CovaDOTS: In Silico Chemistry-Driven Tool to Design Covalent Inhibitors Using a Linking Strategy
Author(s) -
Laurent Hoffer,
Magalí SáezAyala,
Dragos Horvath,
Alexandre Varnek,
Xavier Morelli,
Philippe Roche
Publication year - 2019
Publication title -
journal of chemical information and modeling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.24
H-Index - 160
eISSN - 1549-960X
pISSN - 1549-9596
DOI - 10.1021/acs.jcim.8b00960
Subject(s) - covalent bond , in silico , chemistry , combinatorial chemistry , non covalent interactions , adduct , small molecule , computer science , computational biology , nanotechnology , molecule , biochemistry , organic chemistry , materials science , biology , hydrogen bond , gene
We recently reported an integrated fragment-based optimization strategy called DOTS (Diversity Oriented Target-focused Synthesis) that combines automated virtual screening (VS) with semirobotized organic synthesis coupled to in vitro evaluation. The molecular modeling part consists of hit-to-lead chemistry, based on the growing paradigm. Here, we have extended the applicability of the DOTS strategy by adding new functionalities, allowing a generic chemistry-driven linking approach with a particular emphasis on covalent drugs. Indeed, the covalent mode of action can be described as a specific case of linking, where suitable linkers are sought to fuse a bound organic compound with a nucleophilic protein side chain. The proof of concept is established using three retrospective study cases in which known noncovalent inhibitors have been converted to covalent inhibitors. Our method is able to automatically design reference covalent inhibitors (and/or analogs) from an initial activated substructure and predict their binding mode. More importantly, the reference compounds are ranked high among several hundred putative adducts, demonstrating the utility of the approach to design covalent inhibitors.
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