Maxime Liberelle

Florine Toulotte

Nicolas Renault

Muriel Gelin

Frédéric Allemand

ALLEMAND ‡ Patricia Melnyk

Jean-François Guichou

Philippe Cotelle

Maxime Liberelle §&

Florine Toulotte §&

Nicolas Renault #

Toward the Design of Ligands Selective for the C-Terminal Domain of TEADs

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

I.

Introduction

A.

Hippo pathway

The evolutional conserved Hippo pathway, firstly discovered in Drosophila in 1995, [START_REF] Justice | The Drosophila Tumor Suppressor Gene Warts Encodes a Homolog of Human Myotonic Dystrophy Kinase and Is Required for the Control of Cell Shape and Proliferation[END_REF] controls organ size and cell differentiation through the regulation of cell proliferation and apoptosis. Growing interest in the Hippo pathway has been firstly

driven by its deregulation in many diverse cancers (as reported in many reviews), [START_REF] Moroishi | The Emerging Roles of YAP and TAZ in Cancer[END_REF][START_REF] Zanconato | YAP/TAZ at the Roots of Cancer[END_REF] then found interest in regenerative medicine [START_REF] Johnson | The Two Faces of Hippo: Targeting the Hippo Pathway for Regenerative Medicine and Cancer Treatment[END_REF][START_REF] Moya | Hippo-YAP/TAZ Signalling in Organ Regeneration and Regenerative Medicine[END_REF][START_REF] Dey | Targeting the Hippo Pathway in Cancer, Fibrosis, Wound Healing and Regenerative Medicine[END_REF] to finally emerged in the field of neurodegenerative diseases. [START_REF] Sahu | The Emerging Role of Hippo Signaling in Neurodegeneration[END_REF][START_REF] Jin | The Effects of YAP and Its Related Mechanisms in Central Nervous System Diseases[END_REF] The Hippo pathway is mainly composed of a series of kinases which after stimulation by upstream signals causes the YAP (Yes-Associated Protein) /TAZ (transcriptional co-activator with PDZ-binding motif, also known as WWTR1 (WW domain-containing transcription regulator protein 1) phosphorylation to remain in the cytoplasm, eventually leading to its capture and degradation. When the Hippo pathway is inactivated, unphosphorylated YAP/TAZ enters the nucleus and promote downstream genes expression through the formation of transcriptional complexes with other transcription factors such as RUNX1/2, TBX5, [START_REF] Piccolo | The Biology of YAP/TAZ: Hippo Signaling and Beyond[END_REF] and specially TEAD1-4 transcription factors which are considered as the most important output of the Hippo pathway.

B.

Physiological pan-TEAD pathway TEAD family has Hippo-dependent coactivators (YAP and TAZ) but also Hippoindependent coactivators (VGLL1-4) and newly discovered interactors (FAM181 proteins).

YAP and TAZ (transcriptional co-activator with PDZ-binding motif, also known as WWTR1) bind to TEAD1-4 to drive expression of target genes such as CTGF, Cyr61 or Axl (cell proliferation), Survivin (Birc-5) (inhibition of apoptosis), Sox2, Nanog and Oct4 (stemness, pluripotency). Besides YAP/TAZ, the most studied coactivators of TEAD1-4 transcriptional activity, the Vestigial-like (VGLL) protein family, which consists in four members (VGLL1-4), has been shown to interact with TEAD to regulate gene expression [START_REF] Yamaguchi | Multiple Roles of Vestigial-Like Family Members in Tumor Development[END_REF] .

Although VGLL1-4 bind to the YAP-TAZ binding domain of TEAD1-4, VGLL1-3 and VGLL4 have distinct molecular functions and only VGLL4 has been reported to inhibit YAP/TAZ-TEAD interactions.

A third family of TEAD interactor has been recently identified. FAM181 genes constitute a novel gene family [START_REF] Dequéant | A Complex Oscillating Network of Signaling Genes Underlies the Mouse Segmentation Clock[END_REF] that is conserved among vertebrates with two paralogs, namely FAM181A and FAM81B, per species. Both genes display highly dynamic and specific expression patterns (most prominently in neural tissues) during murine embryonic development [START_REF] Marks | Analysis of the Fam181 Gene Family during Mouse Development Reveals Distinct Strain-Specific Expression Patterns, Suggesting a Role in Nervous System Development and Function[END_REF] . These last proteins also interact with TEAD in the same C-terminal domain than YAP, TAZ and VGLLs.

Mammals express four TEAD genes located on four different chromosomes.

TEADs are broadly expressed in almost all tissues with a specific pattern that indicates tissue-specific roles for each TEAD members. TEADs play important roles in development (cardiogenesis (TEAD1), neural crest (TEAD2) and notochord (TEAD1/2) development, cell lineage fate determination [START_REF] Heng | Role of YAP/TAZ in Cell Lineage Fate Determination and Related Signaling Pathways[END_REF] ) but each TEAD has tissue specific expression (TEAD1: schwann cell development, smooth muscle cell proliferation and differentiation, angiogenesis stimulation in endothelial cells; TEAD2: mouse embryonic stem cell self-renewal; TEAD4: myogenic differentiation). Recently, TEAD1 and TEAD3 were found to regulate human epidermal proliferation [START_REF] Li | TEAD1 and TEAD3 Play Redundant Roles in the Regulation of Human Epidermal Proliferation[END_REF] while TEAD3 mediates cardiac lineage formation from human-induced pluripotent stem cells. [START_REF] Han | YAP/TEAD3 Signal Mediates Cardiac Lineage Commitment of Human-Induced Pluripotent Stem Cells[END_REF] C.

Pathologies with specific TEAD dysregulation

Dysregulation of the Hippo pathway may occur in many diseases, including cancers, neurodegenerative diseases and rare diseases. Almost all the upstream regulators may be dysregulated. Here, we specifically focus on dysregulation of TEADs.

A specific mutation of TEAD1 (Y421H) is associated with Sveinsson's chorioretinal atrophy, a rare genetic disorder that results in degeneration of the choroid and retina. [START_REF] Fossdal | A Novel TEAD1 Mutation Is the Causative Allele in Sveinsson's Chorioretinal Atrophy (Helicoid Peripapillary Chorioretinal Degeneration)[END_REF] TEAD1 and YAP regulate ballooning cell death in Htt17Q expressing primary mice neurons (a Huntington disease cellular model). [START_REF] Mao | Targeting TEAD/YAP-Transcription-Dependent Necrosis, TRIAD, Ameliorates Huntington's Disease Pathology[END_REF] YAP and TEAD1 are specifically expressed in Müller cells and are upregulated following retinal degeneration. [START_REF] Hamon | Retinal Degeneration Triggers the Activation of YAP/TEAD in Reactive Müller Cells[END_REF] In cancers, TEAD1 is mainly implicated in prostate, cervical and breast cancers. [START_REF] Malt | Alteration of TEAD1 Expression Levels Confers Apoptotic Resistance through the Transcriptional Up-Regulation of Livin[END_REF][START_REF] Knight | TEAD1 and C-Cbl Are Novel Prostate Basal Cell Markers That Correlate with Poor Clinical Outcome in Prostate Cancer[END_REF] TEAD2 has been reported to be a novel prognostic factor for hepatocellular carcinoma [START_REF] Joo | TEAD2 as a Novel Prognostic Factor for Hepatocellular Carcinoma[END_REF] and its expression is increased during epithelialmesenchymal transition in mammary gland epithelial cells and breast cancer cells, [START_REF] Diepenbruck | Tead2 Expression Levels Control the Subcellular Distribution of Yap and Taz, Zyxin Expression and Epithelial-Mesenchymal Transition[END_REF] and emerged as an independent prognostic factor in pancreatic ductal adenocarcinoma. [START_REF] Drexler | Association of Subcellular Localization of TEAD Transcription Factors with Outcome and Progression in Pancreatic Ductal Adenocarcinoma[END_REF] In glioblastoma, neurofibromatosis 2 controls the invasiveness through YAP-TEAD2-dependent expression of Cyr61. [START_REF] Lee | Neurofibromatosis 2 (NF2) controls the invasiveness of glioblastoma through YAP-dependent expression of CYR61/CCN1 and miR-296-3p[END_REF] TEAD4 expression significantly increases in colorectal cancer [START_REF] Liu | Increased TEAD4 Expression and Nuclear Localization in Colorectal Cancer Promote Epithelial-Mesenchymal Transition and Metastasis in a YAP-Independent Manner[END_REF] and in hepatoblastoma [START_REF] Zhang | Vestigial like Family Member 3 Is a Novel Prognostic Biomarker for Gastric Cancer[END_REF] and elevated levels of a splicing isoform of TEAD4 associated with an increased rate of survival was also reported in cancer patients. [START_REF] Qi | A Splicing Isoform of TEAD4 Attenuates the Hippo-YAP Signalling to Inhibit Tumour Proliferation[END_REF] Amongst the different strategies to combat YAP and TAZ in cancers that have been recently reviewed, [START_REF] Pobbati | A Combat with the YAP/TAZ-TEAD Oncoproteins for Cancer Therapy[END_REF] targeting YAP/TAZ-TEAD complexes (group II compounds) by TEAD ligands have yielded to published or patented pan-TEAD inhibitors [START_REF] Pobbati | Protein-Protein Interaction Disruptors of the YAP/TAZ-TEAD Transcriptional Complex[END_REF] but subtle structural differences in the TEAD internal pocket have already been suggested to give selective TEAD inhibitors. [START_REF] Holden | Targeting the Hippo Pathway and Cancer through the TEAD Family of Transcription Factors[END_REF] Creating selective TEAD ligands would find interest in diseases were one TEAD is overexpressed but also in deciphering the exact role of each TEAD member in healthy or disease cellular models.

Here, starting from the newly available structures of hTEADx from AlphaFold2, we reanalyzed the highly conserved but non-identical C-terminal domains of the four members of TEAD family. Two main strategies of TEAD targeting are:

disrupting the protein-protein interaction with their activators or modulating the acylation of their internal pocket. Facing the growing evidences of major divergence of function between the TEAD family members, we focused on the differences that may give raise to selectivity: (i) the known internal pocket and the acylation, (ii) the protein-protein interface with the yet-unexplored flexible loop of hTEAD2 (loop A) and the non-conserved loop that is close to both ends of the Cterminal domain (loop B). We described here a ligand of this new specific TEAD2 loop A which will pave the way to the discovery of selective ligand of hTEAD2.

Ligands displaying selectivity over some of the TEAD family members have already been described, albeit in small number and solely toward the internal pocket such as VT103 (16), the first selective inhibitor of hTEAD1 autopalmitoylation patented by Vivace Therapeutics [START_REF] Aal | Non-Fused Tricyclic Compounds[END_REF][START_REF] Lin | Preparation of Substituted Naphthalene-2-Carboxamide Derivatives Useful for Treatment of Cancer By Konradi[END_REF][START_REF] Tang | Small Molecule Inhibitors of TEAD Auto-Palmitoylation Selectively Inhibit Proliferation and Tumor Growth of NF2-Deficient Mesothelioma[END_REF] and DC-TEAD3in03 (17), a selective inhibitor of hTEAD3 [START_REF] Lu | Discovery of a Subtype-Selective, Covalent Inhibitor against Palmitoylation Pocket of TEAD3[END_REF] . We thus performed a docking study to explore the structural determinants that could underlie such specificity, using Alphafold2 and in-house model developed to take account of the plasticity of the internal pocket where the internal cavity is enlarged by a non-fatty acid ligand.

Our conclusion led us to note some discrepancies regarding the paradigm of TEAD activation by its protein partners and once again, using the Alphafold2 structures and some recent results, we were able to formulate a new hypothesis that allow further development of TEAD modulators. 1) of YAP-TEAD complexes were reported in 2010 by several groups [START_REF] Li | Structural Insights into the YAP and TEAD Complex[END_REF][START_REF] Chen | Structural Basis of YAP Recognition by TEAD4 in the Hippo Pathway[END_REF][START_REF] Tian | Structural and Functional Analysis of the YAP-Binding Domain of Human TEAD2[END_REF] while mTAZ-mTEAD crystallographic structure was reported in 2017. [START_REF] Kaan | Crystal Structure of TAZ-TEAD Complex Reveals a Distinct Interaction Mode from That of YAP-TEAD Complex[END_REF] Two structures have been reported for mVGLL-mTEAD4 interactions [START_REF] Pobbati | Structural and Functional Similarity between the Vgll1-TEAD and the YAP-TEAD Complexes[END_REF][START_REF] Jiao | A Peptide Mimicking VGLL4 Function Acts as a YAP Antagonist Therapy against Gastric Cancer[END_REF] and very recently a short peptide mimicking mVGLL4 was designed and crystallized with mTEAD4 C-terminal domain. [START_REF] Adihou | A Protein Tertiary Structure Mimetic Modulator of the Hippo Signalling Pathway[END_REF] Finally, FAM181A and B peptides were crystallized with hTEAD4. [START_REF] Bokhovchuk | Identification of FAM181A and FAM181B as New Interactors with the TEAD Transcription Factors[END_REF] All these fragments of proteins (YAP, TAZ, VGLL and FAM) binds to TEAD Cterminal domain at its external surface (interfaces 1, 2 and 3) (Figure 1 and Table 2).

II. TEAD structures & functions

(UCSF). 80

The interaction of these proteins with TEAD involves the three same interfaces, with YAP, TAZ and VGLL2 binding to the three, VGLL1&3 binding to the interface 1 and 2 and the FAM181 only to the third. VGLL4 is a bit divergent, with a binding to a first TEAD monomer in the interface 1 and 2 and with a second TEAD monomer in the interface 2. All but VGLL4 are activators of TEAD, even if the involvement of FAM181 remains unclear, their main difference coming from their cellular context of effect: It appears VGLL members act mostly when the Hippo pathway is on while YAP/TAZ interact with TEAD when the Hippo pathway is off.

B. TEAD internal pocket

In 2016, the presence of palmitate in an internal pocket of hTEAD2 or hTEAD3 was reported for the first time, which seems to increase the stability of the TEAD protein. [START_REF] Noland | Palmitoylation of TEAD Transcription Factors Is Required for Their Stability and Function in Hippo Pathway Signaling[END_REF][START_REF] Chan | Autopalmitoylation of TEAD Proteins Regulates Transcriptional Output of the Hippo Pathway[END_REF][START_REF] Li | Structural and Ligand-Binding Analysis of the YAP-Binding Domain of Transcription Factor TEAD4[END_REF][START_REF] Mesrouze | Adaptation of the Bound Intrinsically Disordered Protein YAP to Mutations at the YAP:TEAD Interface[END_REF][START_REF] Bokhovchuk | Molecular and Structural Characterization of a TEAD Mutation at the Origin of Sveinsson's Chorioretinal Atrophy[END_REF] This internal pocket can also welcome a myristate and those fatty acids were found free or bonded to conserved cysteine (C380 in hTEAD2) (thioester function) or lysine residues (K357 in hTEAD2) (amide function) (Figure 2). [START_REF] Mesrouze | Effect of the Acylation of TEAD4 on Its Interaction with Co-Activators YAP and TAZ[END_REF] Since direct N-acylation of a lysine residue with palmitoyl-CoA is relatively slow, a cysteine-to-lysine transfer [START_REF] James | Nucleotide-binding sites can enhance N-acylation of nearby protein lysine residues[END_REF][START_REF] James | Proximal Cysteines that Enhance Lysine N-Acetylation of Cytosolic Proteins in Mice Are Less Conserved in Longer-Living Species[END_REF] is expected to probably occur in the pocket due to the proximity of both residues, explaining the observations made by Noland et al. [START_REF] Noland | Palmitoylation of TEAD Transcription Factors Is Required for Their Stability and Function in Hippo Pathway Signaling[END_REF] on the irreversibility of TEAD palmitoylation which was considered rather uncharacteristic.

Figure 2. View of the entry of the internal pocket where the fatty acid is free (top) or bonded to conserved cysteine (left) or lysine (right)

The internal pocket can be divided into 2 sub-pockets: 6 a highly conserved hydrophobic sub-pocket (Figure 3 and table 3, in blue) located at the bottom which accommodates the carbon skeleton of the fatty acid which therefore interacts with these amino acids through Van der Waals interactions and a hydrophilic subpocket (Figure 3 and table 3, in purple) which is close to the entrance and surrounds the acid moiety of the fatty acid. This carboxylic function interacts by hydrogen bonds, through covalent bond with conserved cysteine (in grey) and lysine residues or ionic bond with lysine residue.

Figure 3. Hydrophobic and hydrophilic sub-pockets of the internal pocket of hTEAD2; grey circles correspond to residues that make covalent bond with fatty acid; blue circles correspond to hydrophobic residues; magenta circles correspond to hydrophilic residues; purple circle corresponds to non-conserved residues

Whereas the hydrophobic sub-pocket is highly conserved, the hydrophilic subpocket displays significant differences (see Figure 3 and Table 3): at the bottom we found C405 for hTEAD1, Y426 and Y413 for hTEAD2 and hTEAD4 and F414 for hTEAD3; at the entry of the hydrophobic pocket we found Y233 for hTEAD3 and a phenylalanine residue for the other hTEADs (F221, F233 and F229 for hTEAD1, hTEAD2 and hTEAD4 respectively); finally, close to C405, hTEAD1 has L389 which is a glutamine residue (Q410, Q398 and Q397 for hTEAD1, hTEAD2 and hTEAD4) in the others TEADs. The number of cysteine residues that point toward this pocket is also different for each in hTEAD1. C296, C322, C359 and C405 are located quite far from each other, whereas only two cysteine residues where found for hTEAD2 and hTEAD4 (C343 and C380 for TEAD2 and C330 and C367 for TEAD4) and only one cysteine is present in hTEAD3 (C368). At the extremity of the hydrophobic sub-pocket lies a totally non-conserved residue which is small and hydrophilic (C296 for hTEAD1, S305 for hTEAD3 and T304 for hTEAD4) and large and hydrophobic (W308 for hTEAD2).

III. TEAD targeting

Since 2015, several structures of TEAD with small molecules have been reported

and are available at the Protein Data Bank (Table 1 and Figure 4). Either, compounds bind to TEAD at the internal pocket ( A.

Targeting TEAD palmitoylation

The most druggable site of TEAD is the internal pocket which hosts myristate or palmitate. [START_REF] Gibault | Targeting Transcriptional Enhanced Associate Domains (TEADs)[END_REF] 1, entries 12-13 and Figure 4 , 5-6). [START_REF] Holden | Small Molecule Dysregulation of TEAD Lipidation Induces a Dominant-Negative Inhibition of Hippo Pathway Signaling[END_REF] Finally, several groups designed covalent TEAD inhibitors targeting the thiol function of the conserved cysteine residue at the entrance to the internal pocket, bearing chloroacetate groups or an acrylamide moiety (Table 1, entries 5 and 15 Figure 4, 1 and 8). [START_REF] Kaneda | The Novel Potent TEAD Inhibitor, K-975, Inhibits YAP1/TAZ-TEAD Protein-Protein Interactions and Exerts an Anti-Tumor Effect on Malignant Pleural Mesothelioma[END_REF]-61 1 (K-975) was compared to K-886 that is a derivative of K-975 with an acryl amide structure but whose structure is not disclosed in the article.

Figure 4. Structures of small molecules that form complexes with TEAD (compound 4 has been redrawed)

The authors reported that this derivative of K-975 bearing the same reactive function was found inactive without any explanation of this difference. The design of 8 (TED-347) is directly inspired by the structure of 2 (flufenamic acid) and clearly associates the affinity of 2 for the internal pocket and the reactivity of a chloroacetyl group which is known to be one of the highest reactivity in SN2 reactions. [START_REF] Chemistry -Clayden | Organic Chemistry[END_REF] Finally, Tang et al. [START_REF] Tang | Small Molecule Inhibitors of TEAD Auto-Palmitoylation Selectively Inhibit Proliferation and Tumor Growth of NF2-Deficient Mesothelioma[END_REF] reported the crystal structure of VT105 ( 14) with hTEAD3.

B. Targeting TEAD-activators protein-protein interaction

Targeting the protein-protein interaction between TEAD and YAP or TAZ has been the earliest strategy leading to the design of YAP-inspired peptides and cyclic peptides [START_REF] Zhou | Targeting Hippo Pathway by Specific Interruption of YAP-TEAD Interaction Using Cyclic YAP-like Peptides[END_REF][START_REF] Furet | Structure-Based Design of Potent Linear Peptide Inhibitors of the YAP-TEAD Protein-Protein Interaction Derived from the YAP Omega-Loop Sequence[END_REF] leading to inhibitors of YAP-TEAD interactions while VGLL4 mimicking led to opposite results: Jiao et al. [START_REF] Jiao | A Peptide Mimicking VGLL4 Function Acts as a YAP Antagonist Therapy against Gastric Cancer[END_REF] Few small external TEAD ligands were reported. Compound 15 was identified through a fragment based-approach. [START_REF] Kaan | Targeting YAP/TAZ-TEAD Protein-Protein Interactions Using Fragment-Based and Computational Modeling Approaches[END_REF] It binds to YAP-binding interface 2 of TEAD but its affinity for mTEAD4 is very low and it has practically no detectable cellular activity. We recently reported [START_REF] Sturbaut | Discovery of a Cryptic Site at the Interface 2 of TEAD -Towards a New Family of YAP/TAZ-TEAD Inhibitors[END_REF] the synthesis of a series of pyrazoles (Table 1, entries 16-20 Figure 4, 9-13) which also bound to TEAD2 at the interface 2 but at a new cryptic pocket created by the movement of Y382.

Although initially the most attractive target, no small molecule ligand of interface 3 has been reported to date.

IV. Toward specific TEAD targeting

A.

Through external binding pocket

In the large majority of the available crystal structures of C-terminal domain of which is not always well-defined in TEAD crystal structure is situated just under the interface 3. The number of residues is fully conserved whatever the TEAD member but not their nature. We anticipate that the basis of the loop A could be an ideal place for a ligand which could be selective for hTEAD2 vs hTEAD1,3,4. Indeed, the pocket present for hTEAD2 is occupied by residues of hTEAD1,3,4. These unsolved loops of Cterminal domain of TEADs are now modelized and available at the AlphaFold2 [START_REF] Jumper | Highly Accurate Protein Structure Prediction with AlphaFold[END_REF] web site (https://alphafold.ebi.ac.uk/)(Figure 5).

Concomitantly to this study, we screened a small home-made library of 500 fragments by thermal shift assay (TSA) on the C-terminal domain of hTEAD2 and the 44 fragments with a ΔTm > 0.7 °C were soaked with hTEAD2. Amongst the collected crystals, we discovered that one of the fragments (3-(1H-pyrazol-5yl)aniline named F-292)(ΔTm = 0.95 °C) crystallized in this hTEAD2-specific cavity (PDB code: 7OYJ, supplement table 1). TSA curves of hTEAD2 in the absence or in the presence of F-292 are given in supplementary (Supplement figures 1 and 2). Superimposing hTEAD2 (from AlphaFold2) with the crystallographic structure (Figure 6), shows the fragment F-292 fits very well in the cavity predicted by AlphaFold2. The phenyl ring of F-292 makes hydrophobic interactions with P293 of TEAD2 and the amino group creates hydrogen bond with Q247 whereas at the other end of F-292 the pyrazole ring is close to S323. F-292 occupies a unique pocket specific of hTEAD2. However due to its small size, we expected a low binding affinity towards TEAD and a low efficacy in disrupting the formation of the YAP/TAZ-TEAD protein complex in cells as it was found for fragment 15. [START_REF] Kaan | Targeting YAP/TAZ-TEAD Protein-Protein Interactions Using Fragment-Based and Computational Modeling Approaches[END_REF] Nevertheless, F-292 constitutes an ideal platform for the design of selective TEAD2 ligands.

B. Through internal binding pocket

To date, most of the workforce bent toward the internal pocket, and selectivity was mostly reached without being looked at.

16 is an optimized analog of a validated hit selected by HTS by Vivace Therapeutics. 16 selectively prevents palmitoylation of TEAD1 in a cell-based palmitoylation assays and inhibits endogeneous TEAD1 palmitoylation in cells. [START_REF] Tang | Small Molecule Inhibitors of TEAD Auto-Palmitoylation Selectively Inhibit Proliferation and Tumor Growth of NF2-Deficient Mesothelioma[END_REF] TSA experiments showed strong stabilizing effects of 16 on purified recombinant TEAD1 (8.3°C) and in a lesser extent on TEAD2 (4.2°C). YAP/TAZ-TEAD interaction disruption has only been conducted in NF2 (Neurofibromatosis 2)mutant NCI-H2373 cells on TEAD1 and TEAD4 and 16 was found to selectively reduce YAP-TEAD interaction after 4 and 24 h and TAZ-TEAD after 4 h. 16

potently inhibited the proliferation of NF2-mutated/deficient cell lines in vitro, but failed to show antiproliferation activity in additional mesothelioma cell lines without NF2 mutations, but harboring alterations in other Hippo pathway core components.

1 was reported as a novel TEAD inhibitor with anti-tumor effects on pleural mesothelioma. [START_REF] Kaneda | The Novel Potent TEAD Inhibitor, K-975, Inhibits YAP1/TAZ-TEAD Protein-Protein Interactions and Exerts an Anti-Tumor Effect on Malignant Pleural Mesothelioma[END_REF] SPR experiments showed that 1 inhibited the interaction of TEAD1 C-terminal binding domain and biotinylated YAP peptide and in NCI-H226 cells, 1 was found to be more active on TEAD1-YAP disruption than on TEAD4-YAP complex. Although 1 was not claimed to be a selective ligand of TEAD1, it appears it exerted a stronger inhibitory activity towards NF2-nonexpressing mesothelioma cell lines as found for 16 (Figure 7). 18 was reported to be a selective ligand of TEAD3. It derived from 17 which can inhibit TEAD1/3 at submicromolar level. [START_REF] Lu | Discovery of a Subtype-Selective, Covalent Inhibitor against Palmitoylation Pocket of TEAD3[END_REF] These promising strategies share the same drawback: a lack of rational design potential other than the covalent binding. Thus, we focused our interest onto the structural determinants that could and should exist and underlie of the observed selectivity. For this purpose, we performed docking study on these selective ligands (1, 16-18).

Despite that 1, 17 and 18 are able to covalently bind to TEAD through a nucleophilic attack of thiol function of the conserved cysteine, we did not used covalent docking first intention to avoid to introduce a priori bias to the method.

Indeed, an effective covalent ligand can be viewed as a specific non-covalent ligand that will undergo covalent bond formation after interaction with its target. [START_REF] Singh | The resurgence of covalent drugs[END_REF] Since we were interested in the structural determinant of binding, the use of covalent docking would introduce an a priori for the most favorable binding site.

In our approach, we looked for binding specificities of the described ligands to observe the emergence of a rational binding pattern. Subsequently, if a covalent inhibitor specifically binds in a manner that allows reactivity with the thiol function, our model would then validate its specificity. due to a series of subtle differences (tyrosine in TEAD3 for a phenylalanine in the other TEADs, that was previously identified by Holden and Cunningham [START_REF] Holden | Targeting the Hippo Pathway and Cancer through the TEAD Family of Transcription Factors[END_REF] , as reported in table 3 (in blue and purple). The N-methylsulfamide warhead is surrounded by several protic residues (serine, cysteine, lysine) that make hydrogen bonds with the oxygen and nitrogen atoms of this moiety (Figures 9).

This docking is in accordance with TSA experiments. [START_REF] Tang | Small Molecule Inhibitors of TEAD Auto-Palmitoylation Selectively Inhibit Proliferation and Tumor Growth of NF2-Deficient Mesothelioma[END_REF] In the TEAD palmitoylation assay in cells, HEK293T cells are transfected with myc-TEADx expression plasmid but the transfection seemed to be less efficient with myc-TEAD2 than with the others. It appears 16 seemed to moderately inhibit TEAD2 palmitoylation.

Docking of 1 gave the same results as for 16. 1 fits in the internal pocket of TEAD1 and TEAD2 (Figure 9A) with score for the best pose of -8.1 and -9.1 respectively but is inserted into the surface pocket close to loop B of TEAD3 and TEAD4 (Figure 9B) with score for the best pose of -6.6 and -6.3 respectively. The discrepancy is more marked in term of scoring for 1 than for 16.

The best pose of 1 in TEAD1 and TEAD2 showed the vinyl group of 1 is ideally exposed to the nucleophilic attack of C359 or C380. This docking is in accordance with the pull-down experiments in cells [START_REF] Kaneda | The Novel Potent TEAD Inhibitor, K-975, Inhibits YAP1/TAZ-TEAD Protein-Protein Interactions and Exerts an Anti-Tumor Effect on Malignant Pleural Mesothelioma[END_REF] showing that 1 inhibits more efficiently YAP/TAZ-TEAD1 interactions than YAP/TAZ-TEAD4 interactions. ). In TEAD1, 2 and 3, 18 has its vinylsulfamide moiety oriented towards nucleophilic residues (C359 for TEAD1, S331 for TEAD2, K345 for TEAD3). 17

and 18 seemed to be too small and too flexible for the docking to discriminate between the tight and subtle differences of the internal pocket of the four TEAD members. In the original publication [START_REF] Lu | Discovery of a Subtype-Selective, Covalent Inhibitor against Palmitoylation Pocket of TEAD3[END_REF] , the authors explained the selectivity of 17

for TEAD1 and 3 and of 18 for TEAD3 by docking 17 and 18 using Covalent Docking panel integrated in Maestro 9.2. In their study, they claimed 17 has a steric clash with L383 (TEAD2) and L366 (TEAD4) that are methionine residues in TEAD1 and 3 and 18 could form hydrogen bond with Y230 (TEAD3).

Secondly, we docked covalent ligands 1, 17 and 18 on C-terminal domain of TEAD1-4 using GOLD. [START_REF] Biovia | Dassault Systèmes, Discovery Studio[END_REF] As expected, covalent docking gave solutions for these three acrylamide derivatives for the four C-terminal domains of TEAD and is therefore unable to explain selectivity (Supplement figures 5, 6 and 7).

Finding this potential lack of apparent rational structure-activity relationship, we analyzed the volume of the internal pocket of hTEAD2 for each hTEAD2 monomer using Ligbuilder 3.0 cavity. For crystal structures where the internal pocket is occupied by myristate or palmitate (Table 1, entries 6-20), the volume is 393.4 ± 32.7 Å 3 whereas the volume of soaked hTEAD2 with small molecules is 468.0 ± 58.5 Å 3 (table 1, entries 9-15)(Figure 9). The same difference can be found in hTEAD1 and hTEAD3. This means that the internal pocket has remarkable plasticity/adaptability to the ligand (fatty acid or exogenous molecule) which makes the design of selective ligands based on steric constraints extremely unlikely. Therefore, we propose here a design of rational selective ligands using our finding.

TEAD1 displays two cysteines in its internal pocket that are not conserved on the others, C296 and C405, that could be targeted by covalent binding. Opposingly, TEAD3 lacks two conserved cysteines (V331 and V411) and could therefore be avoided or targeted by more hydrophobic moieties near these regions. TEAD2

noticeably displays a non-conserved tryptophane in the very bottom of its internal pocket, making it smaller and allowing specific targeting through aromatic interactions.

V. Conclusion

The analysis of the C-terminal domain of the four members of the TEAD family revealed a high conservation of the protein-protein interface with its co-activators but significant differences in regard of the internal pocket : (i) the number of cysteine residues pointing towards the internal pocket could be used to design new ligands specific of TEAD1 (4 cysteines), TEAD2/4 (2 cysteines) or TEAD3 (1 cysteine); (ii) the bottleneck that forces palmitate/myristate to form a bend at C5/C6 (M358/M362 for TEAD1, M379/L383 for TEAD2, M367/M371 for TEAD3 and L359/M363 for TEAD4); (iii) the specific tyrosine residue of TEAD3 (Y230) [START_REF] Holden | Targeting the Hippo Pathway and Cancer through the TEAD Family of Transcription Factors[END_REF] ; (iv) the external loop A of TEAD2 which is close to W308 pointing at the hydrophobic end of the internal pocket.

A lot of effort has been devoted to targeting both the protein-protein interaction of TEADs with its co-activators with moderate success. Most of the effort are now focused on the internal palmitoylated pocket that appears to be able to modulate (mainly inhibit but also activate [START_REF] Pobbati | Identification of Quinolinols as Activators of TEAD-Dependent Transcription[END_REF] ) the activity of TEADs. Several groups have designed molecules bearing a reactive function to create a covalent bond with the highly conserved cysteine at the entry of palmitate pocket (C380 in hTEAD2).

Selective drugs could bear two reactive functions with different reactivity (Michael acceptors, epoxide, sulfoxide, chloroacetamide, nitrile, ketoamide) [START_REF] Bum-Erdene | Small-molecule covalent bond formation at tyrosine creates a binding site and inhibits activation of Ral GTPases Proc[END_REF][START_REF] Sutanto | Covalent inhibitors: a rational approach to drug discovery[END_REF] that could react with two cysteines or with one cysteine and another nucleophile (tyrosine, serine, threonine). To date, all the published strategies are presently lacking a structure-based design as the internal pocket displayed a high plasticity.

Silencing individual members of the TEAD family in hepatoblastoma cell lines gives raise to the overexpression of other members and of certain target genes [START_REF] Zhang | TEA Domain Transcription Factor 4 Is the Major Mediator of Yes-Associated Protein Oncogenic Activity in Mouse and Human Hepatoblastoma[END_REF] while in primary human keratinocytes, it is necessary to silent both TEAD1 and TEAD3 to reduce the expression of target genes with a concomitant increase of TEAD2. [START_REF] Li | TEAD1 and TEAD3 Play Redundant Roles in the Regulation of Human Epidermal Proliferation[END_REF] Therefore, in given cellular conditions, some TEADs can display effects opposing the others, which would lead to a failure of pan-TEAD inhibitors and justify the interest of selective TEAD ligands. Selectivity has already been approached by several groups, and here we propose to design covalent ligands toward non-pan-conserved cysteines. We also demonstrated that a specific pocket

VI. Perspectives: toward a model of full-TEAD inhibition

In this article, we mainly analyzed the primary and tertiary structures of C-terminal domain of TEADs, their ligands to date and questioned their inhibitor potency. The mechanism of action of the ligands of the internal pocket and the acylation to TEADs activity is still largely unknown, let alone the mechanism of ligands targeting this pocket. Conversely, while the targeting of the protein-protein interaction with the co-activators seems more straightforward, most of the ligands inhibiting the interaction failed to translate to cell activities and cell-active compounds seem unrelated to the binding of co-activators. Such inconsistencies raised a major question about the mechanism of TEADs activation. To date, four classes of protein partners are known for TEADs: VGLL1-to-3 activate TEAD independently of the Hippo pathway, YAP/TAZ activate TEADs when unphosphorylated (Hippo pathway off), VGLL4 suppresses TEAD by sequestering it onto an abnormal dimer, [START_REF] Jiao | VGLL4 targets a TCF4-TEAD4 complex to coregulate Wnt and Hippo signalling in colorectal cancer[END_REF] and finally the FAM181 whose effect toward TEADs are still unknown. It seems that YAP/TAZ binding overwrites the VGLL ones but nothing is known to which extent and why, as their binding determinants are mostly shared (Figure 1). [START_REF] Mesrouze | A new perspective on the interaction between the Vg/VGLL1-3 proteins and the TEAD transcription factors[END_REF] The activation of TEADs leads to the binding of the Chène's group on the fact that the binding of the YAP α-helix to TEAD (interface 2) occurs before any event at the interface 3. [START_REF] Bokhovchuk | An Early Association between the α-Helix of the TEAD Binding Domain of YAP and TEAD Drives the Formation of the YAP:TEAD Complex[END_REF] This anti-inhibited form involving interface 2 explains both the present observations on the TEADs activation and the relative failure of the PPI inhibitors. Such inhibitors that will out-compete YAPlike binding will, in this hypothesis, also compete with the auto-inhibited form of TEADs, ultimately leading to its activation. [START_REF] Adihou | A Protein Tertiary Structure Mimetic Modulator of the Hippo Signalling Pathway[END_REF] This hypothesis, once validated, should lead to a more efficient way to modulate the TEAD activity.

Notes

The authors declare no competing financial interest.

Biographies

ACCESSION NUMBERS

The atomic coordinates and structure factors for hTEAD2-F292 has been deposited at the PDB with the code PDB: 7OYJ. Authors will release the atomic coordinates and experimental data upon article publication.

ABBREVIATIONS

Figure 1 .

 1 Figure 1. The different TEAD complexes: (A) with YAP (PDB code: 3KYS); (B) with TAZ (PDB code: 5GNO); (C) with VGLL4 (PDB code: 4LN0); (D) with FAM181A (PDB code: 6SEN); TEAD is in light grey, the  loops at interface 3 are in red, the  helixes at interface 2 are in green and light blue and the  sheets

hYAP1 52 HQIVHV 57 mVGLL1 25

 525725 ----RGDSETDLEALF-NAVMNPKTANVPQTVPMRLRKLPDSFFKPPE 100 mYAP1[START_REF] Tian | Structural and Functional Analysis of the YAP-Binding Domain of Human TEAD2[END_REF] HQVVHV----RGDSETDLEALF-NAVMNPKTANVPQTVPMRLRKLPDSFFKPPE 85 hTAZ[START_REF] Han | YAP/TEAD3 Signal Mediates Cardiac Lineage Commitment of Human-Induced Pluripotent Stem Cells[END_REF] QQVIHV----TQDLDTDLEALF-NSVMNPK----PSS-WRKKILPESFFKEP-D 57 mTAZ[START_REF] Han | YAP/TEAD3 Signal Mediates Cardiac Lineage Commitment of Human-Induced Pluripotent Stem Cells[END_REF] QQVIHV----TQDLDTDLEALF-NSVMNPK----PSS-WRKKILPESFFKEP-D

  reported YAP antagonists while Adihou et al. 41 reported VGLL4 antagonist. In their article, Jiao et al. used the mVGLL4 227 S-249 I doeicosapeptide named TDU2 (Tondu Domain 2) which was optimized into a "superTDU peptide" where TDU2 is linked to YAP's -loop whereas Adihou et al. started from 233 S-252 A peptide which was modified by a simple D 235 E change in order to optimize an intramolecular ionic bond.

Figure 5 .

 5 Figure 5. Superimposition of C-terminal domain of hTEADx (hTEAD1 (tan),

Figure 6 .

 6 Figure 6. Superimposition of hTEAD2 soaked with F-292 (PDB code: 7OYJ)(grey)

Figure 7 .

 7 Figure 7. Structure of selective ligands of one or two members of TEAD

Figure 8 .

 8 Figure 8. Superimposition of the best poses of 16 docked in C-terminal domain of

Figure 9 .

 9 Figure 9. Comparison of hTEAD internal pocket volumes. The boxplots represent

  of hTEAD2 can welcome a small molecule (F-292) that could be a new platform for the design of selective ligands of TEAD2. Three molecules (structures are not disclosed) entered in phase 1 clinical trial: VT-3989 (NCT04665206: Evaluation in Patients With Metastatic Solid Tumors Enriched for Tumors With NF2 Gene Mutations) from Vivace Therapeutics in early 2021, followed by IAG933 (NCT04857372: Evaluation in Patients With Advanced Mesothelioma and Other Solid Tumors) from Novartis and finally IK-930 (NCT05228015: Evaluation in Subjects With Advanced Solid Tumors) from Ikena Oncology in the beginning of 2022.

  most N-terminal part to DNA response sequence. But nothing is known about how the binding of an activator to the C-terminal part of TEADs modulate this Nterminal part. The activation of TEADs means that an inactive form should exist, that should be modified by the co-activators. At this point, Alphafold2 provided us with the starting point of a new hypothesis, modeling a part of the linker (between the N-terminal and the C-terminal domains) (Figure10A) region of TEADs as a bent helix interacting with the interface 2. Regarding the conservation of the sequence, both the N-and C-terminal domain are strongly conserved but the linker region also displays three sub-regions highly conserved, among which one is the one from the bent helix of the Alphafold2 models (Figure10Bin dark grey). Thus, we formulated the hypothesis that TEADs exist in an inactive auto-inhibited form involving the linker region folded around the interface 2 and therefore sequestrating the N-terminal domain. This correlated well with the conclusions of

Figure 10 .

 10 Figure 10. A: Sequence alignment of the linker between the DNA binding domain

Maxime

  Liberelle holds an MSc in drug design from University of Lille (France), awarded in 2015. He obtained his PhD in structural biochemistry in 2019 on the characterization, structure-function relationships, and therapeutical targeting of oncogenic complex MUC4-ErbB2 under the supervision of Prof. Nicolas Lebègue at the University of Lille in the laboratory of Prof. Patricia Melnyk. After a 2-year postdoc position at the University of Louvain (UCLouvain, Belgium), with Prof. Raphaël Frédérick, he joined the University of Lille, where he is associate professor of biophysics and medicinal chemistry. His research focuses on the protein-protein interaction field, from characterization to targeting. Florine Toulotte obtained her MSc in drug design at the University of Lille. She has just obtained her PhD thesis in medicinal chemistry at the University of Lille in the laboratory of Prof. Patricia Melnyk in dec 2021. Her main research interest concerns the design and synthesis of new small molecules to inhibit protein-protein interaction and their evaluation. Nicolas Renault obtained his PhD degree in molecular modelling at the University of Lille in 2010. He is a research engineer with an expertise in structural bioinformatics and in silico drug design. Affiliated to the INFINITE research team dedicated to inflammation, he coordinates a platform of protein modelling and virtual screening with successful applications of structure-based design of cannabinergic, purinergic or PPI ligands. He also contributed to many studies focusing onto structure-function relationships of proteins. Muriel Gelin obtained an engineering degree and a PhD, both in chemistry in 1999, worked 6 years in a pharmaceutical company in drug development, and then obtained a Master of Science in structural biology. She works as a CNRS research engineer at the Centre de Biologie Structurale (CBS) in Montpellier. Her fields of expertise are crystallography of biomolecules, synthesis in medicinal chemistry, structural chemoinformatics including virtual screening, molecular modeling, rational drug design (Fragment Based Drug Design), automation by writing programs in python and experimental screening by crystallography and several other techniques such as Thermal Shift Assay or ITC. She is in charge of the ligand screening activity on the CBS crystallographic platform. Frédéric Allemand is an engineer from Toulouse National Institut of Applied Sciences. He obtained his PhD in biochemistry and molecular biology at the university of Paris-Jussieu in 2006. He is Research Engineer in the Scientific Research National Center at the Montpellier Structural Biology Center (CBS). He studied for several years the regulation of ribosomal genes expression in prokaryotes. Then, he specialized in proteins biochemistry, proteins biophysical characterizations and molecular interactions. He is the technical manager of the CBS Biophysical characterizations platform. Patricia Melnyk Patricia Melnyk earned her degree in Chemical Engineering from Chimie ParisTech (1989) and a PhD in Organic Chemistry from the Institut de Chimie des Substances Naturelles (Paris 6 University, 1993). She is Professor of Chemistry at the Faculty of Pharmacy of Lille University and the team leader of "Brain Biology & Chemistry" team in the Lille Neuroscience & Cognition research center (Inserm UMR-S1172). Her major research interests focus on medicinal chemistry and chemical biology in the area of neurodegenerative diseases and cancer. She cofounded AlzProtect, a start-up dedicated to the clinical development of drug candidates for Alzheimer and neurodegenerative diseases. She is at the origin of the discovery of AZP2006, a drug candidate in clinical phase II. Jean-François Guichou obtained his PhD in Organic chemistry at the University of Lausanne in 2002. He is professor of structural biology and drug design at the University of Montpellier, and his expertise is in medicinal chemistry, FBDD, drug design and X-ray crystallography. He worked in the field of antiviral agents (inhibitors of cyclophilin), infectious diseases and cancer. He is the scientific director of AGVDiscovery, a company developping targeted therapies in oncology. Philippe Cotelle obtained his PhD in Spectrochemistry at the University of Lille in 1987. He is professor of organic chemistry at the National Graduate School of Engineering Chemistry of Lille -Centrale Lille Institut, and his expertise is in medicinal chemistry and translational research. He worked for several years in the field of antiviral agents (HIV-1 integrase, HIV-1 and HBV ribonuclease H and other two-magnesium viral enzymes) and has coordinated several national projects in viral diseases. He moved on the area of protein-protein interactions and is interested in developing new drugs/chemical tools targeting the final effectors of the Hippo pathway. ACKNOWLEDGMENTS This work was financially supported by grants from le Ministère de l'Education et de la Recherche and the University of Lille (F.T.) This work was also supported by the French Infrastructure for Integrated Structural Biology (FRISBI) ANR-10-INSB-05-01. These experiments were performed at ID30A-1 beamline at ESRF Synchrotron with the collaboration of ESRF staff. We acknowledge the European Synchrotron Radiation Facility for provision of synchrotron radiation facilities.

Table 2 .

 2

Sequence alignments of TEAD binding domain of YAP, TAZ, VGLLs and FAM181. Residues of the interfaces 1, 2 and 3 are highlighted in purple, green and red respectively. Numbering of the different proteins can be found in http://www.uniprot.org/ (P46937, P46938, Q9GZV5, Q9EPK5, Q99NC0, Q80V24, Q8N9Y4 and A6NEQ2).

Table 1

 1

	, entries 5, 9-15, 22)

Peptides have been specially designed to bind to interface 3 (Table 1, entry 34) or interface 2 (Table 1, entry 43).

Table 3 .

 3

	found in http://www.uniprot.org/ (P28347, Q15562, Q99594, Q15561 and Q62296
	respectively).

Sequence alignments of YBD (YAP-Binding Domain) of crystallized

TEADs. Residues of the interfaces 2 (in green) and 3 (in red) are highlighted.

Residues of the internal pocket are highlighted in cyan (hydrophobic sub-pocket) and magenta (hydrophilic sub-pocket. Residues making covalent bond with fatty acid are highlighted in bold grey. Not always well-defined loops are in purple box (loop A) and in green box (loop B). Numbering of the different proteins can be

  Many groups have developed ligands targeting this internal pocket. Firstly, Pobbati et al. reported niflumic acid an fenamic acid derivatives (Table 1, entries 9-10 and Figure 4, 2-3) 52 as ligands of this internal pocket, following by W. Xu et al. which patented MGH-CP1 and derivatives (Table 1, entry 11 and Figure

4, 4).

[START_REF] Li | Lats1/2 Sustain Intestinal Stem Cells and Wnt Activation through TEAD-Dependent and Independent Transcription[END_REF][START_REF] Wu | Tead Transcription Factor Autopalmitoylation Inhibitors[END_REF]

More recently, Gagnon et al. reported the structure of hTEAD2 with LM98, a synthetic analog of niflumic acid

[START_REF] Gagnon | Development of LM98, a Small-Molecule TEAD Inhibitor Derived from Flufenamic Acid[END_REF]

(Table

1

, entry 14 and Figure

4, 7

) and Holden et al. discovered other powerful inhibitors of palmitoylation (Table

AUTHOR INFORMATION

Corresponding author

* Phone: 362 28 36 94; E-mail: philippe.cotelle@univ-lille1.fr

ORCID


Nathalie Mitton
email: nathalie.mitton@inria.fr

Yasir Saleem
email: yasir.saleem@aber.ac.uk

Valeria Loscri
email: valeria.loscri@inria.fr

Christophe Bureau

Adaptive HELLO Protocol for Vehicular Networks

In vehicular-to-vehicular networks, the update of car Firmwares Over-The-Air (FOTA) is becoming a challenging issue. Indeed, it mainly relies on topology discovery of neighbouring nodes. Topology discovery in mobile wireless networks is usually done by using HELLO messages. Due to mobility, topology changes occur frequently and must be quickly discovered to avoid routing failures. Since the optimal HELLO frequency depends on parameters that are subject to changes (e.g., speed of nodes, density of nodes), it must be dynamically adjusted to obtain the best trade-off between the network load and the freshness of routing tables. Existing solutions mainly focus on general wireless networks assuming random mobility and constant node density and average speed. Such assumptions do not hold in the case of vehicular networks in which vehicles follow specific trajectory patterns (the roads) and density and speed evolve as a function of time (rush hour vs non-rush hour) and area (urban, rural, highway). In this paper, we first draw the specific features of a vehicular network at different times and spaces by analysing real datasets. This study then allows us to adapt a dynamic neighbour discovery protocol to the specific case of vehicular-to-vehicular communications to propose VANP (Vehicular Adaptive Neighbour Discovery Protocol). VANP is a fully distributed and software-based solution that sends beacons at an optimal frequency without knowing it a priori. The objective is to reduce the frequency at which HELLO messages are sent to save bandwidth and energy while still preserving the quality of the neighbour discovery. Through extensive simulations run on real datasets, we show that the optimal HELLO frequency can be reached by maintaining a constant optimal turnover, independent from the speed of the nodes and by aiming at this turnover, nodes automatically use the optimal HELLO frequency. Results show that VANP allows the discovery of relevant neighbours by missing at most two neighbours over all scenarios and reducing the number of HELLO messages up to twice, hence saving bandwidth and energy.

I. Introduction

The update of car Firmwares Over-The-Air (FOTA) is a growing trend that transforms software related recalls into mere updates, thus considerably reducing the cost of recalls for car manufacturers, while increasing driver safety in quasi real time. However, with the steep increase in the number of processors per vehicle, combined with the increase in the number of connected and electric vehicles, the number and data volume of updates of Firmwares Over-The-Air (FOTA) is expected to increase exponentially. Multiplied by the increasing cost of mobile data subscriptions, this leads to the paradox that by 2030 or even before that, it may be more costly to update vehicles than to move them if FOTA is only relying on mobile network communication (be it LTE/4G or 5G) [START_REF]Car fota based on mobile networks: A dead end?[END_REF]. In addition, a significant portion (15 to 20%) of the reduction in CO2 footprint brought by (connected) electric vehicles is ruined by the carbon impact of mobile networks and cloud infrastructure [START_REF]Estimating carbon emissions in mobile networks[END_REF]. There is thus a need to find a credible alternative to mobile networks for FOTA's, from the ones that occur on the parking of the factory to the ones taking place when cars are already on the road. One appealing solution resides in the use of through-car mesh networks: car crowds are "quasinetworks", only missing an ubiquitous mesh organisation with a radio network providing sufficient throughput. Such mesh networks are collaborative in nature, and much more open to creative business models without subscriptions, hence with the potential to bypass all or part of the cost of data subscription that presently makes FOTA appear like a dead-end. In addition, a mesh network being intrinsically more efficient that a global LTE network, one can also expect a significant reduction in the carbon footprint of FOTA using mesh networks rather than mobile-based networks. In such a mesh, vehicular-tovehicular (V2V) communications are dynamically created when the vehicles are close enough to one another, and no pre-established infrastructure is required. Due to the path loss of radio communications, only close vehicles may directly communicate to each other. Long-distance communications require multi-hop routing, where packets are forwarded by multiple intermediate nodes. Many efficient localised routing and data forwarding protocols rely on a local neighbourhood table. This table is created by each node u and contains the list of nodes with which u can directly communicate (its neighbours). It is generally maintained by letting nodes broadcast HELLO messages to their neighbours.

The efficiency of table-driven protocols (e.g., routing, clustering, activity scheduling) obviously relies on the accuracy of these tables. In a mobile environment, neighbourhood tables are subject to change, and in this case, the accuracy depends on the frequency of HELLO messages. If this frequency is too low, nodes may not be detected by their neighbours, leading deprecated neighbourhood tables, and protocol failures are likely to occur. On the other hand, if the frequency is too high, neighbourhood tables are up to date, but then energy and bandwidth are wasted to the detriment of data traffic.

Yet, determining the correct frequency is not obvious. The optimal value, providing a good trade-off between these behaviours, actually depends on dynamic characteristics, such as the speed of nodes, and should thus be dynamically updated. By optimal frequency, we mean the minimum frequency at which HELLO messages can be sent to ensure that nodes correctly detect each other. The most straightforward solution is to suppose that nodes know their speed, but this assumption requires dedicated hardware (e.g., GPS) that may not be available.

In this paper, we first analyse the behaviour of a vehicular network in different environments (urban, highway) at different times (rush hour, non-rush hour) by running extensive real dataset based experimentation. Thanks to them, we could observe among others that each node discovers a non negligible part of neighbours with which it does not stay in range long enough to initiate some data exchanges. In a vehicular network application, we can thus distinguish the "relevant neighbours" from the set of all neighbours. We define the "relevant neighbours" as the neighbours with which we remain in range of each other long enough to exchange data. By adapting and decreasing the HELLO frequency, we consequently may miss neighbours. What we claim in this study is that this is not mandatory to discover all of them, it is even desirable since we mainly need to discover "relevant neighbours".

These important observations have driven our study and the adaptation brought to TAP (Turnover-based Adaptive HELLO Protocol), an existing adaptive neighbour discovery protocol designed for general wireless networks [3]. Our goal is to set proper parameters in our HELLO frequency adaptation algorithm in order to reduce HELLO frequency when possible without jeopardising the efficient discovery of "relevant" neighbours. As a result, we propose VANP , a vehicular adaptive neighbour discovery protocol. The key features of VANP are as follows :

• It is localised, and thus topology changes have very limited impact. The contributions of this paper can be summed up as follows:

• a road traffic analysis based on real datasets that shows that it is not useful to discover all neighbours every time, • the VANP protocol, an adaptation of the TAP protocol to the vehicular context, • a complete simulation-based evaluation relying on real datasets showing that VANP allows the discovery of relevant neighbours by missing at most two neighbours over all scenarios and reducing the number of HELLO messages up to twice hence saving bandwidth and energy. The outline of this paper is as follows. After discussing related works in Section II, Section III presents the motivation of this work. Section IV provides a background of TAP. In Section V, we describe our protocol and discuss a few implementation issues, mainly about the accurate estimation of the turnover. Section VI provide some experimental results run over real datasets and presents the performance of VANP . We finally conclude and discuss open issues in Section VII.

II. Related works

Hello protocols and neighbours discovery have been the focus of several existing studies since networks exist. In this related work review, we mainly focus on neighbour discovery for vehicular networks [START_REF] Kim | Resolving the unfairness of distributed rate control in the IEEE WAVE safety messaging[END_REF], [START_REF] Chaabouni | A collision-based beacon rate adaptation scheme (CBA) for VANETs[END_REF], [START_REF] Bansal | Limeric: A linear adaptive message rate algorithm for dsrc congestion control[END_REF].

The authors of [START_REF] Abbas | A position-based reliable emergency message routing scheme for road safety in VANETs[END_REF] propose REMR, a position-based routing scheme for emergency messages which adapts the HELLO interval based on the neighbourhood density to minimise HELLO messages congestion. The HELLO interval is initialised to 0.03s. Before sending a HELLO message, a vehicle checks whether the number of its neighbours is greater than the average number of neighbours in the network (considered as a threshold value). If so, the network is considered as high-density and the vehicle adapts the new HELLO interval by adding the ratio of the number of vehicles at current and previous time steps to the HELLO interval. Otherwise, it sets the HELLO interval to 0.03s. The limitation of this work is that there is no means to reduce the HELLO interval except resetting it to 0.03s, which is not always pertinent and assumptions do not always hold.

Li [START_REF] Li | Cooperative beacon rate adaptation for vehicular adhoc network[END_REF] proposed the adaptation of HELLO interval using cooperative scheme for vehicular networks based on the acknowledgements of HELLO messages. The acknowledgements are used to identify HELLO messages loss. When a vehicle detects HELLO messages loss, it increases its HELLO frequency to retain the neighbourhood information. The limitation of this work is that vehicles are required to know their neighbours for receiving acknowledgements and the medium is quickly saturated by multiple acknowledgements.

In [START_REF] Wang | Research on adaptive beacon message transmission power in vanets[END_REF], rather than adapting the HELLO interval, the authors investigate adapting the transmission power of HELLO messages based on the prediction error of vehicle position. The vehicles increase their transmission power of HELLO messages when prediction errors are high, while reduce their transmission power on lower prediction errors. The simulations results showed reduced channel busy time and higher packet transmission rate compared to fixed transmission power of HELLO messages but they pursue a different goal.

Lyu et al. [START_REF] Lyu | Abc: Adaptive beacon control for rear-end collision avoidance in vanets[END_REF] worked on an adaptation of HELLO interval to avoid rear-end car crash by defining a danger coefficient which identifies the danger threat of each vehicle to be involved in a rear-end collision. Based on the danger coefficient, the authors proposed a distributed HELLO messages congestion control strategy to adapt the HELLO interval. Each vehicle calculates its danger coefficient and shares with neighbouring vehicles through HELLO messages. The vehicles having higher danger coefficient use lower HELLO interval to allow taking immediate actions by rear vehicles in case of sudden braking to avoid collisions.

Li et al. [START_REF] Li | A mobility prediction based beacon rate adaptation scheme in VANETs[END_REF] used mobility prediction to adapt the HELLO interval and to reduce channel occupancy due to the frequent broadcasting of HELLO messages. The authors claim that vehicles can predict the position of neighbouring vehicles. The vehicles use Kalman Filter to predict the future possible moving states and use kinematics law to predict the mobility of their neighbouring vehicles. The HELLO interval is adapted by comparing the prediction error to a deviation threshold. If prediction error is higher than the deviation threshold, the HELLO messages are broadcast, otherwise the HELLO interval is reduced.

Nguyen and Jeong [START_REF] Nguyen | Mobility-adaptive beacon broadcast for vehicular cooperative safety-critical applications[END_REF] investigated adaptive HELLO broadcast using mobility prediction for guaranteed tracking of degree (GTK) K. The allowed tracking inaccuracy that does not affect the reliability of vehicle collision avoidance is called tracking threshold. Given a tracking threshold, GTK K is defined as the guarantee that a vehicle that receives at least one of the K HELLO messages from a sending vehicle, should be able to estimate the position of sending vehicle within the accuracy of tracking threshold. The main objective of authors' scheme is to postpone the broadcasting of HELLO message as long as the tracking inaccuracy is less than the tracking threshold. This saves the frequent broadcasting of HELLO messages.

In [START_REF] Barbieri | Adaptive beaconing for safety enhancement in vehicular networks[END_REF], the authors investigate rear-end collision and proposed BASE for the adaptation of HELLO interval to save the radio resources without jeopardising the safety requirements. BASE adapts the HELLO interval of each vehicle by guaranteeing that a minimum safety distance should always be maintained between vehicles. The minimum safety distance is defined as the required distance to avoid rear-end collision caused by sudden brake of vehicle in front. BASE is mainly focused on normal traffic conditions and therefore, does not consider complicated conditions, such as crossroads and overtaking.

In [START_REF] Goudarzi | Non-cooperative beacon rate and awareness control for VANETs[END_REF], the authors worked on congestion control by investigating the adaptation of HELLO interval and awareness control using non-cooperative game theory and proposed NORAC. NORAC assigns a HELLO interval to each vehicle fulfilling its needs by guaranteeing fairness among vehicles having similar needs. NORAC is distributed and non-cooperative. It guarantees fairness using the fair concept of Nash Equilibrium.

Unlike these works, our approach does not require heavy-computing or predictions. It is localised and fully adaptive.

III. Motivation : vehicular networks study

In order to characterise key features of a vehicular network, we have run a simulation based study by analysing real traffic datasets. We have used the SUMO (Simulation of Urban MObility) [START_REF] Lopez | Microscopic Traffic Simulation using SUMO[END_REF] road traffic simulator integrated with OMNeT++ [START_REF] Varga | An Overview of the OMNeT++ Simulation Environment[END_REF], an event-driven network simulator to simulate the vehicular wireless communications and Veins [START_REF] Sommer | Bidirectionally Coupled Network and Road Traffic Simulation for Improved IVC Analysis[END_REF], an open-source framework that provides the functionality of vehicular network.

Various real-world road traffic scenarios of different cities have been made available by researchers 1 for SUMO [START_REF] Lopez | Microscopic Traffic Simulation using SUMO[END_REF] that can be imported to various network simulators (e.g., OMNeT++, NS-3). We conducted this analysis over different cities. In this paper, we only present the results for the city of Dublin over different scenarios but results are similar for different cities.

A. Scenarios description

In this paper, we mainly focus on the scenarios of rush and non-rush hours of Dublin City Centre (referred as Ireland urban scenario hereafter) and Ireland National Road (referred as Ireland national highway hereafter). The rush hour (saturated traffic) is when the level of traffic is high and it starts getting congested. The non-rush hour (free flow traffic) is early morning traffic when the level of traffic is low.

1) Ireland Urban Scenario: Ireland urban scenario is comprised of 5km×3.5km Dublin city centre having 435 signalised intersections. Dublin SCATS dataset2 , a traffic light control system, was used to generate the traffic by counting the vehicles using SCATS sensors every six minutes at 480 locations in Dublin city. It provides traffic for 24 hours. The traffic between 8am-9am and 4am-5am are the rush and non-rush hours traffic, respectively [START_REF] Gueriau | Quantifying the impact of connected and autonomous vehicles on traffic efficiency and safety in mixed traffic[END_REF].

2) Ireland National Highway Scenario: Ireland National Highway is N7, a 3-lane two-way road of 17.1 km long having 11 on-and off-ramps each way. The loop sensors from open dataset were used to generate the traffic and the Transport Infrastructure Ireland3 published the data that includes 5-minute aggregated data for each lane and direction for several months. The traffic is averaged to create a workday traffic by excluding weekends and bank holidays. It provides traffic for 24 hours. The traffic between 5am-6am and 4am-5am are the rush and nonrush hours traffic, respectively [START_REF] Gueriau | Quantifying the impact of connected and autonomous vehicles on traffic efficiency and safety in mixed traffic[END_REF].

B. On the pertinence of relevant neighbours

As previously discussed, we claim that it is not useful to detect all neighbours at everytime but only relevant neighbours, i.e. the ones that allow a contact long enough for a data transmission. To illustrate this, Figure 1 the average contact duration of connections between two vehicular neighbours. We can see for instance on this figure that in an urban environment at rush hour time (orange curve) that 50% of connections last for less than 12s and that only 20% of connections last more than 20s. Applications in vehicular networks generally require the exchange of data and thus a stable contact during a minimum time. Vertical lines on figure mark the limits for connections that last respectively more than 3, 5 or 10s. If we define the relevant neighbours as the neighbours that remain in contact for at least x seconds, we can see that in urban environment in rush hour, only 93% neighbours are relevant for x = 3, 90% for x = 5 and that this amount drops to 76% for x = 10s. This demonstrates that there is no use to design a neighbour discovery protocol that has a constant complete view of neighbourhood since part of the nodes will not be usable. Figure 2 shows for each environment the average time before meeting a relevant neighbour. As expected, it highlights that in average, a node needs much more time before meeting a relevant neighbour than any single neighbour. As such, this means that the delay between two HELLO messages can be increased. This motivates the need to provide an adaptive Hello protocol specific to the vehicular context.

Urban non-rush hour

Table I sums up the notations used in this paper.

IV. Background: the TAP protocol

In this section, we provide a summary of the TAP protocol [3] that lays the basis of VANP. Let us assume that nodes send HELLO messages at the frequency f HELLO (a HELLO message is sent every d HELLO = 1 f HELLO ). Whenever a node receives a HELLO message, it updates its neighbourhood table, thus generating some turnover Given a period of time ∆t, we define the turnover r ∆t to be the ratio between the number of new neighbours (i.e., nodes that were not already neighbours ∆t units of time earlier) and the current total number of neighbours.

Obviously, the turnover depends on both ∆t and f HELLO . Without loss of generality, let us set ∆t = 1/f HELLO = d HELLO , that is, the turnover is updated each time a new HELLO message is sent. As is, a high frequency induces a low turnover (nodes frequently update their tables and thus discover few new neighbours each time), while a low frequency induces a high turnover. Because of that direct relationship between the two values, we can note that acting on one of them directly affects the other one. TAP relies on the idea that the optimal HELLO frequency f opt generates an optimal turnover r opt , and by keeping r close to r opt , f HELLO automatically tends toward f opt . Nodes thus have to slightly adjust their frequency with regards to the observed turnover. Authors of [3] proved that while the optimal frequency depends on the speed of the node, the optimal turnover is fixed and does not depend on any such parameter. The optimal frequency indeed evolves accordingly to the speed (i.e., it increases when the speed increases, and decreases when the speed decreases), but eventually generates a constant turnover r which can be computed offline. TAP is also efficient in static networks.

V. Vehicular Adaptive Neighbour Discovery Protocol

As explained, VANP is inspired by TAP. However, TAP does not specify the way to adapt the frequency based on the observed turnover. Also, TAP has computed the optimal turnover r opt in a general wireless network, assuming nodes are uniformly distributed in space and follow a random way point mobility model with fixed average speed, which is not the case in vehicular network. In this section, we describe VANP and in particular how it adapts the HELLO frequency. Then we compute the optimal turnover to be observed in our environment.

A. Implementation 1) Implementation: Obviously, accurately estimating the turnover is of prime importance. As we will show in the next section, the value of the optimal turnover may be quite low, and for low densities it can be difficult to effectively estimate the current turnover. For instance, if a node has only two neighbours at a given moment, the turnover is limited to three distinct values (zero if none of the neighbours are new, one if only one of them is new, or two otherwise), which is not precise enough to accurately adjust the current HELLO frequency. A solution to this problem is to take account of the number of new neighbours that appeared at every X previous observations, X being the size of the history. In that case, the value may be obtained by enumerating new neighbours between two successive tables:

r = d HELLO t X -t 0 X i=1 new ti-ti-1 |N ti | , (1)
where new ti-ti-1 is the number of new neighbours detected between times t i-1 and t i , and N ti is the neighbourhood table at time t i and |N ti | its size. By doing this, it is possible to obtain a sufficient accuracy of the turnover estimation, as we will show in Section VI.

The adjustment of f HELLO requires the use of an incremental update function based on the observed turnover r. A very simple series like the following one perfectly fits this purpose:

d HELLO = d HELLO + d HELLO α × g(r) if r ≤ r opt , d HELLO - d HELLO α × g(r) otherwise.
(2) Here, α is a constant controlling the speed of the convergence, and g(r) is a function of the observed turnover that returns how much d HELLO should be changed. To design this function, we should first note that the more r and r opt are different from each other, the more likely the current frequency f HELLO and the optimal frequency f opt are different from each other. Thus, the higher the difference between r and r opt , the more quickly f HELLO should "move" towards f opt . We define g(x) as follows:

g(r) = ( r-r opt r opt ) 2 if r < 2 × r opt , 1 otherwise. (3)
When r and r opt are only slightly different, then the normalised amplitude is close to 0, resulting in a slight variation of f HELLO . Opposed to this, the higher the difference between r and r opt , the higher the amplitude and the faster f HELLO converges toward the optimal frequency f opt . Any other function g(r) such that g(r opt ) = 0 may of course be used. However, this one is very straightforward to implement, and a lookup table could actually be used to avoid overhead.

As a result, Algorithm 1 describes VANP .

B. Determining the optimal turnover r opt Now that the general design of our protocol has been presented, the principal issue that remains opened is: What is the optimal turnover r opt ? Finding the correct value of f opt is indeed not trivial, as it depends on a lot of parameters. To deduce it, we rely on our real dataset analysis.

Algorithm 1 Adaptive Hello Protocol. Compute g(r) using Eq. 3

7:

Compute d HELLO using Eq. 2 Figure 3 shows the proportion of relevant neighbours over time for each scenario. In this figure, we considered as relevant neighbours the ones that remain in contact for more than 3 and 10s respectively. Globally we can observe that whatever the scenario and thus the density and speed of nodes, this proportion remains constant over time and is the same for different times in the urban scenario (about 85% of neighbours in contact for more than 3s and 60% in contact for more than 10s). Third observation is that in highway scenarios where there are less intersections, the gap between the two categories of relevant neighbours is small (in rush hours, 50% of neighbours in contact for more than 3s against 40% for more than 10s and in nonrush hours, for all kind of relevant neighbours 20% of neighbours only). Obviously, when the vehicles can dive fast like in non-rush hour And this proportion allows us to determine the optimal turnover r opt value to be used in the Hello adaptation process.

Based on these values, we retain the r opt values depicted in Table II.

VI. Experimental Results

In this section, we analyse first the behaviour of VANP and then its performances. We use the same set up and simulation environment as detailed in Section III.

A. Protocol behaviour Fig. 4 presents the behaviour of the delay between two HELLO messages for each non-rush hour scenario. We can observe that the delay between two HELLO messages dynamically change over time, as expected.

Figure 5 shows the resulting average d HELLO in every non-rush hour scenario at the end of the simulation. One can observe that for each case, d HELLO > 0.5s the usual d HELLO applied in communication protocols. This demonstrates that VANP sends less HELLO messages than classical protocols in urban environment and thus save energy and bandwidth. At the contrary, more packets are sent in high speed environment (e.g. highway in nonrush hour) in order not to miss important neighbours. We can also observe that as expected, more packets are sent to discover neighbours that remain in contact for more than 3s than for neighbours that remain in contact for more than 10s (delay is smaller) since more nodes have to be spotted.

We can also note that the size of history X is not anodyne since using X = 10 instead of X = 5 allows even more saving and the saving is even more important in high speed scenarios as in highway scenario. This is because a greater history size allows to smooth rapid changes.

B. Protocol performances

Saving energy and bandwidth is paramount but not at the cost of neighbour tables accuracy. Therefore, Fig. 6 presents the amount of false positive relevant neighbours (Relevant neighbours in the neighbourhood table but not in communication range) in different scenarios for nonrush hour.

Whatever the scenarios, we can observe that VANP is very accurate since it never badly tags more than one node at a single time in the worst case and in average 0.2 nodes (so no bad tagging in most of cases).

Similarly, Fig. 7 presents the amount of missed relevant neighbours detections (Relevant neighbours in communication range but not in the neighbourhood table) in different scenarios for non-rush hour.

As previously, we can observe the high performance of VANP since it never miss more than two node at a single time in the worst case and in average 0.5 nodes (so no missed detection in most of cases).

VII. Conclusion

We have presented an adaptive HELLO protocol for vehicular networks that estimates the neighbourhood turnover and adjusts the HELLO frequency consequently. Besides the fact that our protocol is very straightforward to implement, it is especially well-tailored to standard mobile wireless networks since it does not rely on any specific hardware to aim at an optimal HELLO frequency. We have shown under realistic scenarios using real datasets that VANP is very accurate and allows substantial energy and bandwidth saving. Future work will focus on the automatic detection of the scenario (e.g. urban vs highway, rush hour vs non-rush hours) in order to dynamically adapt the optimal parameter setting to the network density and traffic model.

  shows for each environment (urban rush hour, non-rush hour, highway rush hour, non-rush hour) the distribution of

Fig. 1 :

 1 Fig. 1: Distribution of contact time.

Fig. 2 :

 2 Fig. 2: Average time before meeting a new relevant neighbour

1 :

 1 Initialise r opt , d HELLO , X; 2: i = 1;

NFig. 5 :

 5 Fig. 5: Average d HELLO in non-rush hour scenarios

Fig. 6 :

 6 Fig. 6: Number of false positive neighbours in different non-rush hour scenarios

Fig. 7 :

 7 Fig. 7: Number of missed relevant neighbours in different non-rush hour scenarios

TABLE I :

 I Notations.

	Notation	Description
	r	Current observed turnover
	r opt	Optimal turnover
	f HELLO d HELLO f opt	Hello frequency ( f HELLO = d HELLO 1 Delay between two Hello messages ) ( d HELLO = 1 ) f HELLO Optimal Hello frequency
	X	Size of history
	Nt	Neighbourhood table at time t
	r.

TABLE II :

 II r opt values.

	8:	if i < X then i++
	9:	end if
	10:	Schedule Hello message after d HELLO period;
	11: end while
		Urban		Highway
		Rush hour Non-rush hour Rush hour	Non-rush hour
	> 3s	0.85	0.85	0.5	0.2
	> 10s	0.6	0.6	0.4	0.2

https://sumo.dlr.de/docs/Data/Scenarios.html

https://data.gov.ie/dataset/traffic-volumes

https://trafficdata.tii.ie/publicmultinodemap.asp