Related Experiment Video
Updated: Oct 22, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
Designing of the N-ethyl-4-(pyridin-4-yl)benzamide based potent ROCK1 inhibitors using docking, molecular dynamics,
Suparna Ghosh1, Seketoulie Keretsu1, Seung Joo Cho1,2
1Department of Biomedical Sciences, College of Medicine, Chosun University, Gwangju, South Korea.
This study used molecular modeling to design new N-ethyl-4-(pyridin-4-yl)benzamide compounds as Rho-associated kinase-1 (ROCK1) inhibitors. Seven novel compounds show high predictive activity, offering potential for cardiovascular disease therapies.
Area of Science:
- Medicinal Chemistry
- Computational Biology
- Pharmacology
Background:
- Rho-associated kinase-1 (ROCK1) is implicated in cardiovascular diseases, malignancy, and neurological disorders.
- ROCK1 hyperactivity contributes to smooth muscle cell contraction, relevant to vascular system pathologies.
- ROCK1 inhibition presents a promising therapeutic strategy for cardiovascular conditions.
Purpose of the Study:
- To investigate N-ethyl-4-(pyridin-4-yl)benzamide derivatives as potential ROCK1 inhibitors.
- To establish structure-activity relationships (SAR) for designing more potent ROCK1 inhibitors.
- To provide insights for developing novel therapeutic agents targeting ROCK1.
Main Methods:
- Employed molecular modeling techniques including docking and molecular dynamics (MD) to analyze compound-ROCK1 interactions.
- Utilized 3-Dimensional quantitative structure-activity relationship (3D-QSAR) methods, specifically Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA).
- Designed and evaluated new compounds based on SAR insights, followed by ADME/Tox and SA score predictions.
Main Results:
- Docking and MD simulations identified critical interactions and binding affinities between ROCK1 and tested inhibitors.
- CoMFA and CoMSIA models demonstrated good predictive capabilities (q²=0.774, q²=0.676 respectively) and revealed key substitution patterns.
- Seven newly designed compounds exhibited enhanced predictive activity (pIC50), with further analyses supporting their potential.
Conclusions:
- The integrated approach of docking, MD, and 3D-QSAR effectively guided the modification of existing molecules.
- The study successfully identified promising novel ROCK1 inhibitors with potential therapeutic applications.
- Findings offer valuable insights for the future development of more potent ROCK1-targeting drugs.
More Related Videos
10:33Development of Inhibitors of Protein-protein Interactions through REPLACE: Application to the Design and Development Non-ATP Competitive CDK Inhibitors
Published on: October 26, 2015
08:49Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
Published on: June 20, 2025