<p>Drug-drug interactions (DDIs) occur when multiple drugs are used concurrently. Caused by one drug inhibiting or inducing the metabolism of a second drug, DDIs often alter plasma concentrations and could seriously impact efficacy and safety of co-administered medications. Cytochrome P450 (CYP), a superfamily of enzymes, plays an important role in metabolizing a majority of FDA approved drugs currently on the market. 70% of predicable DDIs are associated with CYP enzymes inhibition. In-silico methods are increasingly adopted as a cost-effective complement to guide and prioritize efforts in drug discovery. Recent emerging applications of artificial intelligence algorithms have demonstrated promising results capable of prioritizing the selection of large chemical libraries, thereby outlining the future of in-silico methods assisting in drug discovery. Nevertheless, current methods rely on molecular descriptors that almost exclusively focus on chemical properties and atomic structures that fail to capture critical conformation and biological interaction related properties. There is also a lack of trainable molecular descriptors with feature specificity that reflect detailed protein-ligand binding energy and enable biological activity prediction. The overall objective of this dissertation is to understand molecular biological binding activity through electronic structure-based local descriptors derived from quantum based conceptual density functional theory (CDFT). This method will be used to assess the correlation of intermolecular interaction energy with ligand-protein binding with 2D feature maps reduced from the 4D molecular surfaces of the binding site and ligand (3D molecular surface with 1D electronic property). Additionally, it will be used to explore the possibility of predicting CYP related DDIs using descriptors generated using first principles including protein-ligand binding with specificity and strength and deep learning algorithms. Using quantum chemistry to interpret topological molecular information residing on 3D molecular surface permits the extraction of interacting features directly from the ligand structure. To achieve that, a set of curatable data containing consistent measurements was accessed through publicly accessible libraries. A series of novel Manifold Embedding of Molecular Surface (MEMS) descriptors were generated containing local electronic properties residing on the 3D molecule structure surface of each ligand using manifold learning. Major information were captured featuring electronic characteristics on the molecular 3D surface. Shape context was employed to derive transnational invariance feature vectors from MEMS with high granularity, thus preserving molecular information with specificity. DeepSet was utilized to perform permutation equivariance model training and validation. Powerful model learning is observed with an F-measure for all targets above 75% with the highest of 87% from external testing. Despite their promising prediction performance, molecular conformation changes and analytical featurization methods need to be implemented to expand model applicability and improve model reliability.</p>

Minimizing anti-cancer drug toxicity is a major challenge for the pharmaceutical industry. Toxicity is most frequently due to either the direct interaction of the drug on previously unidentified targets or its conversion to metabolites by drug metabolizing enzymes (e.g. CYP450 enzymes) that cause cellular, tissue or organ damage. Pharmacoproteomics is beginning to take a central role in studying changes in protein expression corresponding to drug administration, the results of which, inform about the mode of action, toxicity, and resistance in pre-clinical and clinical stages of drug development. The main aim of this research is to apply comparative proteomics studies on livers from male and female mice xenograft models treated with major anti-cancer drugs (5-flourouracil, paclitaxel, cisplatin, and doxorubicin) and CYP inducer, TCPOBOP, to investigate their effect on protein expression profiles (proteome). Within this thesis, an attention is paid to optimise a highly validated proteomics workflow for biomarker identification. Proteins were extracted from liver microsomes of mice treated in two separate sets; Set A – male (5-fluoruracil, doxorubicin, cisplatin and untreated) or Set B – female (5-fluoruracil, paclitaxel, TCPOBOP and untreated) using cryo-pulverization and sonication method. The extracts were digested with trypsin ii and the resulting peptides labelled with 4-plex iTRAQ reagents. The labelled peptides were subjected for separation in two-dimensions by iso-electric focusing (IEF) and RP-HPLC techniques before analysis by mass spectrometry and database searching for protein identification. Set A and Set B resulted in identification and quantification of 1146 and 1743 proteins, respectively. Moreover, Set A and Set B recovered 26 and 34 cytochrome P450 isoforms, respectively. The microsomal changes after drug treatments were quite similar. However, more changes were observed in the male set. Up-regulation of MUPs showed the greatest distinction in the protein expression patterns in the treated samples comparing to the untreated controls. In Set A, 5-fluoruracil and cisplatin increased the expression of three isoforms (MUP1, 2, and 6), whereas doxorubicin has increased the expression of four isoforms (MUP1, 2, 3, and 6). On the other side, only TCPOBOP in Set B has increased the expression of two isoforms (MUP1 and 6). Our findings showed that the expression of MUP, normally involved in binding and excretion of pheromones, have drug- and sex-specific differences. The mechanism and significance of MUP up-regulation are ambiguous. Therefore, the impact of each therapeutic agent on MUP and xenobiotic enzymes will be discussed.

The full text will be available at the end of the embargo: 17th July 2024

No / Nutritionally important PUFAs (polyunsaturated fatty acids) mediate some of their bioactivities through formation of oxygenated metabolites. These bioactive lipids are formed by COX (cyclo-oxygenase), LOX (lipoxygenase) and cytochrome-P450-catalysed reactions, as well as non-enzymatic lipid peroxidation. These reactions produce numerous species, some of which can be formed through more than one pathway. MS-based lipidomics offers the selectivity and sensitivity required for qualitative and quantitative analysis of multiple lipid species, in a variety of biological systems, and can facilitate the study of these mediators.

No / Lipid mediators are produced from the oxidation of polyunsaturated fatty acids through enzymatic and free radical-mediated reactions. When subject to oxygenation via cyclooxygenases, lipoxygenases, and cytochrome P450 monooxygenases, polyunsaturated fatty acids give rise to an array of metabolites including eicosanoids, docosanoids, and octadecanoids. These potent bioactive lipids are involved in many biochemical and signaling pathways, with inflammation being of particular importance. Moreover, because they are produced by more than one pathway and substrate, and are present in a variety of biological milieus, their analysis is not always possible with conventional assays. Liquid chromatography coupled to electrospray mass spectrometry offers a versatile and sensitive approach for the analysis of bioactive lipids, allowing specific and accurate quantitation of multiple species present in the same sample. Here we explain the principles of this approach to mediator lipidomics and present detailed protocols for the assay of enzymatically produced oxygenated metabolites of polyunsaturated fatty acids that can be tailored to answer biological questions or facilitate assessment of nutritional and pharmacological interventions.

This thesis is focused on an investigation of the mechanisms of three enzymatically mediated carbon skeleton isomerisation reactions. Chapter 1 provides an overview of some representative examples of the carbon skeleton rearrangement reactions in enzymology. Chapter 2 describes the preparation and use of fluorolittorines to explore the mechanism of the rearrangement of the tropane alkaloid littorine to hyoscyamine which is a reaction mediated by the cytochrome P450 enzyme. Chapter 3 describes the synthesis of D-ribose-1-phosphonates and the cyclic phosphonates (phostone) that are candidate inhibitors of the enzymatic isomerisation of 5-fluoro-5-deoxy-ribose-1-phosphate (5-FDRP) to 5-fluoro-5-deoxy-ribulose-1-phosphate (5-FDRulP), an important step in fluorometabolite biosynthesis pathway in Streptomyces cattleya. Chapter 4 describes the synthesis of 5-hydroxy-3,4-dioxohexylphosphonate and [5-13C]-5-hydroxy-3,4-dioxohexylphosphonate. These compounds are proposed as candidates for the transition state of the retro-aldol/aldol mechanism of the enzymatic isomerisation of 1-deoxy-D-xylulose-5-phosphate (DXP) to 2-C-methylerythitol-phophate-2-phosphate (MEP) in the biosynthesis of isopentenyl pyrophosphate (IPP) and dimethylallyl pyrophosphate (DMAPP). The influence of pH on tautomerisation of [5-13C]-5-hydroxy-3,4-dioxohexylphosphonate is also described. Chapter 5 describes the general chemical and biochemical methodologies utilised in this research project.

Le souhait de réduire des effets secondaires associés aux anticancéreux a mené à considérer l'utilisation de prodrogues activables au site d'action, comme la cyclophosphamide (CPA). La CPA est activée majoritairement par le CYP2B6 humain avec une faible efficacité, obligeant à l'utilisation de concentrations importantes de prodrogue. Celles-ci peuvent être réduites par transfection au niveau de la tumeur d'un gène codant pour un P450 optimisé, possédant une efficacité catalytique élevée vis-à-vis de la CPA tout en étant le moins immunogène possible. Pour ce faire, en partant de la modélisation du CYP2B6 et du CYP2B11, forme canine à bas Km pour l'activation de la CPA, un gène synthétique du CYP2B11 pour l'expression dans la levure a été dessiné et divisé en 15 "modules" structuraux. Quinze chimères à points de jonction définis entre les deux CYP2Bs ont ensuite été construites par échange de ces modules, via une méthode originale de génération de banques ordonnées de chimères, SIGNAL, indépendante de l'homologie de séquence des enzymes parentaux. SIGNAL, à mi-chemin entre les processus classiques d'évolution dirigée et de mutagenèse dirigée, nous a permis, après analyse fonctionnelle des chimères, de mieux comprendre le mécanisme de métabolisation de la CPA par les deux enzymes et d'identifier des modules structuraux jouant potentiellement un rôle important dans la haute affinité du CYP2B11. En parallèle, la mise au point d'un système de sélection à haut débit des variants les plus efficaces pour l'activation de la CPA dans la levure, basé sur le principe du gène rapporteur, a été débutée, afin de pouvoir raffiner l'optimisation du P450 par un processus de mutagenèse aléatoire.

<p>Molecular interactions lie at the heart of myriad biological processes. Knowledge of molecular recognition processes and the ability to model and predict interactions of any biological molecule to any chemical compound are the key for better understanding of cell functions and discovery of more efficacious medicines.</p><p>This thesis presents contributions to the development of a novel chemo-bioinformatics approach called proteochemometrics; a general method for interaction space analysis of biological macromolecules and their ligands. In this work we explore proteochemometrics-based interaction models over broad groups of protein families, evaluate their validity and scope, and compare proteochemometrics to traditional modeling approaches.</p><p>Through the proteochemometric analysis of large interaction data sets of multiple retroviral proteases from various viral species we investigate complex mechanisms of drug resistance in HIV-1 and discover general physicochemical determinants of substrate cleavage efficiency and binding in retroviral proteases. We further demonstrate how global proteochemometric models can be used for design of protease inhibitors with broad activity on drug-resistant viral mutants, for monitoring drug resistance mechanisms in the physicochemical sense and prediction of potential HIV-1 evolution trajectories. We provide novel insights into the complexity of HIV-1 protease specificity by constructing a generalized IF-THEN rule model based on bioinformatics analysis of the largest set of HIV-1 protease substrates and non-substrates.</p><p>We discuss how proteochemometrics can be used to map recognition sites of entire protein families in great detail and demonstrate how it can incorporate target variability into drug discovery process. Finally, we assess the utility of the proteochemometric approach in evaluation of ADMET properties of drug candidates with a special focus on inhibition of cytochrome P450 enzymes and investigate application of the approach in the pharmacogenomics field.</p>

Plants produce a rich variety of natural products to face environmental constraints. Enzymes of the cytochrome P450 CYP98 family are key actors in the production of phenolic bioactive compounds. They hydroxylate phenolic esters for lignin biosynthesis in angiosperms, but also produce various other bioactive phenolics. We characterized CYP98s from a moss, a lycopod, a fern, a conifer, a basal angiosperm, a monocot and from two eudicots. We found that substrate preference of the enzymes has changed during evolution of land plants with typical lignin-related activities only appearing in angiosperms, suggesting that ferns, similar to lycopods, produce lignin through an alternative route. A moss CYP98 knock-out mutant revealed coumaroyl-threonate as CYP98 substrate in vivo and showed a severe phenotype. Multiple CYP98s per species exist only in the angiosperms, where we generally found one isoform presumably involved in the biosynthesis of monolignols, and additional isoforms, resulting from independent duplications, with a broad range of functions in vitro / Graduate / 2017-08-31

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.