The availability of completely sequenced genomes for a number of organisms provides an opportunity to understand the molecular basis of physiology, metabolism, regulation and evolution of these organisms. Significant understanding of the complexity of organisms can be obtained from the functional characterization of repertoire of proteins encoded in their genomes. Computational approaches for recognition of function of proteins of unknown function encoded in genomes often rely on ability to detect well characterized homologues. Homology searches based on pair-wise sequence comparisons can reliably detect homologues with sequence identity more than 30%. However, detecting homologues characterized by sequence identity below 30% is difficult using these methods. Distant homology relationship can be established using profiles or position specific scoring matrices, which encapsulate information about structurally and functionally conserved residues. These conserved residues imply high constraints at a particular amino acid residue site due to their involvement in structural stability, enzymatic activity, ligand binding, protein folding or protein–protein interactions. In addition, information on three dimensional structures of proteins also aid in detection of remote homologues, as tertiary structures of proteins are conserved better than the primary structures of proteins. The gross objective of the work reported in this thesis is to employ various sensitive remote homology detection methods to recognize relevant functional information of proteins encoded mainly in pathogenic organisms. Since proteins do not work in isolation in a cell, it has become essential to understand the in vivo context of functions of proteins. For this purpose, it is essential to have an understanding of all molecules that interact with a particular protein. Thus, another major area of bioinformatics has been to integrate protein-protein interaction information to enable better understanding of context of functional events. Protein-protein interaction analysis for host-pathogen can lead to useful insight into mode of pathogenesis and subsequent consequences in host cell. Chapters 2-6 of the thesis discuss the sequence and structural characteristics along with remote evolutionary relationships and functional implications of uncharacterized proteins encoded in genomes of following pathogens: Helicobacter pylori, Plasmodium falciparum and Leishmania donovani. The Chapters 6-8 discuss mainly various sequence, structural and functional aspects of protein kinases encoded in genomes of various prokaryotes and viruses. Chapter 1 discusses background information and literature survey in the areas of homology detection and prediction of protein-protein interactions. The growth of genomic data and need for processing genomic data to infer context of various functional events have been highlighted. Different approaches to recognize functions of proteins (experimental as well as computational) have been discussed. Various experimental and computational approaches to detect/predict protein-protein interactions have been mentioned. Chapter 2 discusses recognition of non-trivial remote homology relationships involving proteins of Helicobacter pylori and their implications for function recognition. H. pylori is microaerophilic, Gram negative bacterial pathogen. It colonizes human gastric mucosa and is a causative agent of gastroduodenal disease. The pathogen infects about 50% of the human population. It can lead to development of Mucosa-associated lymphoid tissue lymphoma. About 10% of the infected population develop gastric or duodenal ulcer and approximately 1% develop gastric cancer. H. pylori has been classified as class I carcinogen by WHO. Pathogen is characterized by type IV secretion system. The complete genomic sequences of three widely studied strains including 26695, J99 and HPAG1 of Helicobacter pylori are available. According to the genome analysis, the number of predicted open reading frames in strain 26695, J99 and HPAG1 are 1590, 1495 and 1536 respectively. Out of predicted H. pylori proteins from 26695, J99 and HPAG1 strains, numbers of proteins with no functional domain assignments in Pfam database (Protein family database) are 453, 357 and 400 respectively. There are proteins in different strains of H. pylori genomes where one part of the protein is associated with at least one protein domain of known function and hence preliminary indication of their functions is available whereas rest of the region is not associated with any function. There are 772, 803 and 790 such segments in proteins from strains 26695, J99 and HPAG1 respectively with at least 45 residues with no functional assignment currently available. Sensitive remote homology detection methods have been employed to establish relationships for 294 amino acid sequences and results have been grouped into 4 categories. Results of homology detection have been further confirmed by studying conservation of amino acid residues which are important for functioning of the proteins concerned. (i) Remote relationship has been established involving protein domain families for which no bonafide member is currently known in H. pylori. For example: DNA binding protein domain (Kor_B) has been assigned to a H. pylori protein at sequence identity of 20%. Study involving secondary structure prediction and conservation of amino acid residues confirms the results of homology detection methods. (ii) Remote relationship has been established involving H. pylori hypothetical proteins and protein domain families, for which paralogous members are present in Helicobacter pylori. For example, Cytochrome_C, an electron transfer protein domain could be associated with a Helicobacter pylori protein sequence which shows a sequence identity of 14% with sequences of bonafide cytochrome C. (iii) “Missing” metabolic proteins of H. pylori have also been recognized. For example, Aspartoacylase (EC 3.5.1.15) catalyzes deacetylation of N-acetylaspartic acid to produce acetate and L-aspartate. This enzyme in aspartate metabolism pathway has not been reported so far from H. pylori. A remote evolutionary relationship between a H. pylori protein and Aspartoacylase domain has been established at sequence identity of 17% thus filling the gap in this metabolic pathway in the pathogen. (iv) New functional assignments for domains in H. pylori sequences with prior assignment of domains for the rest of the sequences have been made. For example, DNA methylase domain has been assigned to C-terminal region of H. pylori protein which already had Helicase domain assigned to the N-terminal region of the protein. All these information should open avenues for further probing by carrying out experiments which will impact the design of inhibitor against this pathogen and will result in better understanding of pathogenesis of this organism in human. Chapter 3 describes prediction of protein–protein interactions between Helicobacter pylori and the human host. A lack of information on protein-protein interactions at the host-pathogen interface is impeding the understanding of the pathogenesis process. A recently developed, homology search-based method to predict protein-protein interactions is applied to the gastric pathogen, Helicobacter pylori to predict the interactions between proteins of H. pylori and human proteins in vitro. Many of the predicted interactions could potentially occur between the pathogen and its human host during pathogenesis as we focused mainly on the H. pylori proteins that have a transmembrane region or are encoded in the pathogenic island and those which are known to be secreted into the human host. By applying the homology search approach to protein-protein interaction databases DIP and iPfam, in vitro interactions for a total of 623 H. pylori proteins with 6559 human proteins could be predicted. The predicted interactions include 549 hypothetical proteins of as yet unknown function encoded in the H. pylori genome and 13 experimentally verified secreted proteins. A total of 833 interactions involving the extracellular domains of transmembrane proteins of H. pylori could be predicted. Structural analysis of some of the examples reveals that the predicted interactions are consistent with the structural compatibility of binding partners. Various probable interactions with discernible biological relevance are discussed in this chapter. For example, interaction between CFTR protein (NP_000483) and multidrug resistance protein (HP1206) has been predicted. The structure of the CFTR intracellular domain is known in the homomeric form and consists of five AAA transport domains in tandem (PDB code 1XMI). Out of the five identical subunits, two subunits (the B chain and the E chain in the PDB structure) have been selected. The structure of multidrug resistance protein of the pathogen based on the B chain (sequence identity 32%) of the template has been modeled. This exercise suggests that interface residues in the model are congenial for interaction. This makes the structural complex feasible in in vitro conditions and suggests that the pathogen protein may compete for occupancy with the host protein. Chapter 4 describes recognition of Plasmodium-specific protein domain families and their roles in Plasmodium falciparum life cycle. Malaria in humans is caused by the parasites of intracellular, eukaryotic protozoan of apicomplexan nature belonging to the genus Plasmodium. Out of five species of Plasmodium, namely, P. falciparum, P. ovale, P. vivax, P. malariae and P. knowlesi which infects human, P. falciparum causes lethal infection. P. falciparum proteins have diverged extensively during the course of evolution. Pathogen genome is rich in A+T composition which larger than the homologous proteins from other organisms due to presence of low complexity regions. Organism specific families are important as they play roles in peculiar life style of an organism. If the organism is a pathogen, then these family members may play roles in pathogenesis. Inhibiting these specific proteins is unlikely to interfere with host system as no homolog may be present in host. In the present work we identify Plasmodium specific protein families and their role in different stages of life cycle of the pathogen. A total of 5086 amino acid sequences (full length sequences/fragments of proteins) show homology only with amino acid sequences from Plasmodium organisms and hence are Plasmodium-specific. These Plasmodium-specific amino acid sequences cluster into 106 Plasmodium-specific families (≥2 members per family). 14 Plasmodium-specific protein domain families with known physico-chemical properties are observed. These Plasmodium-specific protein domain families are involved in various important functions such as rosetting and sequestering of infected erythrocytes, binding to surface of host cell and invasion process in life cycle of pathogen. Also, 89 new Plasmodium-specific protein domain families have been recognized. Analysis of various aspects of members of Plasmodium-specific proteins domain families such as their potential to target apicoplast, protein-protein interaction, expression profile and domain organization has been performed to derive relevant information about function. New Plasmodium specific domain families for which no function can be associated could provide some insight into much diverged Plasmodium species. These proteins may play role in parasite-specific life style. Experimental work on these Plasmodium-specific proteins might fill the gaps of less understood physiology of this parasite. Chapter 5 presents genome-wide compilation of low complexity regions (LCR) in proteins. An indepth analysis of the nature, structure, and functional role of the proteins containing low complexity regions in Plasmodium falciparum, was undertaken given the high prevalence of LCRs in the proteome of this organism. Low complexity regions and repeat patterns have been recognized in proteins encoded in 986 genomes (68 archaea, 896 prokaryotes and 22 eukaryotes). Low complexity regions have been classified into following three categories: a) Composition of LCRs: (i) LCRs can be stretches of homo amino acid residues (ii) LCRs can be stretches of more than one amino acid residue type b) Periodicity of amino acids in LCRs: Certain amino acid residues can be observed at certain specific periodicity in proteins. c) Repeat patterns: Certain motif of amino acid residues are repeated in protein. 850 Plasmodium falciparum proteins are observed to have at least one repeat pattern where the repeating unit is at least 5 amino acid residues long. Statistical analysis on single amino acid residue repeats indicate that occurrence of stretches of homo amino acid residues is not a random event. Studies on recognition of functions, protein protein interactions and organization of tethered domain(s) in proteins containing LCR suggest that these proteins are part of variety of functional events such as signal transduction, enzymatic processes, cell differentiation, pyrimidine biosynthesis, fatty acid biosynthesis and chromosomal replication. Representations of low complexity regions of Plasmodium falciparum in protein data bank suggest that LCRs can take conformation of regular secondary structure (apart from disordered regions) in 3-D structures of proteins. Chapter 6 describes sequence analysis, structural modeling and evolutionary studies of Leishmania donovani hypusine pathway enzymes. Leishmania is an eukaryotic kinetoplastid protozoan parasite which causes leishmaniasis in humans. Hypusine is a non standard polyaminederived amino acid Nε-(4-amino-2-hydroxybutyl) lysine and is named after its two structural components, hydroxyputrescine and lysine. The eukaryotic translation initiation factor 5A (eIF5A) is the only cellular protein containing hypusine. Synthesis of hypusine is critical for the function of elF5A and is essential for eukaryotic cell proliferation and survival. Formation of hypusine is the result of a two step post-translational modification process involving enzymes (i) deoxyhypusine synthase (DHS) (ii) deoxyhypusine hydroxylase (DOHH). DHS, the first enzyme involved in hypusine pathway catalyzes the NAD-dependent transfer of the butylamino moiety of spermidine (substrate) to the ε-amino group of a specific lysine residue of eIF5A precursor and generates deoxyhypusine containing intermediate. DOHH, the second enzyme in same pathway catalyzes the hydroxylation of deoxyhypusine-containing intermediate, generating hypusine-containing mature eIF5A. Two putative deoxyhypusine synthase (DHS) sequences DHS34 and DHS20 have been identified in Leishmania donovani, by Professor Madhubala and coworkers (Jawaharlal Nehru University, New Delhi) with whom the work embodied in this chapter was done in collaboration. Detailed comparison of DHS34 sequence from Leishmania with human DHS protein indicated conservation of functionally important residues. 3D structural modeling studies of protein suggested that residues around the active site were absolutely conserved. NAD binding regions are located spatially closer, however, one NAD binding region was observed in a large (225 amino acid residues long) insertion. Based on these observations, DHS34 was predicted to have enzymatic activity. Experimental studies done by our collaborators confirmed preliminary results of computational analysis. Based on sequence and structural analysis of DHS20 and DOHH proteins, DHS20 and DOHH were proposed to be catalytically inactive and active respectively. Experimental studies on these proteins supported results of computational analysis. Deoxyhypusine synthase (DHS) and Deoxyhypusine hydroxylase (DOHH) are key proteins conserved in the hypusine synthesis pathways of eukaryotes. Because they are highly conserved, they could be coevolving. Comparison of the genetic distance matrices of DHS and DOHH proteins reveals that their evolutionary rates are better correlated when compared to the rate of an unrelated protein such as Cytochrome C. This indicates that they are coevolving, further serving as an indicator that, even non-interacting proteins that are functionally coupled, experience correlated evolution. However, this correlation does not extend to their tree topologies. Chapter 7 provides a classification scheme for protein kinases encoded in genomes of prokaryotic organisms. Overwhelming majority of the Ser/Thr protein kinases identified by gleaning archaeal and eubacterial genomes could not be classified into any of the well known Hanks and Hunter subfamilies of protein kinases. This is owing to the development of Hanks and Hunter classification scheme based on eukaryotic protein kinases which are highly divergent from their prokaryotic homologues. A large dataset of prokaryotic Ser/Thr protein kinases prokaryotic Ser/Thr protein kinases. Traditional sequence alignment and phylogenetic approaches have been used to identify and classify prokaryotic kinases which represent 72 subfamilies with at least 4 members in each. Such a clustering enables classification of prokaryotic Ser/Thr kinases and it can be used as a framework to classify newly identified prokaryotic Ser/Thr kinases. After series of searches in a comprehensive sequence databases, it is recognized that 38 subfamilies of prokaryotic protein kinases are associated to a specific taxonomic level. For example 4, 6 and 3 subfamilies have been identified that are currently specific to phylum proteobacteria, cyanobacteria and actinobacteria respectively. Similarly, subfamilies which are specific to an order, sub-order, class, family and genus have also been identified. In addition to these, it was also possible to identify organism-diverse subfamilies. Members of these clusters are from organisms of different taxonomic levels, such as archaea, bacteria, eukaryotes and viruses. Interestingly, occurrence of several taxonomic level specific subfamilies of prokaryotic kinases contrasts with classification of eukaryotic protein kinases in which most of the popular subfamilies of eukaryotic protein kinases occur diversely in several eukaryotes. Many prokaryotic Ser/Thr kinases exhibit a wide variety of modular organization which indicates a degree of complexity in protein-protein interactions and the signaling pathways in these microbes. Chapter 8 focuses on recognition, classification of protein kinases encoded in genomes of viruses and their implications in various functions and diseases. Protein kinases encoded by viral genomes play a major role in infection, replication and survival of viruses. Using traditional sequence homology detection tools, sequence alignment methods and phylogenetic approaches, protein kinases were recognized. 646123 protein sequences from 35799 viral genomes (including strains) have been used in this analysis. Protein kinases are identified using a combination of profile-based search methods such as PSI-BLAST, RPS-BLAST and HMMER approaches. Based upon sequence similarity over the length of catalytic kinase domains, 479 protein kinase domains recognized in 244 viral genomes have been clustered into 46 subfamilies with minimum sequence identity of 35% within a subfamily. Viral protein kinases are encoded in genomes of retro-transcribing viruses or viruses which possess double stranded DNA as genetic material. Based on the available functional information present for one or more members of a subfamily, a putative function has been assigned to other members of the subfamily. Information regarding interaction of viral protein kinases with viral/host protein has also been considered for enhancing understanding of function of kinases in a subfamily. Out of 46 subfamilies, 14 subfamilies are characterized by various functions. Kinases belonging to UL97, US69, UL13 and BGLF subfamilies are virus specific. For 7 subfamilies, nearest neighbors are from well characterized eukaryotic protein kinase groups such as AGC, CAMK and CDK. Out of 25 new uncharacterized subfamilies observed in this analysis, 13 subfamilies are virus specific. Different subfamilies have been characterized by various functions which are crucial for viral infection such as synthesis of structural unit, replication of genetic material, modification of cellular components, alteration in host immune system, competing with cellular protein for efficient usage of host machinery. Also, many viral kinases share very high sequence identity (~97%) with their eukaryotic counterpart and represent disease state. For example, a protein kinase encoded in Avian erythroblastosis virus shares 97% sequence identity with catalytic domain of human epidermal growth factor receptor tyrosine kinase. Leucine at position 861 in human protein is substituted by Gln in cancer conditions; the viral protein kinase sequence possesses Gln at corresponding position and thus represents disease state. Chapter 9 provides study of dependency on the ability of 3-D structural features of comparative models and crystal structures of inactive forms of enzymes to predict enzymes by considering protein kinases as case study. With the advent of structural genomics initiatives, there is a surge in the number of proteins with 3-D structural information even before functional features are understood on many of these proteins. One of the useful annotations of a protein is the demarcation of a protein into an enzyme or non-enzyme solely from the knowledge of 3-D structure. This is facilitated by the identification of active sites and ligand binding sites in a protein. In this work, which was carried out in collaboration with Dr Jim Warwicker of Manchester University, UK, an approach developed by Warwicker and coworkers has been used. In the 3D structure of proteins, the largest clefts are generally considered to be ligand binding sites. This feature along with other sequence alignment independent properties such as residue preferences, fraction of surface residues and secondary structure elements have been considered to differentiate enzymes from non-enzymes. Electrostatic potential at the active site is one of the key properties utilized in this respect. Active sites in enzymes are generally associated with ionizable groups which can take part in catalysis. In addition to the feature of large clefts in enzymes, active site residues are in buried environments and show larger deviation in pKa values than surface residues. The method proposed by Warwicker and co-workers distinguish proteins in to enzymes and non-enzymes considering the electrostatic features at clefts along with the sequence profile of the protein concerned. Conformation of the inactive state of an enzyme is not congenial to the catalytic function. In an ideal situation, a method should be capable of predicting an enzyme irrespective of whether determined structure corresponds to active or inactive state. Peak potential values have been calculated by using Warwicker program for a set of 15 protein kinases for which 3-D structures are present in active as well in inactive conformations. Comparison of peak potential values calculated for active and inactive conformations suggests that algorithm can differentiate between active and inactive conformations as value for active conformations are generally higher than corresponding values for inactive conformations. However, the peak potential values are high enough for even the inactive conformations to be predicted as enzyme. Peak potential values calculated for generated homology models of protein kinases (for which crystal structures are already available) at different sequence identities with template sequences predict protein kinases as enzymes and their peak potential values are comparable to corresponding values for X-ray structures. This suggests that proteins for which there are no crystal or NMR structures yet available and no good template with high sequence identity are present, peak potential values for models generated at low sequence identity can still give insight into probable function of protein as an enzyme. The enzyme/non-enzyme prediction algorithm was also found to be useful in confirming enzyme functionality using 3-D models of putative viral kinases. Initially, putative function of kinase has been assigned to these viral proteins based solely upon their sequence characteristics such as presence of residues/motifs which are important for activity of the protein. The enzyme recognition method which is not directly sensitive to these motifs confirmed that all the analyzed putative viral kinases are enzymes. Chapter 10 presents conclusions of work embodied in the entire thesis. Very briefly, various computational approaches have been used to analyze and understand structural and functional properties of repertoire of proteins of pathogenic organisms. Analysis of uncharacterized protein domain families has helped to understand the functional implications of constituent proteins. Experimental validation of these results can further facilitate unraveling of functional aspects of proteins encoded in various pathogenic organisms. Apart from studies embodied in the thesis, author has been involved in two other studies, which are provided as appendices. Appendix 1 describes comparison of substitution pattern of amino acid residues of protein encoded in P. falciparum genome with substitution pattern of corresponding homologous proteins from non-Plasmodium organisms. Salient differences have been highlighted. Appendix 2 discusses study of bacterial tyrosine kinases with an objective of recognition of all putative protein tyrosine kinases in E. coli. Computational study suggests that protein SopA can be a potential tyrosine kinase and this conclusion is being tested experimentally in collaborator’s laboratory.

Les oreillons sont une maladie très contagieuse causée par le virus ourlien. La méthode préventive (le vaccin) contre ce virus a été déjà mise au point. Par contre, les épidémies récentes restent incontrôlables. Il est donc très important de comprendre le mécanisme moléculaire de son cycle de vie afin d’élaborer le traitement effectif et spécifique. Ce virus appartient à la famille des Paramyxoviridae. Son génome, l’ARN non segmenté monocaténaire de polarité négative, est protégé par la nucléoprotéine (N) en formant des structures filamenteuses nucléocapsides. N joue un rôle essentiel dans la synthèse du génome viral. En effet, cette protéine avec la polymérase et son cofacteur phosphoprotéine (P) constitue la machinerie de transcription-réplication du virus. La N et la P sont composées des régions pliées et dépliées. Malgré que la morphologie du virus ourlien est conservée parmi les autres membres de la famille, il existe quelques différences. Il a été démontré que la P est un oligomère antiparallel avec les deux extrémités d’un côté qui interagissent avec la partie structurale de N (Ncore). Tandis que la fonction de la région désordonnée (Ntail) est compliquée à identifier pour le moment. En comparant avec les autres paramyxovirus connus, Ntail n’interagit pas avec le domaine C-terminal de la P. Le rôle des régions déstructurées de P n’a pas été défini. Dans ce projet, nous dévoilons les mécanismes des interactions entre diverses régions de N et P et nous expliquons comment les domaines intrinsèquement désordonnés de N et P sont impliqués dans la régulation de la machine complexe de réplication virale. Nous avons utilisé la résonance magnétique nucléaire qui est la méthode la plus puissante afin de déterminer la structure, la dynamique et les partenaires d’interaction dont la fonction des protéines dépliées virales. / Mumps is a highly contagious disease caused by the mumps virus. The prevention treatment (vaccine) against it is already in the routine use. However, recent outbreaks still remain uncontrollable. Therefore, it is important to understand the molecular mechanism of the mumps virus life cycle. This virus belongs to the family of Paramyxoviridae. Its genome, negative strand non-segmented RNA is protected by the nucleoprotein (N) by forming filamentous structures called nucleocapsids. N plays an important role in viral genome synthesis. Together with the polymerase and its cofactor phosphoprotein (P) they constitute the transcription-replication machinery. Both N and P contain folded and unfolded regions. Despite mumps virus common morphology with other paramyxovirus, there are some differences. It has been proposed that P is an antiparallel oligomer with two extremities on the one side being in interaction with the structural part of N (Ncore). The function of the disordered domain (Ntail) remains unclear, as it does not seem to bind to the C-terminal part of P, as is the case for other paramyxoviruses. The role of the disordered domains of P is also not known. In this project we revealed mechanisms of interaction between different regions of N and P and we explain how disordered regions of N and P are implicated in the regulation of the complex machinery of viral replication. We used the nuclear magnetic resonance which is the most powerful method to determine structure, dynamics and potential interaction partners, and therefore, function of disordered viral proteins.

Foot-and-mouth disease (FMD) is a highly contagious and economically important disease that affects even-toed hoofed mammals. The FMD virus (FMDV) is the causative agent of FMD, of which there are seven clinically indistinguishable serotypes. Three serotypes, namely, South African Territories (SAT)1, SAT2 and SAT3 are endemic to southern Africa and are the most antigenically diverse among the FMDV serotypes. A negative consequence of this antigenic variation is that infection or vaccination with one virus may not provide immune protection from other strains or it may only confer partial protection. The identification of B-cell epitopes is therefore key to rationally designing cross-reactive vaccines that recognize the immunologically distinct serotypes present within the population. Computational epitope prediction methods that exploit the inherent physicochemical properties of epitopes in their algorithms have been proposed as a cost and time-effective alternative to the classical experimental methods. The aim of this project is to employ in silico epitope prediction programmes to predict B-cell epitopes on the capsids of the SAT serotypes. Sequence data for 18 immunologically distinct SAT1, SAT2 and SAT3 strains from across southern Africa were collated. Since, only one SAT1 virus has had its structure elucidated by X-ray crystallography (PDB ID: 2WZR), homology models of the 18 virus capsids were built computationally using Modeller v9.12. They were then subjected to energy minimizations using the AMBER force field. The quality of the models was evaluated and validated stereochemically and energetically using the PROMOTIF and ANOLEA servers respectively. The homology models were subsequently used as input to two different epitope prediction servers, namely Discotope1.0 and Ellipro. Only those epitopes predicted by both programmes were defined as epitopes. Both previously characterised and novel epitopes were predicted on the SAT strains. Some of the novel epitopes are located on the same loops as experimentally derived epitopes, while others are located on a putative novel antigenic site, which is located close to the five-fold axis of symmetry. A consensus set of 11 epitopes that are common on at least 15 out of 18 SAT strains was collated. In future work, the epitopes predicted in this study will be experimentally validated using mutagenesis studies. Those found to be true epitopes may be used in the rational design of broadly reactive SAT vaccines / Life and Consumer Sciences / M. Sc. (Life Sciences)

Le virus de l’immunodéficience humaine de type 1 (VIH-1) est l’agent étiologique du SIDA, un rétrovirus complexe encodant les protéines accessoires : Nef, Vif, Vpr et Vpu. La fonction principale de ces protéines est de moduler l’environnement cellulaire afin de promouvoir la réplication virale. Les travaux présentés dans cette thèse portent sur la protéine virale Vpr, une protéine bien connue pour son activité d’arrêt du cycle cellulaire en phase G2/M dans les cellules en division et pour l’avantage réplicatif qu’elle confère au virus durant l’infection de cellules myéloïdes. Les évènements sous-jacents à ces deux activités restent pour l’heure mal compris. Le but des travaux regroupés dans cet ouvrage est d’identifier de nouveaux facteurs cellulaires pouvant éventuellement expliquer les activités de Vpr précédemment décrites. Pour ce faire, nous avons utilisé une approche d’identification des partenaires de proximité par biotinylation, appelée BioID. L’avantage du BioID est de permettre un marquage in cellulo des protéines à proximité de la protéine d’intérêt. La mise en place et la caractérisation de cette approche font l’objet de la première section de cette thèse. En utilisant cette approche, nous avons défini un réseau de 352 partenaires cellulaires de la protéine Vpr. Parmi ces partenaires de Vpr, plusieurs sont organisés sous forme de complexes ou réseaux protéiques incluant notamment le complexe promoteur de l’anaphase/cyclosome (APC/C) et les centrosomes. Étant donné que le complexe APC/C est l’un des principaux régulateurs du cycle cellulaire, nous avons décidé d’analyser sa relation avec Vpr. Nous avons découvert que Vpr formait un complexe non seulement avec APC1, une sous-unité essentielle du complexe APC/C, mais aussi avec les coactivateurs (CDH1 et CDC20) de ce complexe. Nous avons par la suite démontré que Vpr induisait la dégradation d’APC1 et que celle-ci pouvait être prévenue par une double-mutation N28S-G41N de Vpr. Cette dégradation d’APC1 ne semblerait pas être reliée aux activités précédemment décrites de Vpr. Ces travaux font l’objet de la seconde section de cette thèse. Enfin, dans une troisième section, des travaux effectués en collaboration et analysant la relation entre les centrosomes et Vpr sont présentés. Cette thèse identifie 200 nouveaux partenaires de Vpr, ouvrant la porte à l’exploration de nouvelles cibles et activités de Vpr. Elle décrit également une nouvelle cible de Vpr : le complexe APC/C. Globalement nos résultats contribuent à une meilleure compréhension de la façon dont le VIH-1 manipule l’environnement cellulaire de l’hôte à travers la protéine virale Vpr. / Human immunodeficiency virus (HIV-1) is the AIDS causal agent. This complex retrovirus encodes several accessory proteins; namely Nef, Vif, Vpr and Vpu; whose functions are to manipulate the cellular host environment in order to favor HIV-1 viral replication. This thesis focused on Vpr whose main activities are to induce a cell cycle arrest in the G2/M phase in dividing cells and to provide a replicative advantage to HIV-1 during infection of myeloid cells such as macrophages. The cellular mechanisms underlying these two activities are up to now misunderstood. The main goal of the work presented in this thesis is to identify new cellular factors that could potentially explain the previously described Vpr activities. To do so, we used the proximity labelling approach called BioID. The main strength of BioID is to tag in cellulo partners of the protein of interest. The development as well as optimization of the BioID approach is presented in the thesis first section. Using BioID, we defined a network containing 352 cellular partners in close proximity with the viral protein Vpr. Amongst these cellular partners, several were organized into protein complexes or networks such as the anaphase promoting complex/cyclosome (APC/C) or the centrosome. Given that APC/C is a cell cycle master-regulator, we analyzed the interplay governing Vpr and APC/C interactions. We first demonstrated that Vpr could form a complex containing the scaffolding subunit APC1. APC/C coactivators, namely CDH1 and CDC20, could also be found in association with Vpr. We next showed that Vpr was inducing APC1 degradation and that Vpr residues N28 and G41 were essential to this activity. Surprisingly, the APC1-Vpr interplay does not relate to previously described Vpr activities. This work is presented in the second section of this thesis. Lastly, in the third section, a work done in collaboration analyzed the interplay between Vpr and the centrosomes. In this thesis we identified 200 new potential partners of Vpr, opening the doors to discover novel Vpr targets and activities. This thesis also defined APC/C as new Vpr target. Taken together our results allow a better understanding on how HIV-1 modulates the cellular environment by using the viral accessory protein Vpr.