Virtual screening of substances used in the treatment of SARS-CoV-2 infection and analysis of compounds with known action on structurally similar proteins from other viruses

Biomed Pharmacother. 2022 Sep:153:113432. doi: 10.1016/j.biopha.2022.113432. Epub 2022 Jul 18.

Abstract

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is considered the etiological agent of the disease that caused the COVID-19 pandemic, and for which there is currently no effective treatment. This pandemic has shown that the rapid identification of therapeutic compounds is critical (when a new virus with high transmissibility occurs) to prevent or reduce as much as possible the loss of human lives. To meet the urgent need for drugs, many strategies were applied for the discovery, respectively the identification of potential therapies / drugs for SARS-CoV-2. Molecular docking and virtual screening are two of the in silico tools/techniques that provided the identification of few SARS-CoV-2 inhibitors, removing ineffective or less effective drugs and thus preventing the loss of resources such as time and additional costs. The main target of this review is to provide a comprehensive overview of how in-silico tools have been used in the crisis management of anti-SARS-CoV-2 drugs, especially in virtual screening of substances used in the treatment of SARS-CoV-2 infection and analysis of compounds with known action on structurally similar proteins from other viruses; also, completions were added to the way in which these methods came to meet the requirements of biomedical research in the field. Moreover, the importance and impact of the topic approached for researchers was highlighted by conducting an extensive bibliometric analysis.

Keywords: Bibliometric analysis; Molecular docking; Proteins; Treatment of SARS-CoV-2 infection; Virtual screening; Viruses.

Publication types

  • Review

MeSH terms

  • Antiviral Agents / pharmacology
  • Antiviral Agents / therapeutic use
  • COVID-19 Drug Treatment*
  • Humans
  • Molecular Docking Simulation
  • Pandemics
  • SARS-CoV-2

Substances

  • Antiviral Agents