Title:Computer-aided Drug Discovery Approaches in the Identification of
Natural Products against SARS-CoV-2: A Review
Volume: 20
Issue: 4
Author(s): Mariana Martinelli Junqueira Ribeiro*
Affiliation:
- Faculty of Pharmacy, Estácio de Sá University, Morais e Silva Street, 40, Maracanã, 20271-030, Rio de Janeiro-Rio de Janeiro, Brazil
Keywords:
Computational studies, COVID-19, in silico approach, molecular dynamic, molecular modeling, primary and secondary metabolites.
Abstract: The COVID-19 pandemic is raising a worldwide search for compounds that could act
against the disease, mainly due to its mortality. With this objective, many researchers invested in
the discovery and development of drugs of natural origin. To assist in this search, the potential of
computational tools to reduce the time and cost of the entire process is known. Thus, this review
aimed to identify how these tools have helped in the identification of natural products against
SARS-CoV-2. For this purpose, a literature review was carried out with scientific articles with
this proposal where it was possible to observe that different classes of primary and, mainly, secondary
metabolites were evaluated against different molecular targets, mostly being enzymes and
spike, using computational techniques, with emphasis on the use of molecular docking. However,
it is noted that in silico evaluations still have much to contribute to the identification of an anti-
SARS-CoV-2 substance, due to the vast chemical diversity of natural products, identification and
use of different molecular targets and computational advancement.
