MOTIVATION: Identification of small molecules that could be interesting starting points for drug discovery or to investigate a biological system as in chemical biology endeavours is both time consuming and costly. In silico approaches that assist the design of quality compound collections or help to prioritize molecules before synthesis or purchase are therefore valuable. Here quality refers to the selection of molecules that pass one or several selected filters that can be tuned by the users according to the project and the stage of the project. These filters can involve prediction of physicochemical properties, search for toxicophores or other unwanted chemical groups. RESULTS: FAF-Drugs4 is a novel version of our online server dedicated to the preparation and annotation of compound collections. The tool is now faster and several parameters have been optimized. In addition, a new service referred to as FAF-QED, an implementation of the quantitative estimate of drug-likeness method, is now available. AVAILABILITY AND IMPLEMENTATION: The server is available at http://fafdrugs4.mti.univ-paris-diderot.fr. CONTACT: Bruno.Villoutreix@inserm.fr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: Identification of small molecules that could be interesting starting points for drug discovery or to investigate a biological system as in chemical biology endeavours is both time consuming and costly. In silico approaches that assist the design of quality compound collections or help to prioritize molecules before synthesis or purchase are therefore valuable. Here quality refers to the selection of molecules that pass one or several selected filters that can be tuned by the users according to the project and the stage of the project. These filters can involve prediction of physicochemical properties, search for toxicophores or other unwanted chemical groups. RESULTS: FAF-Drugs4 is a novel version of our online server dedicated to the preparation and annotation of compound collections. The tool is now faster and several parameters have been optimized. In addition, a new service referred to as FAF-QED, an implementation of the quantitative estimate of drug-likeness method, is now available. AVAILABILITY AND IMPLEMENTATION: The server is available at http://fafdrugs4.mti.univ-paris-diderot.fr. CONTACT: Bruno.Villoutreix@inserm.fr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Nicolas Bosc; Christophe Muller; Laurent Hoffer; David Lagorce; Stéphane Bourg; Carine Derviaux; Marie-Edith Gourdel; Jean-Christophe Rain; Thomas W Miller; Bruno O Villoutreix; Maria A Miteva; Pascal Bonnet; Xavier Morelli; Olivier Sperandio; Philippe Roche Journal: ACS Chem Biol Date: 2020-05-05 Impact factor: 5.100
Authors: Lu Bai; Lia A Parkin; Hong Zhang; Rebecca Shum; Mary L Previti; Jessica C Seeliger Journal: ACS Infect Dis Date: 2020-03-03 Impact factor: 5.084
Authors: Gyan Modi; Gary M Marqus; Mohana Rao Vippila; Deviprasad R Gollapalli; Youngchang Kim; Adhar C Manna; Shibin Chacko; Natalia Maltseva; Xingyou Wang; Ryan T Cullinane; Yubo Zhang; Judy L M Kotler; Petr Kuzmic; Minjia Zhang; Ann P Lawson; Andrzej Joachimiak; Ambrose Cheung; Barry B Snider; David M Rothstein; Gregory D Cuny; Lizbeth Hedstrom Journal: ACS Infect Dis Date: 2021-09-30 Impact factor: 5.578
Authors: Karthikeyan Mohanraj; Bagavathy Shanmugam Karthikeyan; R P Vivek-Ananth; R P Bharath Chand; S R Aparna; Pattulingam Mangalapandi; Areejit Samal Journal: Sci Rep Date: 2018-03-12 Impact factor: 4.379