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Paget’s disease of bone (PDB) shows a strong genetic component and mutations in SQSTM1 (Sequestosome 1) are observed in about 10% of sporadic PDB patients. My PhD investigated the RIN3 gene (Ras and Rab interactor protein 3), previously implicated in the pathogenesis of PDB by GWAS. The RIN3 gene encodes a guanine exchange factor (GEF), involved in the activation of GTPases which are crucial in osteoclast activity. It also has a role in endocytosis and recycling of tyrosine kinase receptor. The role of RIN3 in bone remodelling is unclear, however some investigations revealed some associations with bone: RIN3 has been associated with high lower limb bone mineral density in children in a meta-analysis of GWAS studies, and was shown to be expressed in primary calvarial osteoblasts. The expression of RIN3 was down regulated during human primary osteoclast differentiation, and also in iliac bone biopsies from osteoporotic patients compared to healthy postmenopausal donors (Kemp et al, 2014).   In Chapter 1, I present normal bone structure, composition and remodelling before detailing PDB and its genetics. I then introduce RIN3 as a candidate gene for PDB. In Chapter 2, I describe all methods performed and materials used for the completion of this project. This includes primary cell cultures, RNA and protein work, immunostaining, immunochemistry and phenotype analysis on Rin3-/- mice. Chapter 3 presents the fine mapping of RIN3 using Sanger and next generation sequencing performed on PDB cases and controls. 18 variants were detected and one common variant (p.R279C) showed a strong association with PDB. Rare variants were also over-represented in cases, and many were shown to be on the same haplotype as p.R279C. Chapter 4 details the association study performed on a UK cohort and includes the investigation of the clinical phenotype severity in patients against the RIN3 mutations. Chapter 5 presents the expression pattern of RIN3 in bone cells and bone microenvironment. Important variations of RIN3 mRNA and protein were detected during the differentiation of bone marrow derived osteoclasts. Protein levels of RIN3 were also found in osteoclasts from human osteoclastoma, human osteosarcoma, PDB patients, giant cell tumour (GCT) and healthy controls. Within all the mouse tissues analysed, Rin3 mRNA was expressed the highest in bone after lung. Chapter 6 focuses on the work performed on mice deficient of the Rin3 gene. They showed a higher trabecular bone volume and a smaller active resorption surface occupied by osteoclasts in trabecular bone. In conclusion, the combined in vitro and in vivo analyses have uncovered that RIN3 plays a role in bone metabolism and is a strong gene candidate for PDB.

<p>Databases nowadays used in all kinds of application areas often differ greatly in a number of properties. These varieties add complexity to the handling of databases, especially when two or more different databases are dependent.</p><p>The approach described here to propagate updates in an application scenario with heterogeneous, dependent databases is the use of a rule-based mediator. The system EruS (ECA rules updating SCOP) applies active database technologies in a bioinformatics scenario. Reactive behaviour based on rules is used for databases holding protein structures.</p><p>The inherent heterogeneities of the Structural Classification of Proteins (SCOP) database and the Protein Data Bank (PDB) cause inconsistencies in the SCOP data derived from PDB. This complicates research on protein structures.</p><p>EruS solves this problem by establishing rule-based interaction between the two databases. The system is built on the rule engine ruleCore with Event-Condition-Action rules to process PDB updates. It is complemented with wrappers accessing the databases to generate the events, which are executed as actions. The resulting system processes deletes and modifications of existing PDB entries and updates SCOP flatfiles with the relevant information. This is the first step in the development of EruS, which is to be extended in future work.</p><p>The project improves bioinformatics research by providing easy access to up-to-date information from PDB to SCOP users. The system can also be considered as a model for rule-based mediators in other application areas.</p>

A thorough knowledge of non-covalent amino acid interactions within a protein structure is essential for a complete understanding of its conformation, stability and function. Among all the amino acids that usually make up a protein, tryptophan is distinguished both by its rarity and size of its side chain formed by an indole group. It is able to provide various types of indispensable interactions within the protein and between different polypeptide chains, but also between the protein and a biological membrane. In addition, it is the most commonly used natural fluorophore. Databases of solved protein structures are commonly used to study amino acid interactions and allow more or less complex analyzes of the issue. Thus many non-covalent interactions that may occur between tryptophan and other amino acids have been found. However, most of these analyzes focus on specific interactions and do not follow up the tryptophan's environment as a whole, where all amino acids interact. Some newly developed methods have been used in this Thesis, specifically the occurrence profiles of the individual amino acids around the indole group of tryptophan and the results were compared with an available literature. The amino acid that has the greatest preference for tryptophan turned out to be tryptophan again, and...

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.

SUMOylation and ubiquitination are important post-translational modifications. While ubiquitination is well known for targeting proteins for degradation, SUMOylation often regulates the intracellular localization of substrates. In the first project of this dissertation, we developed proteomic strategies to identify novel SUMOylated proteins in mammalian cells. In the second project, we investigated the regulation of protein ubiquitination in the NF-κB signaling pathway in the context of Paget’s disease of bone (PDB). Identification of SUMOylated proteins has been a challenge because of low abundance of SUMOylation substrates. Here, we utilized a mass spectrometry (MS)-based proteomic approach to identify novel SUMOylated proteins in mammalian cells. Seventy-four unique proteins were commonly identified in the collection of four SUMO-1 plasmids, thus considered candidate SUMOylated proteins. Many of these proteins are associated with the nucleus. The results were validated by confirming SUMOylation of a novel substrate Drebrin and a well known substrate Ran-GAP1. Furthermore, the potential SUMOylation sites in Drebrin have been identified and confirmed using site-directed mutagenesis. PDB is a disorder characterized by increased bone turnover containing hyperactive osteoclasts. Mutations in Sequestosome 1 (p62) are associated with 40% of familial PDB. P62 is a scaffold protein and plays a critical role in regulating ubiquitination of TRAF family signaling molecules and mediating the activation of NF-κB by RANK and TNFα ligands. P62 also plays a critical role in shuttling substrates for autophagic degradation. The objective of this project is to determine the effects of PDB-associated p62 mutants on NF-κB signaling and autophagy. We compared the effect of wild-type (WT) p62 and PDB mutations (A381V, M404V and P392L) on the TNFα-induced NF-κB signaling using an NF-κB luciferase assay. Our results show that these p62 mutations increased the NF-κB signaling. In addition, we found that the PDB mutations did not change the interaction between p62 and the autophagy marker protein LC3. In summary, the PDB mutations in p62 are likely gain-of-function mutations that can increase NF-κB signaling and potentially contribute to disease progression. Based on the results, we proposed a model to speculate the synergetic role of p62 PDB mutant on NF-κB signaling and autophagy.

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

abstract: Peptides offer great promise as targeted affinity ligands, but the space of possible peptide sequences is vast, making experimental identification of lead candidates expensive, difficult, and uncertain. Computational modeling can narrow the search by estimating the affinity and specificity of a given peptide in relation to a predetermined protein target. The predictive performance of computational models of interactions of intermediate-length peptides with proteins can be improved by taking into account the stochastic nature of the encounter and binding dynamics. A theoretical case is made for the hypothesis that, because of the flexibility of the peptide and the structural complexity of the target protein, interactions are best characterized by an ensemble of possible bound configurations rather than a single &ldquo;lock and key&rdquo; fit. A model incorporating these factors is proposed and evaluated. A comprehensive dataset of 3,924 peptide-protein interface structures was extracted from the Protein Data Bank (PDB) and descriptors were computed characterizing the geometry and energetics of each interface. The characteristics of these interfaces are shown to be generally consistent with the proposed model, and heuristics for design and selection of peptide ligands are derived. The curated and energy-minimized interface structure dataset and a relational database containing the detailed results of analysis and energy modeling are made publicly available via a web repository. A novel analytical technique based on the proposed theoretical model, Virtual Scanning Probe Mapping (VSPM), is implemented in software to analyze the interaction between a target protein of known structure and a peptide of specified sequence, producing a spatial map indicating the most likely peptide binding regions on the protein target. The resulting predictions are shown to be superior to those of two other published methods, and support the validity of the stochastic binding model. / Dissertation/Thesis / Ph.D. Bioengineering 2010

Protein-protein interactions occur in nature and have different functions. The interacting surface between two interacting proteins contains the respective protein's interface residues. In this thesis, a series of Python scripts are presented which can perform interface-interface comparisons with the method InterComp, to obtain a distance matrix of different protein interfaces. The distance matrix can be studied with the use of clustering algorithms such as DBSCAN. The result from clustering using DBSCAN shows that for the 77,017 protein interfaces studied, a majority of the protein interfaces are part of a single cluster while most of the remaining interfaces are noise for the tested parameters Eps and MinPts. The conclusion of this thesis is the effect on the number of clusters for the tested parameters Eps and MinPts when performing DBSCAN.

Databases nowadays used in all kinds of application areas often differ greatly in a number of properties. These varieties add complexity to the handling of databases, especially when two or more different databases are dependent. The approach described here to propagate updates in an application scenario with heterogeneous, dependent databases is the use of a rule-based mediator. The system EruS (ECA rules updating SCOP) applies active database technologies in a bioinformatics scenario. Reactive behaviour based on rules is used for databases holding protein structures. The inherent heterogeneities of the Structural Classification of Proteins (SCOP) database and the Protein Data Bank (PDB) cause inconsistencies in the SCOP data derived from PDB. This complicates research on protein structures. EruS solves this problem by establishing rule-based interaction between the two databases. The system is built on the rule engine ruleCore with Event-Condition-Action rules to process PDB updates. It is complemented with wrappers accessing the databases to generate the events, which are executed as actions. The resulting system processes deletes and modifications of existing PDB entries and updates SCOP flatfiles with the relevant information. This is the first step in the development of EruS, which is to be extended in future work. The project improves bioinformatics research by providing easy access to up-to-date information from PDB to SCOP users. The system can also be considered as a model for rule-based mediators in other application areas.