MACHINE LEARNING-BASED VIRTUAL SCREENING, MOLECULAR DOCKING, DRUG-LIKENESS, PHARMACOKINETICS AND TOXICITY ANALYSES TO IDENTIFY NEW NATURAL INHIBITORS OF THE GLYCOPROTEIN SPIKE (S1) of SARS-CoV-2

MACHINE LEARNING-BASED VIRTUAL SCREENING, MOLECULAR DOCKING, DRUG-LIKENESS, PHARMACOKINETICS AND TOXICITY ANALYSES TO IDENTIFY NEW NATURAL INHIBITORS OF THE GLYCOPROTEIN SPIKE (S1) of SARS-CoV-2

To identify natural bioactive compounds (NBCs) as potential inhibitors of spike (S1) by means of in silico assays. NBCs with previously proven biological in vitro activity were obtained from the ZINC database and analyzed through virtual screening and molecular docking to identify those with higher...

Full description

Bibliographic Details
Main Authors: Alexandre de F. Cobre, Beatriz Böger, Mariana M. Fachi, Carlos A. Ehrenfried, Dile P. Stremel, Eduardo B. De Melo, Fernanda S. Tonin, Roberto Pontarolo
Format: Article
Language:English
Published: Sociedade Brasileira de Química 2023-06-01
Series:Química Nova
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422023000500450&tlng=en

Similar Items

Similar Items