Expanding molecular modeling and design tools to non-natural sidechains.

Protein-protein interactions encode the wiring diagram of cellular signaling pathways and their deregulations underlie a variety of diseases, such as cancer. Inhibiting protein-protein interactions with peptide derivatives is a promising way to develop new biological and therapeutic tools. Here, we develop a general framework to computationally handle hundreds of non-natural amino acid sidechains and predict the effect of inserting them into peptides or proteins. We first generate all structural files (pdb and mol2), as well as parameters and topologies for standard molecular mechanics software (CHARMM and Gromacs). Accurate predictions of rotamer probabilities are provided using a novel combined knowledge and physics based strategy. Non-natural sidechains are useful to increase peptide ligand binding affinity. Our results obtained on non-natural mutants of a BCL9 peptide targeting beta-catenin show very good correlation between predicted and experimental binding free-energies, indicating that such predictions can be used to design new inhibitors. Data generated in this work, as well as PyMOL and UCSF Chimera plug-ins for user-friendly visualization of non-natural sidechains, are all available at http://www.swisssidechain.ch. Our results enable researchers to rapidly and efficiently work with hundreds of non-natural sidechains.

Augmented epithelial multidrug resistance-associated protein 4 expression in peritoneal endometriosis: regulation by lipoxin A(4).

OBJECTIVE: To compare the expression of the prostaglandin (PG) E(2) transporter multidrug resistance-associated protein 4 (MRP4) in eutopic and ectopic endometrial tissue from endometriosis patients with that of control subjects and to examine whether MRP4 is regulated by the antiinflammatory lipid lipoxin A(4) (LXA(4)) in endometriotic epithelial cells. DESIGN: Molecular analysis in human samples and a cell line. SETTING: Two university hospitals and a private clinic. PATIENT(S): A total of 59 endometriosis patients and 32 age- and body mass index-matched control subjects undergoing laparoscopy or hysterectomy. INTERVENTION(S): Normal, eutopic, and ectopic endometrial biopsies as well as peritoneal fluid were obtained during surgery performed during the proliferative phase of the menstrual cycle. 12Z endometriotic epithelial cells were used for in vitro mechanistic studies. MAIN OUTCOME MEASURE(S): Tissue MRP4 mRNA levels were quantified by quantitative reverse-transcription polymerase chain reaction (qRT-PCR), and localization was analyzed with the use of immunohistochemistry. Cellular MRP4 mRNA and protein were quantified by qRT-PCR and Western blot, respectively. PGE(2) was measured in peritoneal fluid and cell supernatants using an enzyme immunoassay (EIA). RESULT(S): MRP4 was expressed in eutopic and ectopic endometrium, where it was overexpressed in peritoneal lesions and localized in the cytoplasm of glandular epithelial cells. LXA(4) attenuated MRP4 mRNA and protein levels in endometriotic epithelial cells in a dose-dependent manner, while not affecting the expression of enzymes involved in PGE(2) metabolism. Investigations employing receptor antagonists and small interfering RNA revealed that this occurred through estrogen receptor α. Accordingly, LXA(4) treatment inhibited extracellular PGE(2) release. CONCLUSION(S): We report for the first time that MRP4 is expressed in human endometrium, elevated in peritoneal endometriosis, and modulated by LXA(4) in endometriotic epithelial cells.

Molecular design of the Calphabeta interface favors specific pairing of introduced TCRalphabeta in human T cells.

A promising approach to adoptive transfer therapy of tumors is to reprogram autologous T lymphocytes by TCR gene transfer of defined Ag specificity. An obstacle, however, is the undesired pairing of introduced TCRalpha- and TCRbeta-chains with the endogenous TCR chains. These events vary depending on the individual endogenous TCR and they not only may reduce the levels of cell surface-introduced TCR but also may generate hybrid TCR with unknown Ag specificities. We show that such hybrid heterodimers can be generated even by the pairing of human and mouse TCRalpha- and TCRbeta-chains. To overcome this hurdle, we have identified a pair of amino acid residues in the crystal structure of a TCR that lie at the interface of associated TCR Calpha and Cbeta domains and are related to each other by both a complementary steric interaction analogous to a "knob-into-hole" configuration and the electrostatic environment. We mutated the two residues so as to invert the sense of this interaction analogous to a charged "hole-into-knob" configuration. We show that this inversion in the CalphaCbeta interface promotes selective assembly of the introduced TCR while preserving its specificity and avidity for Ag ligand. Noteworthily, this TCR modification was equally efficient on both a Mu and a Hu TCR. Our data suggest that this approach is generally applicable to TCR independently of their Ag specificity and affinity, subset distribution, and species of origin. Thus, this strategy may optimize TCR gene transfer to efficiently and safely reprogram random T cells into tumor-reactive T cells.

SwissBioisostere: a database of molecular replacements for ligand design.

The SwissBioisostere database (http://www.swissbioisostere.ch) contains information on molecular replacements and their performance in biochemical assays. It is meant to provide researchers in drug discovery projects with ideas for bioisosteric modifications of their current lead molecule, as well as to give interested scientists access to the details on particular molecular replacements. As of August 2012, the database contains 21 293 355 datapoints corresponding to 5 586 462 unique replacements that have been measured in 35 039 assays against 1948 molecular targets representing 30 target classes. The accessible data were created through detection of matched molecular pairs and mining bioactivity data in the ChEMBL database. The SwissBioisostere database is hosted by the Swiss Institute of Bioinformatics and available via a web-based interface.

EADock : design of a new molecular docking algorithm and some of its applications

3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with .the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best-ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.

Docking, virtual high throughput screening and in silico fragment-based drug design.

ABSTRACT The drug discovery process has been profoundly changed recently by the adoption of computational methods helping the design of new drug candidates more rapidly and at lower costs. In silico drug design consists of a collection of tools helping to make rational decisions at the different steps of the drug discovery process, such as the identification of a biomolecular target of therapeutical interest, the selection or the design of new lead compounds and their modification to obtain better affinities, as well as pharmacokinetic and pharmacodynamic properties. Among the different tools available, a particular emphasis is placed in this review on molecular docking, virtual high throughput screening and fragment-based ligand design.

SwissSidechain: a molecular and structural database of non-natural sidechains.

Amino acids form the building blocks of all proteins. Naturally occurring amino acids are restricted to a few tens of sidechains, even when considering post-translational modifications and rare amino acids such as selenocysteine and pyrrolysine. However, the potential chemical diversity of amino acid sidechains is nearly infinite. Exploiting this diversity by using non-natural sidechains to expand the building blocks of proteins and peptides has recently found widespread applications in biochemistry, protein engineering and drug design. Despite these applications, there is currently no unified online bioinformatics resource for non-natural sidechains. With the SwissSidechain database (http://www.swisssidechain.ch), we offer a central and curated platform about non-natural sidechains for researchers in biochemistry, medicinal chemistry, protein engineering and molecular modeling. SwissSidechain provides biophysical, structural and molecular data for hundreds of commercially available non-natural amino acid sidechains, both in l- and d-configurations. The database can be easily browsed by sidechain names, families or physico-chemical properties. We also provide plugins to seamlessly insert non-natural sidechains into peptides and proteins using molecular visualization software, as well as topologies and parameters compatible with molecular mechanics software.

Application de la modélisation moléculaire à de nouvelles approches thérapeutiques du cancer [Application of molecular modeling to new therapeutic cancer approaches].

Recent progress in the experimental determination of protein structures allow to understand, at a very detailed level, the molecular recognition mechanisms that are at the basis of the living matter. This level of understanding makes it possible to design rational therapeutic approaches, in which effectors molecules are adapted or created de novo to perform a given function. An example of such an approach is drug design, were small inhibitory molecules are designed using in silico simulations and tested in vitro. In this article, we present a similar approach to rationally optimize the sequence of killer T lymphocytes receptors to make them more efficient against melanoma cells. The architecture of this translational research project is presented together with its implications both at the level of basic research as well as in the clinics.

A long, naturally presented immunodominant epitope from NY-ESO-1 tumor antigen: implications for cancer vaccine design.

The tumor antigen NY-ESO-1 is a promising cancer vaccine target. We describe here a novel HLA-B7-restricted NY-ESO-1 epitope, encompassing amino acids 60-72 (APRGPHGGAASGL), which is naturally presented by melanoma cells. The tumor epitope bound to HLA-B7 by bulging outward from the peptide-binding cleft. This bulged epitope was not an impediment to T-cell recognition, however, because four of six HLA-B7(+) melanoma patients vaccinated with NY-ESO-1 ISCOMATRIX vaccine generated a potent T-cell response to this determinant. Moreover, the response to this epitope was immunodominant in three of these patients and, unlike the T-cell responses to bulged HLA class I viral epitopes, the responding T cells possessed a remarkably broad TCR repertoire. Interestingly, HLA-B7(+) melanoma patients who did not receive the NY-ESO-1 ISCOMATRIX vaccine rarely generated a spontaneous T-cell response to this cryptic epitope, suggesting a lack of priming of such T cells in the natural anti-NY-ESO-1 response, which may be corrected by vaccination. Together, our results reveal several surprising aspects of antitumor immunity and have implications for cancer vaccine design.

Molecular imaging by micro-CT: specific E-selectin imaging.

The primary goal of this study was to design a fluorescent E-selectin-targeted iodine-containing liposome for specific E-selectin imaging with the use of micro-CT. The secondary goal was to correlate the results of micro-CT imaging with other imaging techniques with cellular resolution, i.e., confocal and intravital microscopy. E-selectin-targeted liposomes were tested on endothelial cells in culture and in vivo in HT-29 tumor-bearing mice (n = 12). The liposomes contained iodine (as micro-CT contrast medium) and fluorophore (as optical contrast medium) for confocal and intravital microscopy. Optical imaging methods were used to confirm at the cellular level, the observations made with micro-CT. An ischemia-reperfusion model was used to trigger neovessel formation for intravital imaging. The E-selectin-targeted liposomes were avidly taken up by activated endothelial cells, whereas nontargeted liposomes were not. Direct binding of the E-selectin-targeted liposomes was proved by intravital microscopy, where bright spots clearly appeared on the activated vessels. Micro-CT imaging also demonstrated accumulation of the targeted lipsomes into subcutaneous tumor by an increase of 32 +/- 8 HU. Hence, internalization by activated endothelial cells was rapid and mediated by E-selectin. We conclude that micro-CT associated with specific molecular contrast agent is able to detect specific molecular markers on activated vessel walls in vivo.

Separating the contribution of glucocorticoids and wakefulness to the molecular and electrophysiological correlates of sleep homeostasis.

Study Objectives: The sleep-deprivation-induced changes in delta power, an electroencephalographical correlate of sleep need, and brain transcriptome profiles have importantly contributed to current hypotheses on sleep function. Because sleep deprivation also induces stress, we here determined the contribution of the corticosterone component of the stress response to the electrophysiological and molecular markers of sleep need in mice. Design: N/A Settings: Mouse sleep facility. Participants: C57BL/6J, AKR/J, DBA/2J mice. Interventions: Sleep deprivation, adrenalectomy (ADX). Measurements and Results: Sleep deprivation elevated corticosterone levels in 3 inbred strains, but this increase was larger in DBA/2J mice; i.e., the strain for which the rebound in delta power after sleep deprivation failed to reach significance. Elimination of the sleep-deprivation-associated corticosterone surge through ADX in DBA/2J mice did not, however, rescue the delta power rebound but did greatly reduce the number of transcripts affected by sleep deprivation. Genes no longer affected by sleep deprivation cover pathways previously implicated in sleep homeostasis, such as lipid, cholesterol (e.g., Ldlr, Hmgcs1, Dhcr7, -24, Fkbp5), energy and carbohydrate metabolism (e.g., Eno3, G6pc3, Mpdu1, Ugdh, Man1b1), protein biosynthesis (e.g., Sgk1, Alad, Fads3, Eif2c2, -3, Mat2a), and some circadian genes (Per1, -3), whereas others, such as Homer1a, remained unchanged. Moreover, several microRNAs were affected both by sleep deprivation and ADX. Conclusions: Our findings indicate that corticosterone contributes to the sleep-deprivation-induced changes in brain transcriptome that have been attributed to wakefulness per se. The study identified 78 transcripts that respond to sleep loss independent of corticosterone and time of day, among which genes involved in neuroprotection prominently feature, pointing to a molecular pathway directly relevant for sleep function.

Design of potent inhibitors of human RAD51 recombinase based on BRC motifs of BRCA2 protein: modeling and experimental validation of a chimera peptide.

We have previously shown that a 28-amino acid peptide derived from the BRC4 motif of BRCA2 tumor suppressor inhibits selectively human RAD51 recombinase (HsRad51). With the aim of designing better inhibitors for cancer treatment, we combined an in silico docking approach with in vitro biochemical testing to construct a highly efficient chimera peptide from eight existing human BRC motifs. We built a molecular model of all BRC motifs complexed with HsRad51 based on the crystal structure of the BRC4 motif-HsRad51 complex, computed the interaction energy of each residue in each BRC motif, and selected the best amino acid residue at each binding position. This analysis enabled us to propose four amino acid substitutions in the BRC4 motif. Three of these increased the inhibitory effect in vitro, and this effect was found to be additive. We thus obtained a peptide that is about 10 times more efficient in inhibiting HsRad51-ssDNA complex formation than the original peptide.

Social meets molecular: Combining phylogenetic and latent class analyses to understand HIV-1 transmission in Switzerland.

Switzerland has a complex human immunodeficiency virus (HIV) epidemic involving several populations. We examined transmission of HIV type 1 (HIV-1) in a national cohort study. Latent class analysis was used to identify socioeconomic and behavioral groups among 6,027 patients enrolled in the Swiss HIV Cohort Study between 2000 and 2011. Phylogenetic analysis of sequence data, available for 4,013 patients, was used to identify transmission clusters. Concordance between sociobehavioral groups and transmission clusters was assessed in correlation and multiple correspondence analyses. A total of 2,696 patients were infected with subtype B, 203 with subtype C, 196 with subtype A, and 733 with recombinant subtypes (mainly CRF02_AG and CRF01_AE). Latent class analysis identified 8 patient groups. Most transmission clusters of subtype B were shared between groups of gay men (groups 1-3) or between the heterosexual groups "heterosexual people of lower socioeconomic position" (group 4) and "injection drug users" (group 8). Clusters linking homosexual and heterosexual groups were associated with "older heterosexual and gay people on welfare" (group 5). "Migrant women in heterosexual partnerships" (group 6) and "heterosexual migrants on welfare" (group 7) shared non-B clusters with groups 4 and 5. Combining approaches from social and molecular epidemiology can provide insights into HIV-1 transmission and inform the design of prevention strategies.

Molecular modeling study of the binding and signaling properties of the TCRpMHC complex

The activation of the specific immune response against tumor cells is based on the recognition by the CD8+ Cytotoxic Τ Lymphocytes (CTL), of antigenic peptides (p) presented at the surface of the cell by the class I major histocompatibility complex (MHC). The ability of the so-called T-Cell Receptors (TCR) to discriminate between self and non-self peptides constitutes the most important specific control mechanism against infected cells. The TCR/pMHC interaction has been the subject of much attention in cancer therapy since the design of the adoptive transfer approach, in which Τ lymphocytes presenting an interesting response against tumor cells are extracted from the patient, expanded in vitro, and reinfused after immunodepletion, possibly leading to cancer regression. In the last decade, major progress has been achieved by the introduction of engineered lypmhocytes. In the meantime, the understanding of the molecular aspects of the TCRpMHC interaction has become essential to guide in vitro and in vivo studies. In 1996, the determination of the first structure of a TCRpMHC complex by X-ray crystallography revealed the molecular basis of the interaction. Since then, molecular modeling techniques have taken advantage of crystal structures to study the conformational space of the complex, and understand the specificity of the recognition of the pMHC by the TCR. In the meantime, experimental techniques used to determine the sequences of TCR that bind to a pMHC complex have been used intensively, leading to the collection of large repertoires of TCR sequences that are specific for a given pMHC. There is a growing need for computational approaches capable of predicting the molecular interactions that occur upon TCR/pMHC binding without relying on the time consuming resolution of a crystal structure. This work presents new approaches to analyze the molecular principles that govern the recognition of the pMHC by the TCR and the subsequent activation of the T-cell. We first introduce TCRep 3D, a new method to model and study the structural properties of TCR repertoires, based on homology and ab initio modeling. We discuss the methodology in details, and demonstrate that it outperforms state of the art modeling methods in predicting relevant TCR conformations. Two successful applications of TCRep 3D that supported experimental studies on TCR repertoires are presented. Second, we present a rigid body study of TCRpMHC complexes that gives a fair insight on the TCR approach towards pMHC. We show that the binding mode of the TCR is correctly described by long-distance interactions. Finally, the last section is dedicated to a detailed analysis of an experimental hydrogen exchange study, which suggests that some regions of the constant domain of the TCR are subject to conformational changes upon binding to the pMHC. We propose a hypothesis of the structural signaling of TCR molecules leading to the activation of the T-cell. It is based on the analysis of correlated motions in the TCRpMHC structure. - L'activation de la réponse immunitaire spécifique dirigée contre les cellules tumorales est basée sur la reconnaissance par les Lymphocytes Τ Cytotoxiques (CTL), d'un peptide antigénique (p) présenté à la suface de la cellule par le complexe majeur d'histocompatibilité de classe I (MHC). La capacité des récepteurs des lymphocytes (TCR) à distinguer les peptides endogènes des peptides étrangers constitue le mécanisme de contrôle le plus important dirigé contre les cellules infectées. L'interaction entre le TCR et le pMHC est le sujet de beaucoup d'attention dans la thérapie du cancer, depuis la conception de la méthode de transfer adoptif: les lymphocytes capables d'une réponse importante contre les cellules tumorales sont extraits du patient, amplifiés in vitro, et réintroduits après immunosuppression. Il peut en résulter une régression du cancer. Ces dix dernières années, d'importants progrès ont été réalisés grâce à l'introduction de lymphocytes modifiés par génie génétique. En parallèle, la compréhension du TCRpMHC au niveau moléculaire est donc devenue essentielle pour soutenir les études in vitro et in vivo. En 1996, l'obtention de la première structure du complexe TCRpMHC à l'aide de la cristallographie par rayons X a révélé les bases moléculaires de l'interaction. Depuis lors, les techniques de modélisation moléculaire ont exploité les structures expérimentales pour comprendre la spécificité de la reconnaissance du pMHC par le TCR. Dans le même temps, de nouvelles techniques expérimentales permettant de déterminer la séquence de TCR spécifiques envers un pMHC donné, ont été largement exploitées. Ainsi, d'importants répertoires de TCR sont devenus disponibles, et il est plus que jamais nécessaire de développer des approches informatiques capables de prédire les interactions moléculaires qui ont lieu lors de la liaison du TCR au pMHC, et ce sans dépendre systématiquement de la résolution d'une structure cristalline. Ce mémoire présente une nouvelle approche pour analyser les principes moléculaires régissant la reconnaissance du pMHC par le TCR, et l'activation du lymphocyte qui en résulte. Dans un premier temps, nous présentons TCRep 3D, une nouvelle méthode basée sur les modélisations par homologie et ab initio, pour l'étude de propriétés structurales des répertoires de TCR. Le procédé est discuté en détails et comparé à des approches standard. Nous démontrons ainsi que TCRep 3D est le plus performant pour prédire des conformations pertinentes du TCR. Deux applications à des études expérimentales des répertoires TCR sont ensuite présentées. Dans la seconde partie de ce travail nous présentons une étude de complexes TCRpMHC qui donne un aperçu intéressant du mécanisme d'approche du pMHC par le TCR. Finalement, la dernière section se concentre sur l'analyse détaillée d'une étude expérimentale basée sur les échanges deuterium/hydrogène, dont les résultats révèlent que certaines régions clés du domaine constant du TCR sont sujettes à un changement conformationnel lors de la liaison au pMHC. Nous proposons une hypothèse pour la signalisation structurelle des TCR, menant à l'activation du lymphocyte. Celle-ci est basée sur l'analyse des mouvements corrélés observés dans la structure du TCRpMHC.