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Updated: Aug 23, 2025

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
Published on: June 20, 2025
Molecular docking and dynamics guided approach to identify potential anti-inflammatory molecules as NRF2 activator to
Ajay Mili1, Subham Das2, Krishnadas Nandakumar3
1Department of Pharmacognosy, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, India.
Abstract:
Inflammation and oxidative stress can contribute to the etiology of metabolic and chronic illnesses. The ability to prevent oxidative stress induced diseases such as cancer, cardiovascular disease, Alzheimer's disease, and others has been the subject of global research. Drug-induced liver injury (DILI) pathogenesis can be either due to oxidative stress or inflammatory response elicited by the drug, its metabolite, or herbal supplements. Our present research uses computational studies to identify a molecule with anti-inflammatory properties that can operate as an NRF2 activator. Acquiring and preparing the KEAP1-NRF2 Protein (PDB: 4L7D) with Schrodinger Suite was followed by developing a ligand library (Anti-inflammatory library downloaded from ChemDiv database). Molecular docking studies were performed in HTVS, SP, and XP modes, respectively. Based on the docking score, interaction, ADMET and binding free energy, the top ten compounds were selected and subjected to induced-fit docking (IFD) analysis for further study. The top three molecules were chosen for a molecular dynamics (MD) simulation study. Using the Desmond module of the Schrodinger Suite, the stability of the protein-ligand complex and protein-ligand contact throughout 100ns were evaluated during the MD simulation study. In our study, it was observed that three compounds exhibit exceptional stability and retain the essential interaction throughout the studies, and it is anticipated that these compounds may act as effective NRF2 activators. Further in vitro and in vivo assessments can be conducted to determine its potential to prevent DILI via acting as an NRF2 activator for future drug development.
Insights
Computational studies identified three promising molecules that act as NRF2 activators, potentially preventing diseases linked to inflammation and oxidative stress like drug-induced liver injury.
Area of Science:
- Computational chemistry
- Drug discovery
- Molecular biology
Background:
- Inflammation and oxidative stress are key factors in chronic diseases.
- Drug-induced liver injury (DILI) can stem from oxidative stress or inflammation.
- NRF2 activators are sought for disease prevention.
Purpose of the Study:
- To computationally identify novel molecules with anti-inflammatory properties.
- To find potential NRF2 activators for preventing oxidative stress-related diseases.
- To investigate compounds for preventing drug-induced liver injury (DILI).
Main Methods:
- Utilized Schrodinger Suite for protein preparation (KEAP1-NRF2, PDB: 4L7D) and molecular docking (HTVS, SP, XP modes).
- Screened an anti-inflammatory ligand library from ChemDiv database.
- Performed induced-fit docking (IFD) and 100ns molecular dynamics (MD) simulations using Desmond module.
Main Results:
- Identified top compounds based on docking scores, interactions, ADMET properties, and binding free energy.
- Three selected compounds demonstrated exceptional stability and maintained essential interactions during MD simulations.
- These compounds are potential NRF2 activators with promise for DILI prevention.
Conclusions:
- The identified compounds show potential as effective NRF2 activators.
- Further in vitro and in vivo studies are recommended to validate their therapeutic potential.
- These findings contribute to the development of new drugs for preventing DILI and other oxidative stress-related diseases.
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