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The number of experimentally resolved protein structures in the Protein Data Bank has been growing fast in the last 20 years, which motivates the develop- ment of many computational tools for protein-ligand binding sites prediction. Binding sites prediction from protein 3D structure has many important applica- tions; it is an essential step in the complex process of rational drug design, it helps to infer the side-effects of drugs, it provides insight into proteins biological functions and it is helpful in many other fields, such as protein-ligand docking and molecular dynamics. As far as we know, there has not been a study that would systematically investigate general properties of known ligand binding sites on a large scale. In this thesis, we examine these properties using existing experimen- tal and predicted residue-level annotations of protein sequence and structure. We present an automated pipeline for statistical analysis of these annotations, based on hypothesis testing and effect size estimation. It is implemented in Python and it is easily extensible by user-defined annotations. The usage is demonstrated on 33 existing annotations and 4 different datasets. The practical significance of the results is tested with P2Rank prediction method. We hope that the results as well as the pipeline...

Cancer is a leading cause of death worldwide. Development of new cancer drugs is increasingly costly and time-consuming. By exploiting massive amounts of biological data, computational repositioning proposes new uses for old drugs to reduce these development hurdles. A promising approach is the systematic analysis of structural data for identification of shared binding pockets and modes of action. In this thesis, I developed the Protein-Ligand Interaction Profiler (PLIP), which characterizes and indexes protein-ligand interactions to enable comparative analyses and searching in all available structures. Following, I applied PLIP to identify new treatment options in cancer: the heat shock protein Hsp27 confers resistance to drugs in cancer cells and is therefore an attractive target with a postulated drug binding site. Starting from Hsp27, I used PLIP to define an interaction profile to screen all structures from the Protein Data Bank (PDB). The top prediction was experimentally validated in vitro. It inhibits Hsp27 and significantly reduces resistance of multiple myeloma cells against the chemotherapeutic agent bortezomib. Besides computational repositioning, PLIP is used in docking, binding mode analysis, quantification of interactions and many other applications as evidenced by over 12,000 users so far. PLIP is provided to the community online and as open source.

<p>The identification and quantification of protein-protein interactions in large scale is critical to understanding biological processes at a systems level. Current approaches for the analysis of protein -protein interactions are generally not quantitative and largely limited to certain types of interactions such as binary and strong binding interactions. They also have high false-positive and false-negative rates. Described here is the development of and application of mass spectrometry-based proteomics metehods to detect and quantify the strength of protein-protein and protein-ligand interactions in the context of their interaction networks. Characterization of protein-protein and protein-ligand interactions can directly benefit diseased state analyses and drug discovery efforts. </p><p>The methodologies and protocols developed and applied in this work are all related to the Stability of Unpurified Proteins from Rates of amide H/D Exchange (SUPREX) and Stability of Protein from Rates of Oxidation (SPROX) techniques, which have been previously established for the thermodynamic analysis of protein folding reactions and protein-ligand binding interactions. The work in this thesis is comprised of four parts. Part I involves the development of a Histidine Slow H/D exchange protocol to facility SURPEX-like measurements on the proteomic scale. The Histidine Slow H/D exchange protocol is developed in the context of selected model protein systems and used to investigate the thermodynamic properties of proteins in a yeast cell lysate. </p><p>In Part II an isobaric mass tagging strategy is used in combination with SPROX (i.e., a so-called iTRAQ-SPROX protocol) is used to characterize the altered protein interactions networks associated with lung cancer. This work involved differential thermodynamic analyses on the proteins in two different cell lines, including ADLC-5M2 and ADLC-5M2-C2. </p><p>Parts III and IV of this thesis describe the development and application of a SPROX protocol for proteome-wide thermodynamic analyses that involves the use of Stable Isotope Labeling by Amino acid in cell Culture (SILAC) quantitation. A solution-based SILAC-SPROX protocol is described in Part III and a SILAC-SPROX protocol involving the use of cyanogen bromide and a gel-based fractionation step is described in Part IV. The SILAC-SPROX-Cyanogen bromide (SILAC-SPROX-CnBr) protocol is demonstrated to significantly improve the peptide and protein coverage in proteome-wide SPROX experiments. Both the SILAC-SPROX and SILAC-SPROX-CnBr porotocols were used to characterize the ATP binding properties of yeast proteins. Ultimately, the two protocols enabled 526 yeast proteins to be assayed for binding to AMP-PNP, an ATP mimic. A total of 140 proteins, including 37 known ATP-binding proteins, were found to have ATP binding interactions.</p> / Dissertation

<p>Detection and quantification of protein-ligand binding interactions is extremely important for understanding interactions that occur in biological systems. Since traditional techniques for characterizing these types of interactions cannot be performed in complex systems such as cell lysates, a series of energetics-based techniques that are capable of assessing protein stability and measuring ligand binding affinities have been developed to overcome some of the limitations of previous techniques. Now that the capabilities of the energetics-based techniques have been exhibited in model systems, the false-positive rates of the techniques, the range of biological questions to which the techniques can be addressed, and the use of the techniques to discover novel interactions in unknown systems remained to be shown. The Stability of Proteins from Rates of Oxidation (SPROX) technique and the Pulse Proteolysis (PP) technique were applied to a wide range of biological questions in both yeast and human cell lysates to evaluate the scope of these experimental workflows. The false-positive rate of iTRAQ-SPROX protein target discovery on orbitrap mass spectrometer systems was determined to be < 0.8 %. The iTRAQ-SPROX technique was successfully applied to the discovery of both known and novel protein-protein, protein-ATP, and protein-drug interactions, leading to the quantification of protein-ligand binding affinities in each of these studies. In the pursuit of discovering geldanamycin protein interactors, the use of iTRAQ-SPROX and SILAC-PP in combination was determined to be advantageous for confirming protein-ligand interactions since the techniques utilize different quantitation strategies that are subject to separate technical errors in quantitation. Finally, the iTRAQ-SPROX and SILAC-PP techniques were used to evaluate the interactions of manassantin A in a human cell lysate. In this work, a previously unknown protein target of manassantin A, Filamin A, was detected as a hit protein using both the iTRAQ-SPROX and SILAC-PP protocols. The work completed in this dissertation has expanded the understanding of the limitations of energetics-based techniques and shown that biological replicate analyses are essential to confirm ligand interactions with novel protein targets.</p> / Dissertation

La compréhension et la prédiction des relations structure-fonction de protéines par des approches in sillico représentent aujourd'hui un challenge. Malgré le développement récent de méthodes algorithmiques pour l'étude du mouvement et des interactions moléculaires, la flexibilité de macromolécules reste largement hors de portée des outils actuels de modélisation moléculaire. L'objectif de cette thèse est de développer une nouvelle approche basée sur des algorithmes de planification de mouvement issus de la robotique pour mieux traiter la flexibilité moléculaire dans l'étude des interactions protéiques. Nous avons étendu un algorithme récent d'exploration par échantillonnage aléatoire, ML-RRT pour le désassemblage d'objets articulés complexes. Cet algorithme repose sur la décomposition des paramètres de configuration en deux sous-ensembles actifs et passifs, qui sont traités de manière découplée. Les extensions proposées permettent de considérer plusieurs degrés de mobilité pour la partie passive, qui peut être poussée ou attirée par la partie active. Cet outil algorithmique a été appliqué avec succès pour l'étude des changements conformationnels de protéines induits lors de la diffusion d'un ligand. A partir de cette extension, nous avons développé une nouvelle méthode pour la résolution simultanée du séquençage et des mouvements de désassemblage entre plusieurs objets. La méthode, nommée Iterative-ML-RRT, calcule non seulement les trajectoires permettant d'extraire toutes les pièces d'un objet complexe assemblé, mais également l'ordre permettant le désassemblage. L'approche est générale et a été appliquée pour l'étude du processus de dissociation de complexes macromoléculaires en introduisant une fonction d'évaluation basée sur l'énergie d'interaction. Les résultats présentés dans cette thèse montrent non seulement l'efficacité mais aussi la généralité des algorithmes proposés. / Understanding and predicting structure-function relationships in proteins with fully in silico approaches remain today a great challenge. Despite recent developments of computational methods for studying molecular motions and interactions, dealing with macromolecular flexibility largely remains out of reach of the existing molecular modeling tools. The aim of this thesis is to develop a novel approach based on motion planning algorithms originating from robotics to better deal with macromolecular flexibility in protein interaction studies. We have extended a recent sampling-based algorithm, ML-RRT, for (dis)-assembly path planning of complex articulated objects. This algorithm is based on a partition of the configuration parameters into active and passive subsets, which are then treated in a decoupled manner. The presented extensions permit to consider different levels of mobility for the passive parts that can be pushed or pulled by the motion of active parts. This algorithmic tool is successfully applied to study protein conformational changes induced by the diffusion of a ligand inside it. Building on the extension of ML-RRT, we have developed a novel method for simultaneously (dis)assembly sequencing and path planning. The new method, called Iterative-ML-RRT, computes not only the paths for extracting all the parts from a complex assembled object, but also the preferred order that the disassembly process has to follow. We have applied this general approach for studying disassembly pathways of macromolecular complexes considering a scoring function based on the interaction energy. The results described in this thesis prove not only the efficacy but also the generality of the proposed algorithms

L'étude des interactions non-covalentes et des relations structure-fonction est à la base de la compréhension des systèmes biologiques. La MS supramoléculaire est une technique de choix pour l’étude des interactions protéine/protéine ou protéine/ligand. Dans le cadre d'études qualitatives ou quantitatives, pour chaque système étudié, les conditions expérimentales et les paramètres instrumentaux ont été optimisés pour conserver le complexe en phase gazeuse (1). L'objectif principal de ce travail est de caractériser le site nucléotidique de hPEBP1 et de contribuer à la découverte de molécules anti-métastases. Sur le plan fonctionnel, une activité enzymatique de hPEBP1 n'a pas pu être mise en évidence. Pour ce projet, une méthode MS de détermination de KD de complexes à faible affinité, plus précise et ne nécessitant par l'utilisation d'un ligand de référence a été développée (2). Une recherche des déterminants structuraux d'un ligand optimal de hPEBP1 a été réalisée par criblage de composés issus d’une synthèse raisonnée basée sur la structure des nucléotides FMN et GTP et par la détermination de leur KD (3). Les criblages ont montré que les critères structuraux indispensables pour la liaison sont la présence d’un groupement chargé ou donneur d’électrons, d’une structure apparentée à une base azotée et d’un cycle additionnel. Une part importante de l’affinité est liée au caractère hydrophobe du ligand. Certains ligands de synthèse ont montré une activité inhibitrice de l’invasion des lignées tumorales. / The study of noncovalent interactions and structure-function relationships provides the basis for the understanding of biological systems. Supramolecular MS is a favored technique to dissect protein/protein or protein/ligand interactions. In the context of qualitative or quantitative studies, experimental conditions and instrumental parameters have been optimized for each system to preserve the noncovalent complex in the gas-phase (1). The main objective of this work is to characterize the nucleotide site of hPEBP1 and to contribute to the discovery of antimetastatic molecules. Functionally, a catalytic activity for hPEBP1 could not be detected. For this project, an original MS method to more accurately determine KD for low-affinity complexes without a reference ligand was developed (2). Structural features of an optimal hPEBP1 ligand were determined by screening compounds based on FMN and GTP nucleotides in the context of a rational design approach, using KD determination to rank affinities (3). Screening highlighted that the essential structural requirements for binding hPEBP1 consist in a charged group or an electron donor, a structure related to a cyclic nitrogenous base and an additional cycle. A significant part of the affinity depends on the hydrophobic nature of the ligand. Some of the synthesized nucleotide analogs are active as inhibitors of invasion in tumor cell lines.

In recent years the application of single-molecule techniques to probe biomolecules and intermolecular interactions at single-molecule resolution has expanded rapidly. Here, I investigate a series of peptides and proteins in an attempt to gain a better understanding of nanopore sensing as a single-molecule technique. The analysis of retro, inversed, and retro-inversed isomers of glucagon and α-helical Fmoc-D2A10K2 peptide showed that nanopore sensing utilizing a wild-type α-hemolysin pore can distinguish between all four isomers while circular dichroism can only distinguish between chiral isomers, but not between directional isomers. The investigation of a series of proteins of different chemical and physical properties revealed important information about nanopore analysis of proteins. Contrary to some reports in the literature, all proteins analysed here induced large blockade events. The frequency of total events and the proportion of large blockade events were significantly reduced in tris(hydroxymethyl)aminomethane or 4-(2-hydroxyethyl)piperazine-1-ethanesulfonic acid buffers and were only restored by the addition of ethylenediaminetetraacetic acid or the use of phosphate buffer, both of which can sequester metal ions. Furthermore, the results obtained with the proteins in the presence of ligands demonstrated that transient or partial unfolding of proteins can be detected by nanopore analysis confirming the usefulness of this technique for conformational studies or for protein/ligand interactions. Interestingly, while the blockade current histograms were different for each protein there was no obvious correlation between the properties of the proteins and the blockade current histograms. In an attempt to identify whether the large blockade events were translocation or intercalation, both an indirect and a direct approach were taken. The indirect approach which relies on the effect of voltage on the interaction of the molecule with the pore provided no conclusive answer to the question of protein translocation through the α-hemolysin pore. In contrast, the direct approach in which ribonuclease A is added to the cis side of the pore and then the trans side is tested for enzyme activity showed that ribonuclease A doesn't translocate through the α-hemolysin pore.

<p>Proteins fold into well-defined three-dimensional structures to carry out their biological functions which involve non-covalent interactions with other cellular molecules. Knowledge about the thermodynamic properties of proteins and protein-ligand complexes is essential for answering fundamental biological questions and drug or biomarker discovery. Recently, chemical labeling strategies have been combined with mass spectrometry methods to generate thermodynamic information about protein folding and ligand binding interactions. The work in this thesis is focused on the development and application of two such chemical labeling protocols coupled with mass spectrometry including one termed, SUPREX (stability of unpurified proteins from rates of H/D exchange), and one termed SPROX (stability of proteins from rates of oxidation). The work described in this thesis is divided into two parts. The first part involves the application of SUPREX to the thermodynamic analysis of a protein folding chaperone, Hsp33, and its interaction with unfolded protein substrates. The second part involves the development of a new chemical labeling protocol that can be used to make protein folding and ligand binding measurements on the proteomic scale. </p><p>In the first part of this work, the SUPREX technique was used to study the binding interaction between the molecular chaperone Hsp33 and four different unfolded protein substrates including citrate synthase, lactate dehydrogenase, malate dehydrogenase, and aldolase. The results of the studies, which were performed at the intact protein level, suggest that the cooperativity of the Hsp33 folding/unfolding reaction increases upon binding with denatured protein substrates. This is consistent with the burial of significant hydrophobic surface area in Hsp33 when it interacts with its substrate proteins. The SUPREX derived Kd-values for Hsp33 complexes with four different substrates were also found to be all within a range of 3-300 nM. The interaction between Hsp33 and one of its substrates, citrate synthase (CS), was characterized at a higher structural resolution by using the SUPREX technique in combination with a protease digestion protocol. Using this protocol, the thermodynamic properties for both Hsp33 and CS were evaluated at different stages of binding, including reduced Hsp33 (inactive form), oxidized Hsp33 (active form), followed by native CS and finally of Hsp33ox -CS complexes before and after reduction with DTT. The results suggest that Hsp33 binds unfolded proteins that still have a significant amount of residual higher- order structure. Structural rearrangements of the substrate protein appear to occur upon reduction of the Hsp33-substrate complexes, which may facilitate the transfer of the substrate protein to other protein folding chaperone systems. </p><p>In the second part of this dissertation, a mass spectrometry-based covalent labeling protocol, which relies on the amidination rate of globally protected protein amine groups, was designed and applied to the thermodynamic analysis of several eight protein samples including: six purified proteins (ubiquitin, BCAII, RNaseA, 4OT, and lysozyme with, and without GlcNAc), a five-protein mixture comprised of ubiquitin, BCAII, RNaseA, Cytochome C, and lysozyme, and a yeast cell lysate. The results demonstrate that in ideal cases the folding free energies of proteins and the dissociation constants of protein-ligand complexes can be accurately evaluated using the protocol. Also demonstrated is the new method's compatibility with three different mass spectrometry-based readouts including an intact protein readout using MALDI, a gel-based proteomics readout using MALDI, and an LC-MS-based proteomics readout using isobaric mass tags. The results of the cell lysate sample analysis highlight the complementarity of the labeling protocol to other chemical modification strategies that have been recently developed to make thermodynamic measurements of protein folding and stability on the proteomic scale.</p> / Dissertation

In this dissertation a novel approach to protein-ligand docking is presented. First an existing method to predict putative active sites is employed. These predictions are then used to cut down the search space of an algorithm that uses the fast Fourier transform to calculate the geometrical and electrostatic complementarity between a protein and a small organic ligand. A simplified hydrophobicity score is also calculated for each active site. The docking method could be applied either to dock ligands in a known active site or to rank several putative active sites according to their biological feasibility. The method was evaluated on a set of 310 protein-ligand complexes. The results show that with respect to docking the method with its initial parameter settings is too coarse grained. The results also show that with respect to ranking of putative active sites the method works quite well.