Computational Investigation of Natural Substances as SARS-CoV-2 Main Protease Inhibitors: A Virtual Screening Method

This study identifies four natural compounds with strong binding affinity and structural stability against SARS-CoV-2 Mpro, supporting their candidacy for further investigation as potential antiviral agents for COVID-19 treatment.

Authors

Institutions

Publication Details

Journal
Recent Advances in Anti-Infective Drug Discovery
Published
2025-07-21
DOI
https://doi.org/10.2174/0127724344379865250709163918
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Computational Investigation of Natural Substances as SARS-CoV-2 Main Protease Inhibitors: A Virtual Screening Method

Titiksh L. Devale, Deepak K. Lokwani, Shirish P. Jain, Sangita R. Chavan et al.
Recent Advances in Anti-Infective Drug Discovery
Computational Drug Discovery Methods
article

Computational Investigation of Natural Substances as SARS-CoV-2 Main Protease Inhibitors: A Virtual Screening Method

Titiksh L. Devale, Deepak K. Lokwani, Shirish P. Jain, Sangita R. Chavan, Samiksha R. Shengokar
article en

Abstract

This study identifies four natural compounds with strong binding affinity and structural stability against SARS-CoV-2 Mpro, supporting their candidacy for further investigation as potential antiviral agents for COVID-19 treatment.

Recent Advances in Anti-Infective Drug DiscoveryVol. 21(1)
C. U. Shah University (IN), Hindu College of Pharmacy (IN)
Openalex Percentile: Top 81%
Computational Drug Discovery Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.