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A critical overview of computational approaches employed for COVID-19 drug discovery

Authors: José L. Medina-Franco; Artem Cherkasov; Alexey V. Zakharov; Sean Ekins; Carolina Horta Andrade; Olexandr Isayev; Denis Fourches; +17 Authors

A critical overview of computational approaches employed for COVID-19 drug discovery

Abstract

We cover diverse methodologies, computational approaches, and case studies illustrating the ongoing efforts to develop viable drug candidates for treatment of COVID-19.

Keywords

Antiviral Agents, Drug Discovery, [CHIM.CHEM] Chemical Sciences/Cheminformatics, Humans, Computer Simulation, DOCKING, BIOLOGICAL EVALUATION, Pandemics, Uncategorized, MAIN PROTEASE, Clinical Trials as Topic, IDENTIFICATION, QSAR, POTENT, SARS-CoV-2, Drug Repositioning, COVID-19, COVID-19 Drug Treatment, Chemistry, Drug Design, LIGAND-BINDING, SARS-COV-2 SPIKE PROTEIN, 3CL PROTEASE, INHIBITORS, Medicinal and biomolecular chemistry not elsewhere classified

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    137
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 0.1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
137
Top 1%
Top 10%
Top 0.1%
Green
hybrid