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A Chemographic Audit of anti‐Coronavirus Structure‐activity Information from Public Databases (ChEMBL)
Author(s) -
Horvath Dragos,
Orlov Alexey,
Osolodkin Dmitry I.,
Ishmukhametov Aydar A.,
Marcou Gilles,
Varnek Alexandre
Publication year - 2020
Publication title -
molecular informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 68
eISSN - 1868-1751
pISSN - 1868-1743
DOI - 10.1002/minf.202000080
Subject(s) - chembl , chemical space , audit , computer science , coronavirus , data science , covid-19 , drug discovery , computational biology , biology , bioinformatics , medicine , business , accounting , disease , pathology , infectious disease (medical specialty)
Discovery of drugs against newly emerged pathogenic agents like the SARS‐CoV‐2 coronavirus (CoV) must be based on previous research against related species. Scientists need to get acquainted with and develop a global oversight over so‐far tested molecules. Chemography (herein used Generative Topographic Mapping, in particular) places structures on a human‐readable 2D map (obtained by dimensionality reduction of the chemical space of molecular descriptors) and is thus well suited for such an audit. The goal is to map medicinal chemistry efforts so far targeted against CoVs. This includes comparing libraries tested against various virus species/genera, predicting their polypharmacological profiles and highlighting often encountered chemotypes. Maps are challenged to provide predictive activity landscapes against viral proteins. Definition of “anti‐CoV” map zones led to selection of therein residing 380 potential anti‐CoV agents, out of a vast pool of 800 M organic compounds.