Computational Biology and Chemistry in MTi: Emphasis on the Prediction of Some ADMET Properties

Maria A Miteva; Bruno O Villoutreix

doi:10.1002/minf.201700008

Computational Biology and Chemistry in MTi: Emphasis on the Prediction of Some ADMET Properties

Mol Inform. 2017 Oct;36(10). doi: 10.1002/minf.201700008. Epub 2017 Feb 21.

Authors

Maria A Miteva^{1

2}, Bruno O Villoutreix^{1

2}

Affiliations

¹ Université Paris Diderot, Sorbonne Paris Cité, Molécules ThérapeutiquesIn Silico, Inserm UMR-S 973, 35 rue Helene Brion, 75013, Paris, France.
² INSERM, U973, F-75205, Paris, France.

PMID: 28221002
DOI: 10.1002/minf.201700008

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.

Keywords: 3D-ADMET; ADMET; Molecular Modelling; QSAR; Structural Bioinformatics; Virtual Screening.

Publication types

Review
Research Support, Non-U.S. Gov't

MeSH terms

Computational Biology / methods*
Data Mining
Databases, Factual
Drug Design
Protein Binding