A cell’s ability to recognise and respond to changes in its environment is crucial to its survival. The availability of nutrients is a fundamental part of the environment, and so cells must be able to identify when they are plentiful and when they are scarce, and adapt accordingly. GCN2 is a key protein kinase within the eukaryotic proteome, and it is activated by a drop in the intracellular concentration of amino acids. When activated, GCN2 phosphorylates the translation initiation factor eIF2, initiating the Integrated Stress Response. This causes the global inhibition of protein synthesis and the upregulation of stress response pathways. GCN2 has been implicated in a wide range of cellular processes in health and diseases, including the development of pulmonary veno-occlusive disease, neurological degeneration and cancer. The molecular mechanisms that control the regulation and activation of GCN2 remain unclear. Some insights have been provided through genetic experiments on yeast, but the complexities of the regulatory pathways have made it difficult to decipher precise mechanistic details. For this reason, the aim of this project was to characterise the human GCN2 kinase both functionally and structurally, and to investigate the molecular mechanisms that enable it to act as a sensor of nutritional stress. This thesis describes the development of a system to reconstitute GCN2 activation using purified components, allowing the effects of different regulators to be tested and characterised. Insights from these data alongside structural insights into the kinase allow the proposal of a model concerning how GCN2 can sense amino acid deprivation in response to various regulatory signals. While GCN2 is activated by nutritional stress, mammalian cells have evolved a panoply of responses to environmental stress. Hsp90 is a chaperone that is required for the stability and maintenance of approximately 60 % of the human kinome, yet how it recognises client kinases is still unclear. The final chapter of this thesis describes the use of biochemical methods in combination with HDX-MS to characterise the interactions between Hsp90’s co-chaperone Cdc37 and client kinases. These analyses enabled the identification of a correlation between protein stability and dependence on Hsp90/Cdc37, and revealed that Cdc37 binding causes a dramatic conformational remodelling of the N-lobe of the kinase.

Enzyme structure dynamics has recently been revealed to be essential for structure-function relationship. Among various structure dynamics analysis platforms, hydrogen deuterium exchange mass spectrometry stands as an efficient and high-throughput way to analyze protein dynamics upon ligand binding, protein folding, and enzyme catalysis. HDX-MS can be used to study the regional dynamics of proteins based on the m/z value or percentage of deuterium incorporation for the digested peptides in the HDX experiments. Various software packages have been developed to analyze HDX-MS data. However, for the accurate, enhanced, and explicit statistical analysis of HDX-MS data statistical analysis of software was developed as HDXanalyzer. The capability of HDX-MS analysis for the identification of enzyme structure dynamics was tested by using model catalysis endoxylanase A (XYN I) from Trichoderma longibrachiatum. The HDX data of XYN I revealed a highly dynamic personality of XYN I through the interaction with two substrates. The dynamic data which certainly restricts the targeted regions for the protein engineering efforts provided useful knowledge about the essential structural modifications for the catalysis of XYN I. The obtained knowledge was then employed for the engineering studies in order to improve the certain characteristics of XYN I protein. The high level stabilization of XYN I protein was gathered and the two highly active and moderately thermostable XYN I recombinants were developed based on the HDX-MS data which further confirmed the efficiency of the current strategy for the rational designs of catalytic proteins. A differential dynamics analysis of the two structurally similar catalysts was also performed through HDX-MS. The functionally and sequentially different but structurally highly similar XYN I and endoglucanase (Eg1A) enzymes revealed distinct structure dynamic characteristics. Compared to XYN I, Eg1A from Aspergillus niger indicated quite restricted structural motions. The data clearly postulated that the intrinsic dynamic modifications of during the enzymatic catalysis may not be the only driving force in all cases. In summary, the integration of the structure dynamics knowledge to the current biochemical and biophysical data of catalysts may provide novel insights to further enzyme improvement applications.

Phylum Apicomplexa comprises several thousand parasitic protozoans that cause significant disease in humans and animals worldwide. Of particular relevance to human health are Plasmodium spp., the causative agents of malaria; and Toxoplasma gondii, which infects approximately 30% of all humans on earth, and causes serious disease in immunocompromised individuals and neonatally infected fetuses. Central to the pathogenesis of apicomplexans is a unique form of substrate-dependent locomotion termed “gliding motility”, which is essential for traversing the environment and actively invading host cells. Driving motility is the class-XIV unconventional myosin motor (MyoA), which is notably divergent from canonical myosins in that it lacks a “tail” and conventional sequence motifs in both the neck and motor regions. Thus, the mechanisms that enable MyoA to function with a step size and velocity similar to canonical human myosins are not well understood. Over the past 2 decades, the apicomplexan research community has identified many of the components involved in gliding motility, resulting in a functional model of MyoA and accessory proteins forming the “glideosome” macromolecular complex. However, there was still relatively little known about the unique physical processes that drive force production and transduction in the apicomplexan motor complex. Thus, I set out to use structural and biophysical methods to interrogate this divergent molecular motor, and provide the first high-resolution model of apicomplexan motility. Towards this goal, I first used structural and biophysical methods to establish the most complete model to date of class-XIV motor complex assembly, answering key questions about the interface between MyoA and its accessory proteins. To understand the unique molecular basis of force production in apicomplexan motors, I then solved the first ever crystal structure of a class-XIV myosin, MyoA from T. gondii. Supplementing this structure with further biophysical data, I was able to determine the functional consequences of class-defining sequence polymorphisms, and elucidate the basis of phosphorylation-dependent motor regulation. The systematic dissection of apicomplexan motor complexes described herein provides crucial insight into a fundamental biological process, and may help overcome existing barriers for targeted therapeutic development. / Graduate

No description available.

Molecular dynamics (MD) simulation is a powerful tool enabling researchers to gain insight into biological processes at the atomic level. There have been many advancements in both hardware and software in the last decade to both accelerate MD simulations and increase their predictive accuracy; however, MD simulations are typically limited to the microsecond timescale, whereas biological motions can take seconds or longer. Because of this, it remains extremely challenging to restrain simulations using ensemble-averaged experimental observables. Among various approaches to elucidate the kinetics of molecular simulations, Markov State Models (MSMs) have proven their ability to extract both kinetic and thermodynamic properties of long-timescale motions using ensembles of shorter MD simulation trajectories. In this dissertation, we have implemented an MSM path-entropy method, based on the idea of maximum-caliber, to efficiently predict the changes in protein folding behavior upon mutation. Next, we explore the accuracy of different MSM estimators applied to trajectory data obtained by adaptive seeding, in which new rounds of short MD simulations are collected from states of interest, and propose a simple method to build accurate models by population re-weighting of the transition count matrix. Finally, we explore ways to reconcile simulated ensembles with Hydrogen/Deuterium exchange (HDX) protection measurements, by constructing multi-ensemble Markov State Models (MEMMs) from biased MD simulations, and reconciling these predictions against the experimental data using the BICePs (Bayesian Inference of Conformational Populations) algorithm. We apply this approach to model the native-state conformational ensemble of apomyoglobin at neutral pH. / Chemistry

Ce travail de thèse porte sur le développement de méthodes de spectrométrie de masse (MS) structurale pour la caractérisation de systèmes protéiques complexes, souvent réfractaires aux approches biophysiques classiques. Dans ce contexte, les développements entrepris furent notamment focalisés sur la caractérisation de complexes impliqués dans la biogénèse des ribosomes et dans la régulation transcriptionnelle, fonctions cellulaires essentielles pouvant être liées à de nombreuses pathologies humaines dont certains cancers. Ainsi, les approches par MS native, pontage chimique et d’HDX-MS ont permis de renseigner sur la connectivité, les proximités spatiales ou encore la dynamique conformationnelle retrouvées au sein des complexes étudiés. Parmi ces techniques, l’HDX-MS permet une approche comparative basée sur les mesures d’incorporations en deutérium renseignant sur la dynamique conformationnelle d’une protéine sous différents états. Aussi, la combinaison d’approches de MS structurale a permis d’approfondir la caractérisation des systèmes complexes étudiés, démontrant ainsi l’intérêt d’une approche intégrative dans ce contexte. / This PhD thesis focuses on developing methods in structural mass spectrometry (MS) to characterize complex protein systems, given their size and their heterogeneity, frequently inaccessible by classical biophysic approaches. In this context, methodological developments have particularly focused on the characterization of protein complexes involved in ribosomes biogenesis and transcriptional regulation. These fundamental cellular processes are related to numerous diseases such as cancers and genetic diseases. Thus native MS, crosslink, and hydrogen/deuterium exchange coupled to MS (HDX-MS) allowed gaining insights about the stoechiometry, spatial proximities and conformational dynamics of studied systems. Among these approaches, HDX-MS enables a comparative approach based on deuterium incorporation measurements giving information about the conformational dynamics of labeled proteins in various experimental conditions. Finally, the combination of structural approaches enables to deeply characterize complex protein systems, highlighting the advantages of an integrative approach in this context.

Although computational structure prediction has had great successes in recent years, it regularly fails to predict the interactions of large protein complexes with residue-level accuracy, or even the correct orientation of the protein partners. The performance of computational docking can be notably enhanced by incorporating experimental data from structural biology techniques. A rapid method to probe protein-protein interactions is hydrogen-deuterium exchange mass spectrometry (HDX-MS). HDX-MS has been increasingly used for epitope-mapping of antibodies (Abs) to their respective antigens (Ags) in the past few years. In this paper, we review the current state of HDX-MS in studying protein interactions, specifically Ab-Ag interactions, and how it has been used to inform computational structure prediction calculations. Particularly, we address the limitations of HDX-MS in epitope mapping and techniques and protocols applied to overcome these barriers. Furthermore, we explore computational methods that leverage HDX-MS to aid structure prediction, including the computational simulation of HDX-MS data and the combination of HDX-MS and protein docking. We point out challenges in interpreting and incorporating HDX-MS data into Ab-Ag complex docking and highlight the opportunities they provide to build towards a more optimized hybrid method, allowing for more reliable, high throughput epitope identification.

The conversion of the native monomeric cellular prion protein (PrPC) into an aggregated pathological β-oligomeric (PrPβ) and an infectious form (PrPSc) is the central element in the development of prion diseases. The structure of the aggregates and the molecular mechanisms of the conformational change involved in this conversion are still unknown. My research hypothesis was that a specific structural rearrangement of normal PrPC monomers leads to the formation of new inter-subunit interaction interfaces in the prion aggregates, leading to aggregation. My approach was to use constraints obtained by structural proteomic methods to create a 3D model of urea-acid induced recombinant prion oligomers (PrPβ). My hypothesis was that this model would explain the mechanism of the conformational change involved in the conversion, the early formation of the β-structure nucleation site, and would describe the mode of assembly of the subunits within the oligomer. I applied a combination of limited proteolysis, surface modification, chemical crosslinking and hydrogen/deuterium exchange (HDX) with mass spectrometry for the differential characterization of the native and the urea-acid converted prion β-oligomer structures to get an insight into the mechanism of the conversion and aggregation. Using HDX, I detected a region of the protein in which backbone amides become more protected from exchange in PrPβ compared to PrPC. In order to obtain the inter-residue distance constraints to guide the assembly of the oligomer model, I then applied zero-length and short-range crosslinking to an equimolar mixture of 14N/15N-metabolically labeled β-oligomer thereby enabling the classification of the crosslinks as either intra-protein or inter-protein. Working with the Dokholyan group at the University of North Carolina at Chapel Hill, I was able to assemble a structure of the β-oligomer based on the combination of constraints obtained from all methods. By comparing the structures before and after the conversion, I was able to deduce the conformational change, that occurs during the conversion as the rearrangement and disassembly of the beta sheet 1– helix 1 – beta sheet 2 (β1-H1-β2) region from the helix 2 – helix 3 (H2-H3) core, forming new β-sheet nucleation site and resulting in the exposure of hydrophobic residues patches leading to formation of inter-protein contacts within aggregates. / Graduate / 2018-06-14