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The Global ETD Search service is a free service for researchers
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Développement et applications d’un outil bio-informatique pour la détection de similarités de champs d’interaction moléculaire / Development and applications of a bioinformatic tool to detect molecular interaction field similaritiesChartier, Matthieu January 2016 (has links)
Résumé : Les méthodes de détection de similarités de sites de liaison servent entre autres à la prédiction de fonction et à la prédiction de cibles croisées. Ces méthodes peuvent aider à prévenir les effets secondaires, suggérer le repositionnement de médicament existants, identifier des cibles polypharmacologiques et des remplacements bio-isostériques. La plupart des méthodes utilisent des représentations basées sur les atomes, même si les champs d’interaction moléculaire (MIFs) représentent plus directement ce qui cherche à être identifié.
Nous avons développé une méthode bio-informatique, IsoMif, qui détecte les similarités de MIF entre différents sites de liaisons et qui ne nécessite aucun alignement de séquence ou de structure. Sa performance a été comparée à d’autres méthodes avec des bancs d’essais, ce qui n’a jamais été fait pour une méthode basée sur les MIFs. IsoMif performe mieux en moyenne et est plus robuste. Nous avons noté des limites intrinsèques à la méthodologie et d’autres qui proviennent de la nature. L’impact de choix de conception sur la performance est discuté.
Nous avons développé une interface en ligne qui permet la détection de similarités entre une protéine et différents ensembles de MIFs précalculés ou à des MIFs choisis par l’utilisateur. Des sessions PyMOL peuvent être téléchargées afin de visualiser les similarités identifiées pour différentes interactions intermoléculaires.
Nous avons appliqué IsoMif pour identifier des cibles croisées potentielles de drogues lors d’une analyse à large échelle (5,6 millions de comparaisons). Des simulations d’arrimage moléculaire ont également été effectuées pour les prédictions significatives. L’objectif est de générer des hypothèses de repositionnement et de mécanismes d’effets secondaires observés. Plusieurs exemples sont présentés à cet égard. / Abstract : Methods that detect binding site similarities between proteins serve for the prediction of function and the identification of potential off-targets. These methods can help prevent side-effects, suggest drug repurposing and polypharmacological strategies and suggest bioisosteric replacements. Most methods use atom-based representations despite the fact that molecular interaction fields (MIFs) represents more closely the nature of what is meant to be identified. We developped a computational algorithm, IsoMif, that detects MIF similarities between binding sites. We benchmark IsoMif to other methods which has not been previously done for a MIF-based method. IsoMif performed best in average and more consistently accross datasets. We highlight limitations intrinsic to the methodology or to nature. The impact of design choices on performance is discussed.
We built a freely available web interface that allows the detection of similarities between a protein and pre-calculated MIFs or user defined MIFs. PyMOL sessions can be downloaded to visualize similarities for the different intermolecular interactions.
IsoMif was applied for a large-scale analysis (5,6 millions of comparisons) to predict offtargets of drugs. Docking simulations of the drugs in the binding site of their top hits were performed. The primary objective is to generate hypotheses that can be further investigated and validated regarding drug repurposing opportunities and side-effect mechanisms.
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Development and applications of new 3D molecular descriptorsFontaine, Fabien 14 January 2005 (has links)
Con el fin de relacionar la estructura y la actividad de series de compuestos, es importante usar descriptores moleculares relevantes. Los descriptores GRIND y VolSurf pertenecen a una nueva familia de descriptores llamado libre de alineamiento. Es decir, que no necesitan alinear los compuestos con el fin de comparar sus campos de interacciones molecular. En este estudio se ha aplicado esos descriptores para la selección de reactivos químicos a partir de una amplia base de datos. La selección se ha echo mediante un protocolo que permite maximizar la diversidad de la muestra y así obtener unos compuestos muy informativos. También se ha desarrollado nuevos descriptores de forma que están basado en los cambios de curvatura de la superficie molecular. Los resultados obtenidos indican que los nuevos descriptores de forma se integran muy bien en los descriptores GRIND originales y que permiten identificar los efectos de forma tanto favorable como desfavorable. Además, se ha desarrollado nuevos descriptores libre de alineamiento llamado 'anchor-GRIND' que usan un átomo de cada molécula como punto de referencia para la comparación de los campos de interacciones molecular. Los descriptores 'anchor-GRIND' permiten una descripción mas precisa y mas sencilla que los descriptores GRIND lo que los hace mas relevante para el análisis de ciertas familias de compuestos. / In order to correlate the differences of structure with the differences of activity of series of compounds, it is important to use relevant molecular descriptors. The GRIND and VolSurf descriptors belong to the so-called alignment-free descriptors family. In other words, they do not require to align the compounds in order to compare its molecular interaction fields. In this study, we applied these descriptors to the selection of chemical reagent from a database of compounds. The selection has been done following a protocol which allows to maximize the diversity of the sample and so to obtain some compounds highly informative. In addition we developed new shape descriptors which are based on the changes of curvature of the molecular surface. The results obtained show that the new shape descriptors are well integrated in the original GRIND descriptors. Furthermore, we designed new alignment-free descriptors called 'anchor-GRIND' which use one atom of each molecule as a reference point for the comparison of the molecular interaction fields. The 'anchor-GRIND' descriptors allow a more precise and more simple description than the GRIND descriptors, which makes them more relevant for the analysis of some families of compounds.
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Estudos de HQSAR, acoplamento molecular e cálculos de propriedades eletrônicas de compostos com atividade biológica frente aos alvos DPP-IV e FAPaMartins, Michelle Cristiane Melo Reis January 2018 (has links)
Orientadora: Profa. Dra. Káthia Maria Honório / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Ciência e Tecnologia/Química, Santo André, 2018. / Um dos alvos biologicos relacionado ao controle da glicemia e a enzima dipeptidil peptidase-IV (DPP-IV); ela esta associada com a estimulacao do pancreas na producao de insulina, sendo, portanto, um alvo de interesse da pesquisa e da industria farmaceutica para o tratamento do diabetes tipo 2. O diabetes e uma doenca cronica que se caracteriza por um aumento da glicemia causando uma serie de complicacoes fisiologicas com destaque para as doencas cardiacas como a aterosclerose; estima-se que 425 milhoes de pessoas sejam portadoras da doenca. Estudos indicam que inibidores da DPP-IV tambem podem apresentar acao sobre a FAP¿¿, uma enzima que esta relacionada com reparacao de tecidos e crescimento de tumores. Este trabalho consiste em utilizar metodos de modelagem molecular, como a construcao e analise de modelos de HQSAR (Hologram Quantitative Structure-Activity) e de CoMFA (analise comparativa de campos de interacao molecular); acoplamento molecular (docking), analise de propriedades eletronicas e deteccao e caracterizacao de sitios de ligacao da enzima FAP¿¿, com intuito de compreender as principais caracteristicas de ambas as enzimas, assim como a interacao das mesmas com uma serie de compostos bioativos. Os modelos CoMFA construidos apresentaram significativos valores de validacao interna (0,768) e externa (0,986); o alinhamento obtido utilizando a tecnica de acoplamento molecular e complementada com o uso da tecnica BINANA delineou as principais interacoes das enzimas com o conjunto de ligantes; identificou-se tres sitios de ligacao da enzima FAP¿¿ utilizando os servidores FTSite e FTMap. Desta forma, com informacoes sobre ambos os alvos e as interacoes estabelecidas com os ligantes, sera possivel propor com maior seguranca modificacoes moleculares para tais compostos candidatos a farmacos mais seguros para o tratamento do diabetes tipo 2. / One of the biological targets related to glycemic control is the dipeptidyl peptidase IV (DPP-IV) enzyme; it is associated with stimulation of the pancreas in insulin production and it is a target of interest for the researches related to the treatment of type 2 diabetes. Diabetes is a chronic disease characterized by an increase in blood glucose causing a series of physiological complications such as atherosclerosis, it is estimated that 425 million people have this disease. Studies have indicated that DPP-IV inhibitors may also have action on FAPá, an enzyme that is related to tissue repair and tumor growth. This work consists of using molecular modeling methods, such as the construction and analysis of HQSAR (Hologram Quantitative Structure-Activity) and CoMFA (comparative analysis of molecular interaction fields) models; molecular docking, analysis of electronic properties, detection and characterization of FAPá enzyme binding sites, and pharmacokinetic and pharmacodynamic properties studies; in order to understand the main characteristics of both enzymes, as well as their interaction with a series of bioactive compounds. The CoMFA models presented significant values of internal validation (0,768) and external (0,986) and the alignment obtained using the molecular docking technique outlined the main interactions of the enzymes with the set of ligands. With information on both targets and the interactions established with the ligands, it will be possible to more safely propose molecular modifications for such safer drug candidates for the treatment of type 2 diabetes.
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Development of high-performance algorithms for a new generation of versatile molecular descriptors. The Pentacle softwareDurán Alcaide, Ángel 04 March 2010 (has links)
The work of this thesis was focused on the development of high-performance algorithms for a new generation of molecular descriptors, with many advantages with respect to its predecessors, suitable for diverse applications in the field of drug design, as well as its implementation in commercial grade scientific software (Pentacle). As a first step, we developed a new algorithm (AMANDA) for discretizing molecular interaction fields which allows extracting from them the most interesting regions in an efficient way. This algorithm was incorporated into a new generation of alignmentindependent molecular descriptors, named GRIND-2. The computing speed and efficiency of the new algorithm allow the application of these descriptors in virtual screening. In addition, we developed a new alignment-independent encoding algorithm (CLACC) producing quantitative structure-activity relationship models which have better predictive ability and are easier to interpret than those obtained with other methods. / El trabajo que se presenta en esta tesis se ha centrado en el desarrollo de algoritmos de altas prestaciones para la obtención de una nueva generación de descriptores moleculares, con numerosas ventajas con respecto a sus predecesores, adecuados para diversas aplicaciones en el área del diseño de fármacos, y en su implementación en un programa científico de calidad comercial (Pentacle). Inicialmente se desarrolló un nuevo algoritmo de discretización de campos de interacción molecular (AMANDA) que permite extraer eficientemente las regiones de máximo interés. Este algoritmo fue incorporado en una nueva generación de descriptores moleculares independientes del alineamiento, denominados GRIND-2. La rapidez y eficiencia del nuevo algoritmo permitieron aplicar estos descriptores en cribados virtuales. Por último, se puso a punto un nuevo algoritmo de codificación independiente de alineamiento (CLACC) que permite obtener modelos cuantitativos de relación estructura-actividad con mejor capacidad predictiva y mucho más fáciles de interpretar que los obtenidos con otros métodos.
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