Evidence map›Paper›PMID 32363750›Full record

ArticleMolecular informatics2020

A Chemographic Audit of anti-Coronavirus Structure-activity Information from Public Databases (ChEMBL).

Dragos Horvath, Alexey Orlov, Dmitry I Osolodkin, Aydar A Ishmukhametov, Gilles Marcou, Alexandre Varnek

Abstract read
In one paragraph

Article in Molecular informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Dragos HorvathChemoinformatics Laboratory, UMR 7140 CNRS/University of Strasbourg, 4, rue Blaise Pascal, 67000, Strasbourg.ORCID http://orcid.org/0000-0003-0173-5714
Alexey OrlovChemoinformatics Laboratory, UMR 7140 CNRS/University of Strasbourg, 4, rue Blaise Pascal, 67000, Strasbourg.
Dmitry I OsolodkinFSBSI "Chumakov FSC R&D IBP RAS", Poselok Instituta Poliomielita 8 bd. 1, Poselenie Moskovsky, Moscow, 108819, Russia.
Aydar A IshmukhametovFSBSI "Chumakov FSC R&D IBP RAS", Poselok Instituta Poliomielita 8 bd. 1, Poselenie Moskovsky, Moscow, 108819, Russia.
Gilles MarcouChemoinformatics Laboratory, UMR 7140 CNRS/University of Strasbourg, 4, rue Blaise Pascal, 67000, Strasbourg.
Alexandre VarnekChemoinformatics Laboratory, UMR 7140 CNRS/University of Strasbourg, 4, rue Blaise Pascal, 67000, Strasbourg.

Funding

High Performance Computing (HPC) Center of the Strasbourg UniversityState Research Funding for FSBSI "Chumakov FSC R&D IBP RAS" 0837-2019-0002
6 · The paper itself

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 800 M organic compounds.

Indexed as

Computer SimulationDrug DiscoveryQuantitative Structure-Activity RelationshipAnimalsAntiviral AgentsCoronavirusCoronavirus InfectionsCOVID-19 Drug TreatmentHumansSARS-CoV-2Viral ProteinsAntiviral AgentsViral ProteinsAntiviralschemographycoronavirusGenerative Topographic MappingSARSStructure-Activity Relationships

Identifiers

PMID32363750
PMCPMC7267182

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.