Related Experiment Video
Updated: Oct 26, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
Molecular docking, DFT analysis, and dynamics simulation of natural bioactive compounds targeting ACE2 and TMPRSS2
Rohitash Yadav1, Shazia Hasan1, Sumit Mahato1
1Department of Pharmacology, All India Institute of Medical Sciences, Rishikesh, India.
Abstract:
The scientific community is continuously working to discover drug candidates against potential targets of SARS-CoV-2, but effective treatment has not been discovered yet. The virus enters the host cell through molecular interaction with its enzymatic receptors i.e., ACE2 and TMPRSS2, which, if, synergistically blocked can lead to the development of novel drug candidates. In this study, 1503 natural bioactive compounds were screened by HTVS, followed by SP and XP docking using Schrodinger Maestro software. Bio-0357 (protozide) and Bio-597 (chrysin) were selected for dynamics simulation based on synergistic binding affinity on S1 (docking score -9.642 and -8.78 kcal/mol) and S2 domains (-5.83 and -5.3 kcal/mol), and the RMSD, RMSF and Rg analyses showed stable interaction. The DFT analysis showed that the adsorption of protozide/chrysin, the band gap of protozide/chrysin-F/G reduced significantly. From SERS, results, it can be concluded that QDs nanocluster will act as a sensor for the detection of drugs. The docking study showed Bio-0357 and Bio-0597 bind to both S1 and S2 domains through stable molecular interactions, which can lead to the discovery of new drug candidates to prevent the entry of SARS-CoV-2. This in-silico study may be helpful to researchers for further in vitro experimental validation and development of new therapy for COVID-19.
More Related Videos
05:50Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro
Published on: September 26, 2025
08:49Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
Published on: June 20, 2025