A Hybrid Classification Approach based on FCA and Emerging Patterns - An application for the classification of biological inhibitors

International audienceClassification is an important task in data analysis and learning. Classification can be performed using supervised or unsupervised methods. From the unsupervised point of view, Formal Concept Analysis (FCA) can be used for such a task in an efficient and well-founded way. From the supervised point of view, emerging patterns rely on pattern mining and can be used to characterize classes of objects w.r.t. a priori labels. In this paper, we present a hybrid classification method which is based both on supervised and unsupervised aspects. This method relies on FCA for building a concept lattice and then detects the concepts whose extents determines classes of objects sharing the same labels. These classes can then be used as reference classes for classifying unknown objects. This hybrid approach has been used in an experiment in chemistry for classifying inhibitors of the c-Met protein which plays an important role in protein interactions and in the development of cancer

Conception par modélisation et criblage in silico d'inhibiteurs du récepteur c-Met

The challenge of this PhD work is the in silico identification of potentially interesting molecules concerning the inhibitory process of tyrosine kinase receptor c-Met. The faculty of this protein to interact in embryogenesis and tissue repair phenomena makes its inhibition crucial for treatments against tumor development in which c-Met is involved. For that purpose, the employed strategy involves the use of several in silico methods for rational drug design. As the basement of this work, we used the multiple crystal structures published in the ProteinData Base (PDB). A preliminary homology modeling work was needed to fill gaps in the crystal structures. To sample at best the c-Met kinase conformational space and to characterize its flexibility, a long Molecular Dynamics (MD) simulation campaign was carried out both on apo and holo forms of available crystal structures. To complete these simulations, part of this work consisted to use normal modes of vibration (NM) method. From these two approaches (DM and NM), we extracted a set of 10 conformers considered as the most representative of the kinase simulated conformational space and we suggested a mode of operation of this kinase. Using extracted conformations from the conformational sampling has enabled us to conduct an extensive campaign on several virtual screening libraries constituting a total of approximately 70,000 compounds. Analysis of the molecular docking results has led us to the selection of several theoretically interesting molecules with good potential affinity for c-Met kinase. These molecules were submitted to experimental tests performed by the biologist team associated to our work.L'enjeu des travaux effectués au cours de cette thèse est l'extraction in silico de molécules potentiellement intéressantes dans le processus d'inhibition du récepteur tyrosine kinase c-Met. La faculté de cette protéine à interagir dans les phénomènes d'embryogenèse et de réparation tissulaires rendent son inhibition cruciale dans les traitements contre les développements tumoraux où c-Met se trouve impliquée. Dans ce but, la stratégie que nous avons employée implique l'utilisation de plusieurs méthodes in silico de conception rationnelle de médicaments. Nous avons utilisé comme support les multiples structures cristallographiques publiées sur la ProteinData Base (PDB). Un travail de modélisation par homologie fut tout d'abord nécessaire pour combler les lacunes des structures cristallographiques collectées. Afin d'échantillonner au mieux l'espace conformationnel du récepteur kinase c-Met et de caractériser sa flexibilité, une longue campagne de simulation de Dynamique Moléculaire (DM) fut menée concernant les formes apo et holo des structures cristallographiques disponibles. Pour compléter ces simulations, une partie du travail consista à utiliser également la méthode des modes normaux de vibration (NM). De ces 2 approches (DM et NM), nous avons extrait un ensemble de 10 conformères considérés comme les plus représentatifs de l'espace conformationnel simulé pour la kinase c-Met et avons proposé un mode de fonctionnement de ce récepteur. Utilisant les conformations extraites de l'échantillonnage conformationnel, nous avons ensuite mené une importante campagne de criblage virtuel sur plusieurs chimiothèques constituant au total environ 70.000 composés. L'analyse des résultats de l'arrimage moléculaire nous a conduits à la sélection de plusieurs molécules intéressantes possédant théoriquement une bonne affinité pour la kinase c-Met. Ces molécules ont été soumises aux tests expérimentaux effectués par l'équipe de biologistes associée à nos travaux

C-Met receptor inhibitors design by molecular modeling and in silico screening

L'enjeu des travaux effectués au cours de cette thèse est l'extraction in silico de molécules potentiellement intéressantes dans le processus d'inhibition du récepteur tyrosine kinase c-Met. La faculté de cette protéine à interagir dans les phénomènes d'embryogenèse et de réparation tissulaires rendent son inhibition cruciale dans les traitements contre les développements tumoraux où c-Met se trouve impliquée. Pour cela, la stratégie employée implique l'utilisation de méthodes in silico de conception rationnelle de médicaments. Nous avons utilisé comme support les multiples structures cristallographiques publiées sur la ProteinData Base. Un travail de modélisation par homologie fut tout d'abord nécessaire pour combler les lacunes des structures cristallographiques collectées. Afin d'échantillonner au mieux l'espace conformationnel de la kinase c-Met et de caractériser sa flexibilité, une longue campagne de simulation de Dynamique Moléculaire fut menée. Pour compléter ces simulations, nous avons également utilisé la méthode des modes normaux de vibration. De ces 2 approches, nous avons extrait un ensemble de 10 conformères considérés comme les plus représentatifs de l'espace conformationnel simulé pour la kinase c-Met et avons proposé un mode de fonctionnement de ce récepteur. Utilisant les conformations représentatives, nous avons ensuite mené une importante campagne de criblage virtuel sur plusieurs chimiothèques constituant environ 70.000 composés. L'analyse des résultats de l'arrimage moléculaire nous a conduits à la sélection de composés intéressants possédant théoriquement une bonne affinité pour la kinase c-Met. Ces molécules ont été soumises aux tests expérimentaux.The challenge of this PhD work is the in silico identification of potentially interesting molecules concerning the inhibitory process of tyrosine kinase receptor c-Met. The faculty of this protein to interact in embryogenesis and tissue repair phenomena makes its inhibition crucial for treatments against tumor development in which c-Met is involved. For that purpose, the employed strategy involves the use of several in silico methods for rational drug design. As the basement of this work, we used the multiple crystal structures published in the ProteinData Base (PDB). A preliminary homology modeling work was needed to fill gaps in the crystal structures. To sample at best the c-Met kinase conformational space and to characterize its flexibility, a long Molecular Dynamics (MD) simulation campaign was carried out both on apo and holo forms of available crystal structures. To complete these simulations, part of this work consisted to use normal modes of vibration (NM) method. From these two approaches (DM and NM), we extracted a set of 10 conformers considered as the most representative of the kinase simulated conformational space and we suggested a mode of operation of this kinase. Using extracted conformations from the conformational sampling has enabled us to conduct an extensive campaign on several virtual screening libraries constituting a total of approximately 70,000 compounds. Analysis of the molecular docking results has led us to the selection of several theoretically interesting molecules with good potential affinity for c-Met kinase. These molecules were submitted to experimental tests performed by the biologist team associated to our work

Exploring c-Met kinase flexibility by sampling and clustering its conformational space

International audienceIt is now widely recognized that the flexibility of both partners has to be considered in molecular docking studies. However, the question how to handle the best the huge computational complexity of exploring the protein binding site landscape is still a matter of debate. Here we investigate the flexibility of c-Met kinase as a test case for comparing several simulation methods. The c-Met kinase catalytic site is an interesting target for anticancer drug design. In particular, it harbors an unusual plasticity compared with other kinases ATP binding sites. Exploiting this feature may eventually lead to the discovery of new anticancer agents with exquisite specificity. We present in this article an extensive investigation of c-Met kinase conformational space using large-scale computational simulations in order to extend the knowledge already gathered from available X-ray structures. In the process, we compare the relevance of different strategies for modeling and injecting receptor flexibility information into early stage in silico structure-based drug discovery pipeline. The results presented here are currently being exploited in on-going virtual screening investigations on c-Met

Recent Trends and Applications in 3D Virtual Screening

International audienceVirtual screening (VS) is becoming an increasingly important approach for identifying and selecting biologically active molecules against specific pharmaceutically relevant targets. Compared to conventional high throughput screening techniques, in silico screening is fast and inexpensive, and is increasing in popularity in early-stage drug discovery endeavours. This paper reviews and discusses recent trends and developments in three-dimensional (3D) receptor-based and ligand-based VS methodologies. First, we describe the concept of accessible chemical space and its exploration. We then describe 3D structural ligand-based VS techniques, hybrid approaches, and new approaches to exploit additional knowledge that can now be found in large chemogenomic databases. We also briefly discuss some potential issues relating to pharmacokinetics, toxicity profiling, target identification and validation, inverse docking, scaffold-hopping and drug re-purposing. We propose that the best way to advance the state of the art in 3D VS is to integrate complementary strategies in a single drug discovery pipeline, rather than to focus only on theoretical or computational improvements of individual techniques. Two recent 3D VS case studies concerning the LXR-β receptor and the CCR5/CXCR4 HIV co-receptors are presented as examples, which implement some of the complementary methods and strategies that are reviewed here

Identification of new aminoacid amides containing the imidazo[2,1-b]benzothiazol-2-ylphenyl moiety as inhibitors of tumorigenesis by oncogenic Met signaling.

18The Met receptor tyrosine kinase is a promising target in anticancer therapies for its role during tumor evolution and resistance to treatment. It is characterized by an unusual structural plasticity as its active site accepts different inhibitor binding modes. Such feature can be exploited to identify distinct agents targeting tumor dependence and/or resistance by oncogenic Met. Here we report the identification of bioactive agents, featuring a new 4-(imidazo[2,1-b]benzothiazol-2-yl)phenyl moiety, targeting cancer cells dependent on oncogenic Met. One of these compounds (7c; Triflorcas) impairs survival, anchorage-independent growth, and in vivo tumorigenesis, without showing side effects. Our medicinal chemistry strategy was based on an in-house Met-focused library of aminoacid-amide derivatives enriched through structure-based computer modeling, taking into account the Met multiple-binding-mode feature. Altogether, our findings show how a rational structure-based drug design approach coupled to cell-based drug evaluation strategies can be applied in medicinal chemistry to identify new agents targeting a given oncogenic-dependency setting. Copyright © 2011 Elsevier Masson SAS. All rights reserved.reservedmixedFurlan, A.; Colombo, F.; Kover, A.; Issaly, N.; Tintori, Cristina; Angeli, Lucilla; Leroux, V.; Letard, S.; Amat, M.; Asses, Y.; Maigret, B.; Dubreuil, P.; Botta, Maurizio; Dono, R.; Bosch, J.; Piccolo, O.; Passarella, D.; Maina, F.Furlan, A.; Colombo, F.; Kover, A.; Issaly, N.; Tintori, Cristina; Angeli, Lucilla; Leroux, V.; Letard, S.; Amat, M.; Asses, Y.; Maigret, B.; Dubreuil, P.; Botta, Maurizio; Dono, R.; Bosch, J.; Piccolo, O.; Passarella, D.; Maina, F