane, and which provide contact-less fluid dispensing. This destination support is fixed on a glass slide, held in a specific handler which is inverted in order to place the membrane above the source well (Suppl.

Accuracy and precision of RPPA versus WB

In order to avoid the detection of unrelated proteins in RPPA approach, the high specificity of antibody directed against IDE (110 kDa) has been checked in WB on HepG2 protein extracts. The second strongest band (90 kDa) was found to have an intensity below 5% of the specific signal at 110 kDa, qualifying the antibody RPPA quantification. (Suppl. Fig. S4). Quantified signals obtained from CETSA experiments (in WB and CETSA-aRPPA) were normalized for each condition of treatment with the signal at the lowest temperature (40 °C) corresponding to 100% of non-aggregated protein. Using the chemical denaturation theory formula, the data were fitted to obtain an aggregation curve of IDE in presence or in absence of inhibitors. To evaluate the accuracy of the CETSA-aRPPA versus Western Blot, three biological experiments for each method underwent the same analysis process (Fig. 2A and 2B respectively,

Suppl. Fig S5-6). Fitted aggregation curves on the three series allowed to determine

TAgg values corresponding of the temperature at 50% of aggregated IDE and ΔTAgg for each condition. For DMSO and the tested inhibitors 1-3, both methods gave consistent results (Fig. 2A and 2B and Suppl. Table S1). Indeed, the TAgg determined by WB or CETSA-aRPPA for each condition of treatment have been compared with one way ANOVA statistic test (Fig. 2C). No significant difference between methods could be established for DMSO or inhibitors 1-3 and this resulted in a good correlation (r 2 = 0.9951 Fig. 2D). Spotting precision of CETSA-aRPPA has been studied by comparing T Agg calculated in three assay replications (P1: Pattern1, P2: Pattern2, P3: Pattern3) as the mean of three TAgg corresponding to each experiment. Images of these three patterns have been analyzed and signals corresponding to IDE have been quantified in order to fit aggregation curves and calculate TAgg (see Fig. 2E and Suppl. Fig. S4).

No significant difference between TAgg obtained into each condition of treatment has been observed when we compared the three patterns.

Cellular target engagement of IDE by inhibitors

The three compounds (Fig. 3A) with inhibitory activities on IDE (enzymatic assay) in the same range (6.5 < pIC50 < 6.9, Fig. 3B) were selected to study target engagement of IDE in hepatocytes. Compounds 1 (BDM44768) and 2 derive from a series of triazoles targeting the catalytic site of IDE and were discovered by in situ click chemistry, (Fig. 3A-B). [START_REF] Deprez-Poulain | Catalytic site inhibition of insulin-degrading enzyme by a small molecule induces glucose intolerance in mice[END_REF] Inhibitor 3 (6bK) is a macrocycle discovered by DNAtemplated library, and targets an exosite (Fig. 3A-B). [START_REF] Maianti | activity of insulindegrading enzyme inhibitors mediated by multiple hormones[END_REF] Aggregation profile of IDE in the presence of inhibitors 1-2 showed a significant shift (Fig. 2B and3C). Interestingly bis-fluorinated analog 2 stabilizes IDE better than 1 (ΔTAgg = 5.63 °C vs 3.06 °C respectively). On the contrary, treatment of cells with 3 did not achieve significant stabilization of IDE versus control (ΔTAgg = -0.36 °C).

Using the same CETSA-aRPPA technique we measured the dose-dependent IDE stabilization (ITDRF: isothermal dose-response fingerprint) by compound 1 (Fig. 4A, Suppl. Fig. S7, Suppl. methods) and 2 (Fig. 4B). To rationalize CETSA-aRPPA and ITDRFCETSA-aRPPA results, we measured the ability of inhibitors 1-3 to cross the membrane of HepG2 cells (Fig. 4C Suppl. Table S2 and Suppl. methods).

Compounds were titrated by LC-MS/MS in cell culture medium and in HepG2 cells using samples from the CETSA experiments. Permeability was expressed as the ratio of concentrations of inhibitors in cells versus in the extracellular medium at the end of the diffusion period (2 hours). While inhibitors 1 and 2 penetrate HepG2 cells, inhibitor 3 was not detected in HepG2. So, the poor result of 3 in CETSA can be attributed to its poor permeability. Interestingly, while inhibitors 1 and 2 display similar inhibitory potencies on IDE (IC50), 2 engages IDE in cells 10 times more efficiently than 1 (EC50 of 2.75 µM vs 25.5 µM respectively) (Fig. 4D). Like 1, compound 2 chelates zinc ion with its hydroxamic acid, makes a cation-π interaction with Arg824 via the triazole ring and a hydrogen bond with Ser138 via the carbonyl of the amide bond (Fig. 4E). The introduction of the second fluorine in compound 2 enhances IDE inhibition by allowing phenyl ring to better engage π-stacking with Phe820, and by engaging naphthyle in an interaction with the backbone of Val833 (Fig. 4E, Suppl. Fig. S8, Suppl. methods).

Introduction of the fluorine increases interactions with the target, decreases the aqueous solubility and desolvatation energy and enhances LogD by 0.4 (Fig. 4D, Suppl. methods). This explains the high potency and better permeability of this compound, translating into a higher ΔTAgg.

Interestingly, potency shift between acellular inhibitory assay (IC50) and cellular engagement assay (EC50) is 3 times lower for compound 2 (21) than for compound 1 (77). As the relative permeability of compounds 1 and 2 differs also by a factor of 3, the potency shift varies mainly in function of the relative permeability of the two compounds.

ITDRF is more relevant to measure target engagement in cells than measuring the global intracellular concentrations of compounds because these could have an uneven cellular distribution. For our chemical series however the potency shift seems to be correlated to the ability to penetrate HepG2 cells.

Compound 2 is thus the best candidate to explore the role(s) of IDE in hepatocytes, while in vivo effects of 3 (6bK) may be only attributed to inhibition of extracellular IDE, a small fraction of IDE in the body.

Target engagement in whole cells or tissues has become a fundamental step in drug discovery projects in order to select drugs candidates before preclinical studies or to confirm functional effects of chemical compounds. In this context, CETSA is a tool of choice to study target engagement. This approach considers addressing, permeability and general protein-binding aspects and permits direct measurement of ligand binding to target protein. Nevertheless, despite an easy implementation for the most laboratories, application to large chemical series or libraries remains challenging.

Based on new features of nanoacoustic transfer device, we developed CETSA-aRPPA

  19.6 µL of wt IDE in Hepes buffer (50 mM with 100 mM NaCl, pH 7.4) at 300 ng/mL were pre-incubated 15 minutes at room temperature with 400 nL of test compound or vehicle (DMSO) transferred with Echo 550 in 96 well half-area microplate (Corning, 3686). The reaction was then started by the addition of 20 µL of insulin at 40 nM. The final concentration of IDE and substrate was 0.25 µg/mL and 20 nM, respectively. Incubations were performed at ambient temperature for 10 minutes. The reaction was then stopped by addition of 40 µL of 200 mM EDTA. The samples were diluted by 10 in AlphaLISA® diluant. 2 µL of samples or standard were incubated with 8 µl of a 2.5X mix of AlphaLISA® Anti-insulin Acceptor beads, biotinylated antibody Anti-insulin and AlphaLISA® immunoassay Buffer in 384 well Proxiplate (Perkin Elmer, AL204C). The microplate was sealed and left on the bench for 60 min at room temperature. 10 µl of a mix SA-Donor beads and AlphaLISA® immunoassay Buffer were added and the plate was read with Mithras LB 940 reader (Berthold) with Alphascreen® protocol at 620 nm after 30 min of incubation. IC50 values were calculated using XLfit 5 software from concentration-response curves fitted by a nonlinear regression analysis to the 4 parameter logistic equation:

  Fig. S2). Spots of protein samples correspond to 20 nL transfer (8 droplets of 2.5 nL). To validate the correlation between IDE signal detected by fluorescence and concentration of this protein target, we have printed 20 nL of IDE protein from 50 µg/mL to 2.5 ng/mL. Pictures acquired after immunoblotting development corresponding to 3 drop-off of IDE range (10 concentrations) are shown in Suppl. Fig. S3. A very good linear correlation (r 2 = 0.9695) between IDE concentration and fluorescence signal was measured.

Figures LegendsFigure 1 .

 1 Figures Legends

Figure 2 .Figure 3 .

 23 Figure 2. Validation of CETSA-aRPPA assay to screen for intracellular target

Figure 4 .

 4 Figure 4. Dose-dependent stabilization (ITDRFCETSA-aRPPA) of IDE in HepG2 cells by

Acknowledgments

The authors would like to thank Dr. Nathalie Hennuyer for the kind gift of HepG2 cell line and Pr Wei-Jen Tang for human recombinant IDE.

Funding

The authors acknowledge financial support from INSERM, University of Lille, Institut Pasteur de Lille, Region Nord Pas de Calais, FEDER, State (0823007, 0823008, 07-CPER 009-01, 2007-0172-02-CPER/3), the European Union under the European Regional Fund (ERDF), by the Hauts-de-France Regional Council (contract N°17003781), the MEL (contract N°2016_ESR_05), and the French State (contract N°2017-R3-CTRL-Phase 1) and Institut Universitaire de France.

ORCID iD

technology with the objective to propose a new valuable tool to explore target engagement with a higher-throughput than conventional and actual analysis techniques and a lower consumption of samples. The method displays a high precision and accuracy compared to Western Blot. It was used to study target engagement of IDE by inhibitors in whole HepG2 cells context. aRPPA detection can also be used to measure ITDRF dose-dependent stabilization of target of interest (ITDRFCETSA-aRPPA) with the same advantages. In the future CETSA-aRPPA will allow further applications including screening or multitarget engagement studies.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplementary Information is available online with this article