Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)

Conception de ligands inhibiteurs de MT5-MMP (MMP-24) : implication dans le traitement de la maladie d'Alzheimer

Alzheimer’s Disease (AD) is lacking any curing therapy. Among the damages of AD we can find aggregated β-amyloid peptides in senile plaques. These peptides derive from the amyloid precursor protein (APP) cleavage by the β- et γ-secretases. Another APP metabolic pathway, the η-secretase pathway, is of interest for AD therapeutic novelties. This pathway leads to the secretion of neurotoxic peptides in the hippocampus, which is the site of long-term memory. η-secretase is a trans-membrane matrix metalloproteinase (MT-MMP). In the central nervous system, the η-secretase corresponds to MT5-MMP (or MMP-24). Genetic knockout of MT5-MMP shows a curative interest in AD in vivo models. However, MT5-MMP structural data are still lacking and this hinders the conception of potentially MT5-MMP inhibitory drugs. In 2016, the CERMN constructed an in silico model of the MT5-MMP catalytic domain, which allowed to discover a hit for the conception and synthesis of an inhibitory ligand of MT5-MMP. In this present work, the challenge was to assess several Ligand-Target binding mode hypotheses in order to propose pharmacomodulations. This is an in silico project. This manuscript is divided into three parts and proposes first a presentation of the Matrix Metalloproteinases and AD, second a presentation of the involvement of Chemoinformatics in Drug Design, and finally a presentation of the work of designing MT5-MMP inhibitory ligands for AD.La maladie d'Alzheimer (MA) fait état d’un manque de thérapie curative. Parmi les lésions de cette pathologie, on retrouve des peptides β-amyloïdes agrégés en plaques séniles. Ces peptides sont issus de la dégradation de la protéine précurseur de l’amyloïde (APP) selon les voies des β- et γ-sécrétases. Une autre voie de métabolisation de l’APP, celle de la η-sécrétase, présente un intérêt en termes de nouveautés thérapeutiques pour la MA. Cette voie entraîne la sécrétion de peptides neurotoxiques et ce principalement au niveau hippocampique, siège de la mémoire à long terme. La η-sécrétase est une Métalloprotéase Matricielle Transmembranaire (MT-MMP). Au niveau central, la η-sécrétase correspond à la MT5-MMP (ou MMP-24). L’inhibition de la MT5-MMP par invalidation génique montre un intérêt curatif dans les modèles in vivo de MA. Cependant, les données structurales de la MMP-24 sont encore inconnues, et cela freine la conception de principes actifs inhibiteurs de celle-ci. Le CERMN a mis au point en 2016 un modèle in silico du domaine catalytique de MT5-MMP ayant permis de disposer d’un hit pour la conception et la synthèse d’un ligand inhibiteur de MT5-MMP. L’enjeu ici a été d’étudier différentes hypothèses de mode de liaison Ligand-Cible pour proposer des pharmacomodulations. Ceci est un travail réalisé in silico. Le manuscrit se divise en trois parties et propose, dans l’ordre, un exposé sur les protéines de la famille des Métalloprotéases Matricielles et sur la MA, puis un exposé sur l’implication de la Chémoinformatique dans les projets de conception de médicaments et enfin un exposé du travail de conception de ligands inhibiteurs de MT5-MMP

Conception, synthèse et caractérisation de perturbateurs des interactions protéine-protéine liées aux phénomènes précoces amyloïdogéniques dans la maladie d’Alzheimer

Les tauopathies, dont la maladie d'Alzheimer (MA), sont des maladies neurodégénératives caractérisées par la présence de dégénérescences neurofibrillaires (DNF). Les DNF sont liées à une agrégation anormale de la protéine tau. Des séquences peptidiques clés ont été identifiées comme responsables de l'oligomérisation précoce, initiant l'ensemble du processus amyloïdogénique. Elles adoptent une structuration en feuillets β et s'empilent, initiant ainsi l'agrégation de la protéine. Notre but est de synthétiser de petites molécules perturbatrices des interactions protéine-protéine afin d'empêcher l'agrégation précoce de la protéine tau. Ce travail a été initié par une analyse conformationnelle de l'hexapeptide clé de la protéine tau impliqué dans l'agrégation, appelé PHF6 (pour Paired Helical Filament hexapeptide). Nous avons construit des agrégats PHF6 et évalué leur stabilité par des simulations de dynamique moléculaire et des analyses des interactions intra et intermoléculaires. Ensuite, nous avons lancé des simulations de ces agrégats de PHF6 avec un perturbateur de l'agrégation de la protéine tau et proposé des mécanismes de perturbation de l'agrégation.Ensuite, un criblage par similarité de notre chimiothèque interne basé sur la structure de la palmatine et des tests in vitro ont fourni 40 structures comme points de départ pour la conception rationnelle et la synthèse de petites molécules susceptibles de perturber les interactions entre les fibrilles amyloïdes. Enfin, nous avons mis en place un nouveau type de simulation en 3D pour comprendre le processus d'agrégation précoce de la protéine tau, qui met en évidence l'agrégation progressive du peptide PHF6 initialement désordonné. Cette simulation a également été réalisée avec deux composés afin d'évaluer leur capacité d'inhibition de l'agrégation à des stades très précoces.Tauopathies, including Alzheimer’s disease (AD), are neurodegenerative diseases characterized by the presence of neurofibrillary tangles (NFTs). NFTs are related to abnormal tau protein aggregation. Key-peptide sequences were identified as responsible for early oligomerization, initiating the whole amyloidogenic process. They adopt a β-sheet structuration and pile themselves up, guiding the protein aggregation initiation. We are aiming to synthesize small molecules as protein-protein interaction disruptors in order to prevent early stage of tau protein aggregation. The presentwork was initiated by a conformational analysis of tau protein key hexapeptide implied in aggregation, called PHF6 (for Paired Helical Filament hexapeptide). We built preformed PHF6 aggregates and assessed their stabilities through molecular dynamics simulations and analyses of intra and intermolecular interactions. Then, MD simulations of PHF6 aggregates with a tau protein aggregation disruptor were launched and mechanisms of aggregation disruption were proposed. Then, similarity screening of our in-house chemical library based on palmatine chloride and in vitro tests provided 40 scaffolds as starting points for the rational design and synthesis of small molecules that could disturb the amyloid fibril interactions. Finally, we set up a new kind of 3D-simulation to comprehend early tau protein aggregation process that brought up together disordered PHF6 peptide gradually aggregating. This simulation was also carried out with two compounds in order to assess their aggregation inhibition capacity in very early stages

Tau protein aggregation: Key features to improve drug discovery screening

Tauopathies are neurodegenerative disorders associated with the accumulation of abnormal tubulin associated unit (tau) protein in the brain. Tau pathologies include a broad spectrum of diseases, with Alzheimer's disease (AD) being the most common tauopathy. The pathophysiological mechanisms of AD are still only partially understood. As a consequence, attempts to establish therapeutic approaches have led to numerous clinical trial failures and, to date, no curative treatment is available for AD despite the considerable number of research programs. Therefore, over the past decade, the aggregation of the tau protein in AD has become a therapeutic target of interest. In this review, we gather in silico, in vitro, and in vivo methodologies that are relevant to assess compounds targeting tau aggregation, from early drug design to clinical trials

Quinazoline-based VEGFR-2 inhibitors as potential anti-angiogenic agents: A contemporary perspective of SAR and molecular docking studies

Angiogenesis, the formation of new blood vessels from the existing vasculature, is pivotal in the migration, growth, and differentiation of endothelial cells in normal physiological conditions. In various types of tumour microenvironments, dysregulated angiogenesis plays a crucial role in supplying oxygen and nutrients to cancerous cells, leading to tumour size growth. VEGFR-2 tyrosine kinase has been extensively studied as a critical regulator of angiogenesis; thus, inhibition of VEGFR-2 has been widely used for cancer treatments in recent years. Quinazoline nucleus is a privileged and versatile scaffold with a broad range of pharmacological activity, especially in the field of tyrosine kinase inhibitors with more than twenty small molecule inhibitors approved by the US Food and Drug Administration in the last two decades. As of now, the U.S. FDA has approved eleven small chemical inhibitors of VEGFR-2 for various types of malignancies, with a prime example being vandetanib, a quinazoline derivative, which is a multi targeted kinase inhibitor used for the treatment of late-stage medullary thyroid cancer. Despite of prosperous discovery and development of VEGFR-2 down regulator drugs, there still exists limitations in clinical efficacy, adverse effects, a high rate of clinical discontinuation and drug resistance. Therefore, there is an urgent need for the design and synthesis of more selective and effective inhibitors to tackle these challenges. Through the gathering of this review, we have strived to broaden the extent of our view over the entire scope of quinazoline-based VEGFR-2 inhibitors. Herein, we give an overview of the importance and advancement status of reported structures, highlighting the SAR, biological evaluations and their binding modes

On the Tracks of the Aggregation Mechanism of the PHF6 Peptide from Tau Protein: Molecular Dynamics, Energy, and Interaction Network Investigations

The formation of neurofibrillary tangles (NFTs), composed of tau protein aggregates, is a hallmark of some neurodegenerative diseases called tauopathies. NFTs are composed of paired helical filaments (PHFs) of tau protein with a dominant β-sheet secondary structuration. The NFT formation mechanism is not known yet. This study focuses on PHF6, a crucial hexapeptide responsible for tau aggregation. A 2 μs molecular dynamics simulation was launched to determine the keys of the PHF6 aggregation mechanism. Hydrogen bonding, van der Waals, and other non-covalent interactions as π-stacking were investigated. Parallel aggregation was slightly preferred due to its adaptability, but antiparallel aggregation remained widely present during the PHF6 aggregation. The analysis highlighted the leading role of hydrogen bonds identified at the atomic level for each aggregation process. The aggregation study emphasized the importance of Tyr310 during the β-sheets’ complexation through π-stacking

On the Tracks of the Aggregation Mechanism of the PHF6 Peptide from Tau Protein: Molecular Dynamics, Energy, and Interaction Network Investigations

The formation of neurofibrillary tangles (NFTs), composed of tau protein aggregates, is a hallmark of some neurodegenerative diseases called tauopathies. NFTs are composed of paired helical filaments (PHFs) of tau protein with a dominant β-sheet secondary structuration. The NFT formation mechanism is not known yet. This study focuses on PHF6, a crucial hexapeptide responsible for tau aggregation. A 2 μs molecular dynamics simulation was launched to determine the keys of the PHF6 aggregation mechanism. Hydrogen bonding, van der Waals, and other non-covalent interactions as π-stacking were investigated. Parallel aggregation was slightly preferred due to its adaptability, but antiparallel aggregation remained widely present during the PHF6 aggregation. The analysis highlighted the leading role of hydrogen bonds identified at the atomic level for each aggregation process. The aggregation study emphasized the importance of Tyr310 during the β-sheets’ complexation through π-stacking

Reliability of baseline self-reported information in the AGRICAN cohort

Purpose: An important challenge in epidemiology is to ensure the reliability of collected data. Very few studies have been conducted in farming populations. We assessed the reliability of self-reported data on lifestyle, reproductive history, health and agricultural activities and tasks from the AGRICAN cohort. Methods: Our analysis focused on 739 individuals from the 181,842 cohort members who completed the questionnaire twice between 2005 and 2007 with a median time interval of 452 days. Consistency in the responses to questionnaire items (lifestyle, health and agricultural activities including pesticide treatments) was assessed by the percentage of exact agreement (PA), Cohen’s Kappa value (K) and the intraclass correlation coefficient (ICC). Results: Agreement was substantial to almost perfect for education, smoking, reproductive history and most health indicators (K/ICC > 0.61). Agreement was moderate for alcohol consumption and fair for diet. Agreement was substantial for animal and crop farming activities and tasks such as pesticide use on crops and protective equipment use (PA 81–99%, K/ICC 0.61–0.96). Most tasks showed moderate to substantial agreement, except a few with low agreement. Substantial to perfect agreement was observed for the duration of tasks, based on exact years of beginning and ending. Conclusion: Farmers’ answers appeared reliable for most occupational data, including data used to assess individual exposure to specific pesticides, and for most potential confounders

Towards a partial order graph for interactive pharmacophore exploration: extraction of pharmacophores activity delta

Abstract This paper presents a novel approach called Pharmacophore Activity Delta for extracting outstanding pharmacophores from a chemogenomic dataset, with a specific focus on a kinase target known as BCR-ABL. The method involves constructing a Hasse diagram, referred to as the pharmacophore network, by utilizing the subgraph partial order as an initial step, leading to the identification of pharmacophores for further evaluation. A pharmacophore is classified as a ‘Pharmacophore Activity Delta’ if its capability to effectively discriminate between active vs inactive molecules significantly deviates (by at least δ standard deviations) from the mean capability of its related pharmacophores. Among the 1479 molecules associated to BCR-ABL binding data, 130 Pharmacophore Activity Delta were identified. The pharmacophore network reveals distinct regions associated with active and inactive molecules. The study includes a discussion on representative key areas linked to different pharmacophores, emphasizing structure–activity relationships