title: Computational Biology and Chemistry in MTi: Emphasis on the Prediction of Some ADMET Properties.
abstract: Our research and teaching group called MTi (Molécules Thérapeutiques in silico) has developed numerous applications available online, thanks to the RPBS platform (Ressource Parisienne en Bioinformatique Structurale), in the field of chemoinformatics, structural bioinformatics and drug design. Since its opening in 2009, over 200 articles/reviews have been reported and involve virtual screening studies, prediction of druggability, analysis of protein-protein interaction inhibitors, development of databases, data mining and knowledge discovery, as well as combined in silico-in vitro work to search for new hits and chemical probes acting on original targets in several therapeutic areas. An international training program has also been developed pertaining to the field of in silico drug design. In this review, we present some tools developed in our laboratory with a special emphasis on the prediction of some ADMET properties, compound collection preparation and 3D-ADMET computations.
authors.affiliation: Université Paris Diderot, Sorbonne Paris Cité, Molécules ThérapeutiquesIn Silico, Inserm UMR-S 973, 35 rue Helene Brion, 75013, Paris, France.|INSERM, U973, F-75205, Paris, France.
authors.forename: Maria A
authors.initials: MA
authors.lastname: Miteva
authors.affiliation: Université Paris Diderot, Sorbonne Paris Cité, Molécules ThérapeutiquesIn Silico, Inserm UMR-S 973, 35 rue Helene Brion, 75013, Paris, France.|INSERM, U973, F-75205, Paris, France.
authors.forename: Bruno O
authors.initials: BO
authors.lastname: Villoutreix
mesh_terms: D019295:Computational Biology / Q000379:methods*; D057225:Data Mining; D016208:Databases, Factual; D015195:Drug Design; D011485:Protein Binding
keywords: 3D-ADMET; ADMET; Molecular Modelling; QSAR; Structural Bioinformatics; Virtual Screening