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Updated: Dec 20, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
Pharmacophore Generation, Quantitative Structure-Activity Relationship (QSAR), and Molecular Dynamic Simulation of
Divya Chauhan1, Sushil Kumar2, Syed Riaz Hashim1
1Department of Chemistry, School of Sciences, IFTM University, Moradabad, Uttar Pradesh, India.
Objective:
The main objective of the study was to develop the Quantitative Structure- Activity Relationship (QSAR) and pharmacophore model by using data obtained from HT-29 cells to develop potent lead molecule for the scientific community.
Materials And Methods:
Common pharmacophore model, atom-based 3D-QSAR, and molecular dynamic (MD) simulation were carried out via computational techniques by using 4H-chromene derivatives.
Results:
The reliable common pharmacophoric hypothesis, DHH13 was generated and 3.95 survival value was also found. Furthermore, the statistically significant 3D-QSAR model was developed where r2=0.52 was found by using the Partial least squares (PLS) regression method. Phase predicted activity and Log GI50 demonstrated an important atomic position in the structure of ligands to ascertain anti colon cancer activity. Also, MD simulation was carried out between top rank leads targeting IL-6 that provided better binding conformational and complex stability into the active pocket site of the target throughout the MD simulation.
Conclusion:
The outcome of this design shows that the pharmacophore model and 3D-QSAR might be helpful for researchers in the field of medicinal chemistry to design and develop potential anti colon cancer compounds.
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