Drug repositioning is the discovery of new indications for approved or failed drugs. This practice is commonly done within the drug discovery process in order to adjust or expand the application line of an active molecule. Nowadays, an increasing number of computational methodologies aim at predicting repositioning opportunities in an automated fashion. Some approaches rely on the direct physical interaction between molecules and protein targets (docking) and some methods consider more abstract descriptors, such as a gene expression signature, in order to characterise the potential pharmacological action of a drug (Chapter 1). On a fundamental level, repositioning opportunities exist because drugs perturb multiple biological entities, (on and off-targets) themselves involved in multiple biological processes. Therefore, a drug can play multiple roles or exhibit various mode of actions responsible for its pharmacology. The work done for my thesis aims at characterising these various modes and mechanisms of action for approved drugs, using a mathematical framework called description logics. In this regard, I first specify how living organisms can be compared to complex black box machines and how this analogy can help to capture biomedical knowledge using description logics (Chapter 2). Secondly, the theory is implemented in the Functional Therapeutic Chemical Classification System (FTC - https://www.ebi.ac.uk/chembl/ftc/), a resource defining over 20,000 new categories representing the modes and mechanisms of action of approved drugs. The FTC also indexes over 1,000 approved drugs, which have been classified into the mode of action categories using automated reasoning. The FTC is evaluated against a gold standard, the Anatomical Therapeutic Chemical Classification System (ATC), in order to characterise its quality and content (Chapter 3). Finally, from the information available in the FTC, a series of drug repositioning hypotheses were generated and made publicly available via a web application (https://www.ebi.ac.uk/chembl/research/ftc-hypotheses). A subset of the hypotheses related to the cardiovascular hypertension as well as for Alzheimer’s disease are further discussed in more details, as an example of an application (Chapter 4). The work performed illustrates how new valuable biomedical knowledge can be automatically generated by integrating and leveraging the content of publicly available resources using description logics and automated reasoning. The newly created classification (FTC) is a first attempt to formally and systematically characterise the function or role of approved drugs using the concept of mode of action. The open hypotheses derived from the resource are available to the community to analyse and design further experiments.

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Les récepteurs couplés aux protéines G (RCPGs), constituent la plus grande famille de protéines membranaires dans le génome humain. Les RCPGs sont des protéines de signalisation, qui exercent leur action à la surface des cellules, en réponse à une grande variété de stimuli extérieurs. Ils jouent un rôle primordial dans de nombreuses fonctions physiologiques et sont donc impliqués dans une multitude de pathologies comme les maladies cardiovasculaires, métaboliques, neurodégénératives, psychiatriques et oncologiques. L'attribution du prix Nobel de chimie 2012 aux professeurs Robert Lefkowitz et Brian Kobilka pour leurs travaux et avancées spectaculaires dans le champ de recherches des RCPGs, souligne encore leur importance. Les RCPGs constituent également la plus importante cible thérapeutique, avec 30% des médicaments actuellement disponibles sur le marché qui exercent leur action via un RCPG. Cependant, la découverte de nouveaux ligands reste un chalenge. Le but est de développer des approches basées sur la RMN à l’état liquide, qui auront un impact positif sur la recherche de ligand de RCPGs, grâce à l’étude et la caractérisation de récepteur pleine taille, solubilisés en micelles de détergents ou enchâssés en bicouches lipidiques natives / G protein-coupled receptors (GPCRs) are the largest class of membrane proteins in the human genome. GPCRs act as cell surface signalling proteins and respond to a variety of external signals. They play a pivotal role in many physiological functions and are therefore associated with a multitude of diseases, including cardiovascular, metabolic, neurodegenerative, psychiatric, and oncologic diseases. The 2012 noble Prize in Chemistry was awarded jointly to Robert J. Lefkowitz and Brian K. Kobilka for studies of GPCRs, highlighting the importance of this protein superfamily. GPCRs constitute also the most important family of drug targets in the human body, with 30% of current drugs acting on GPCRs. However, drug discovery targeting GPCRs remains difficult, owing to the restricted structural information on GPCRs related to the instability of these proteins when isolated from their cell membrane environments. There is also a lack of knowledge for the structural and functional consequences of the interactions of small-molecule compounds with GPCR. The aim is to develop methods to study and characterize a full GPCR solubilized in detergents or in native lipid bilayers, both in its free form and in small molecule bound forms, using liquid-state NMR experiments. The aim is to develop NMR-based approaches that will strongly impact the structure-based drug discovery process for the GPCR family

Live cell imaging has not been an active method of analysis during the drug discovery and development phase due to several limitations. This does not change the fact that it along with its time series data analysis describes an undergoing process better than a conventional study with fixed time points. In this project, I was a part of a team which are currently developing live cell morphological profiling assays which allows measuring cells’ morphology and perturbations caused on it due to toxicity by different treatments. Later, I attempted automating a group of robots to perform these assays automatically. I also developed a few software pipelines which generate quantitative data from live cell images, and performs analysis and data visualization on this quantitative time series data. Later, I implemented these methods on one of the experiment set and displayed importance of time series data by showing different trends displayed by different treatments for different morphology descriptors.

1. SUMMARYMyeloperoxidase (MPO) which belongs to the peroxidase family, is found in mammalian neutrophils. This heme enzyme contributes to the production of (pseudo)halogenous acid such as HOCl which oxidizes proteins, cell membrane, DNA and RNA causing death for the pathogens. It has an antimicrobial effect due to HOCl secreting inside the phagosomes of the neutrophils, whereas it will be released outside neutrophils causing oxidative damages for the host tissues. Proteins, lipids, lipoproteins, DNA and RNA are potential targets of the MPO resulting in several chronic syndromes. Many researchers have discovered the harmful effects of MPO and its products demonstrating its role in many inflammatory chronic diseases such as: Cardiovascular diseases as in atherosclerosis. MPO contribution in atherosclerosis development has been demonstrated. Neurodegenerative diseases also was related to MPO: such as Alzheimer’s disease (AD), multiple sclerosis (MSc) and Parkinson’s disease The enzyme has been also pointed out in other diseases such as renal disease and cancer.For these reasons, MPO as a target of drug discovery has attracted the attention of many researchers. X-ray 3D structures were resolved for this enzyme, biological activity and mechanism of action were investigated in depth, and many medicinal chemists have investigated and screened for new MPO inhibitors. Indeed, this cumulative work including X-ray data, the role of MPO in different pathologies, MPO inhibitory mechanism of action, screening and various chemical entities that inhibit MPO, provided sufficient elements to start a new drug design and drug discovery process on MPO.The aim of the present study was to apply a rational drug design approach to the myeloperoxidase inhibition: from in silico to pharmacological activity. This includes:─ Conducting high throughput virtual screening in order to find new potential hits to inhibit MPO followed by mechanism of inhibition determination. ─ Selecting one hit and then implementing a whole pharmacomodulation process in order to increase the potency of the inhibition greater than the starting hit and to improve the selectivity.Firstly, a rational drug design process was launched to find new hits using high throughput virtual screening. The chosen database for the screening was ASINEX database published in ZINC.X-ray structure of human peroxidase complexed to cyanide and thiocyanate (PDB 1DNW) was selected to conduct High-Throughput Virtual Screening (HTVS). Three successive protocols with different levels of accuracy in the docking and scoring processes were used starting with HTVS, followed by Standard Precision (SP) and finally with Xtra Precision (XP). The quality of the docking process performed was validated by docking a set of 60 chosen molecules of varying chemical structure and known as MPO inhibitors. From the result of the HTVS conducted on 1,350,000 compounds, the 100 best compounds were selected. Among them, 81 molecules were available for purchase from ASINEX, those compounds were tested with a MPO inhibition assay. Thirty-two compounds (39 %) were active, but only 8 compounds were selected, featuring different chemical structures with IC50 values ranging between 0.46 ± 0.07 and 12 ± 3 μM. Among these molecules, two compounds were the best and considered as hits. One has purinedione structure which is similar with the structure of thioxanthine derivatives (F9, IC50=0.46±0.07μM). The second compound has a hexahydropyrimidine structure (A1, IC50 = 0.5 ± 0.1 μM) The most common interactions found among all 8 docked ligands are the ionic bond with Glu102 and a stacking (shifted or not) with pyrrole ring D of the prosthetic group. Hydrogen bonds with Glu102, Thr100, Gln91, Arg239, or the propionate groups of the heme are also found in several docked geometries of the complexes. Interestingly, interactions with Glu102 and pyrrole ring D of the heme were also seen with fluorotryptamine derivatives and also salicylhydroxamic acid (SHA).For measuring MPO-dependent LDL oxidation, the two best compounds were tested. Compounds A1 and F9 showed good inhibition on MPO-dependent LDL oxidation (62 ± 6, 4.5 ± 0.9, 11 ± 2% and 11 ± 2, 2.6 ± 0.8, 6 ± 4%, respectively).Consequently, in order to determine the mechanism of inhibition transient-state kinetics were further investigated of all the 8 selected compounds.Both new lead compounds (A1 and F9) act as electron donors of both Compound I and Compound II of MPO. The reaction with Compound I was significantly faster (k2 ≫ k3). As a consequence, the enzyme is trapped in the Compound II state. They reversibly inactivated the enzyme blocking the harmful halogenation activity of MPO by transferring it to the MPO peroxidase cycle. In the present study, 8 active and reversible MPO inhibitors were selected. They act as electron donors of the oxidoreductase and efficiently block the halogenation activity with reversible inactivation. Two of the selected compounds have a submicromolar activity and inhibit MPO-dependent LDL oxidation. The high-throughput virtual screening was proved to be a successful tool to find new leads of MPO inhibitors. Conducting HTVS on a large-scale database enabled selection of novel scaffolds of MPO inhibitors never explored before in less time and at less expenses.Finding 8 new different chemical scaffolds through the first step of this drug discovery process led us to choose a new hit, compound A1, which has a hexahydropyrimidine structure, compound F9 was not chosen despite being more active due to its similarity to compounds discovered by AstraZeneca. To conduct pharmacomodulation, a validation of the docking procedure was conducted by comparing the X-ray structures of MPO with 2-(3,5-bistrifluoromethylbenzylamino)-6-oxo-1H-pyrimidine-5- carbohydroxamic acid, HX1, and SHA in the X-ray structures of human MPO in complex with cyanide and thiocyanate (PDB code 1DNW) as well as in complex with HX1 (PDB code 4C1M). Compound A1 was docked into both target structures 1DNW and 4C1M. In both cases, A1 showed almost the same poses.Based on the binding modes of A1, different strategies were developed for the design of derivatives which were mainly focused on the substitution of the aromatic rings A and B, the 2 amino groups and the side chain bridges.Pharmacomodulation was carried out on the hit A1 with different strategies:─ Investigating the role of hydroxyl groups on both aromatic rings─ Shifting the position of the amino groups in the hexahydropyrimidine ring to obtain piperazine derivatives and introduction of fluorine ─ Eliminating of one ring and of an amino group in the hexahydropyrimidine ring leading to piperidine derivatives ─ Opening the hexahydropyrimidine ring while keeping amine function and changing the length of the bridge between this amino group and aromatic ring as well as the impact of substitutions on aromatic rings.─ Hybridization of fluorotryptamine derivatives (effective MPO inhibitors) with hit A1.Based on of the docking experiments, 37 designed compounds were synthesized. The assessment of inhibition of the chlorination activity of MPO was undertaken over the 37 compounds. The hit A1 IC50 = 500 nM. The best compounds inhibiting MPO exhibited the following characteristics:─ One amino group on the bridge between aromatic rings was sufficient for the establishment of binding to Glu102 ─ The presence of three methylene groups between the secondary amine and an aromatic ring improved the inhibition of chlorination and thus decreased the IC50 values. These results showed that the position of the hydroxyl group is important. The distance between the hydrogen bond acceptor (HBA) group of one aromatic ring and the amino group is very important. The docking experiments of bisarylpropylamine derivatives showed ionic and hydrogen bonding interactions between Glu102 and hydroxyl group on aromatic ring linked to the longer side chain.─ Hybridized compounds which carry a fluorotryptamine instead of the phenol ring obtained by hybridization of hit A1 and the potent MPO inhibitors fluorotryptamine derivatives. Actually, compound 38 (which had one aromatic ring and a propyl bridge attached to indole ring) had an IC50 = 54 nM which was 10 times more powerful than the starting hit.The 3 best compounds were tested to examine the transient kinetics. They act as electron donors of the oxidoreductase and efficiently shift MPO from the chlorination cycle to the peroxidase cycle. Due to the similarity of the best compound 38 to serotonin it was tested with the two other best compounds on serotonin transporter (SERT) to examine the selectivity between MPO and SERT.Compound 38 had higher selectivity over MPO but the best selective compound was 28 that contains two aromatic rings carrying one hydroxyl and one fluorine.Electron density maps were conducted to predict the site of oxidation. Results suggested it occurs preferentially at the benzene ring or the indole ring in the best compounds.Determination of redox potentials for the synthesized compounds were tested. Best compounds act as electron donors allowing a one-electron reduction of Compound I.In conclusion, the present study succeeded through rational drug design including structure-based drug design and HTVS to identify new chemical entities for MPO inhibition. Eight compounds were more active than the starting hit A1 with submicromolar inhibition potency. Hybridization and structure based design also gave improvement of selectivity of inhibitors against MPO such as compound 38. Bis-arylalkylamine derivatives are a new group of MPO inhibitors with higher selectivity which could be a new hit for future development. / Doctorat en Sciences biomédicales et pharmaceutiques (Pharmacie) / info:eu-repo/semantics/nonPublished

京都大学 / 0048 / 新制・課程博士 / 博士(薬科学) / 甲第18221号 / 薬科博第25号 / 新制||薬科||4(附属図書館) / 31079 / 京都大学大学院薬学研究科医薬創成情報科学専攻 / (主査)教授 掛谷 秀昭, 教授 高須 清誠, 准教授 大野 浩章 / 学位規則第4条第1項該当 / Doctor of Pharmaceutical Sciences / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第21425号 / 工博第4535号 / 京都大学大学院工学研究科合成・生物化学専攻 / (主査)教授 浜地 格, 教授 杉野目 道紀, 教授 秋吉 一成 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

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