A Chemographic Audit of anti-Coronavirus Structure-activity Information from Public Databases (ChEMBL).
Mol Inform
; 39(12): e2000080, 2020 12.
Article
in English
| MEDLINE | ID: covidwho-165203
Preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
ABSTRACT
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 800â
M organic compounds.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Antiviral Agents
/
Viral Proteins
/
Computer Simulation
/
Coronavirus Infections
/
Quantitative Structure-Activity Relationship
/
Drug Discovery
Type of study:
Prognostic study
Limits:
Animals
/
Humans
Language:
English
Journal:
Mol Inform
Year:
2020
Document Type:
Article
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