FAF-Drugs4: free ADME-tox filtering computations for chemical biology and early stages drug discovery
Author(s) -
David Lagorce,
Lina Bouslama,
Jérôme Becot,
Maria A. Miteva,
Bruno O. Villoutreix
Publication year - 2017
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btx491
Subject(s) - computer science , adme , drug discovery , chemical space , identification (biology) , in silico , quality (philosophy) , computational biology , data mining , drug , bioinformatics , biology , pharmacology , biochemistry , philosophy , botany , epistemology , gene
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.
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