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Updated: Mar 1, 2026
Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
3D-QSAR, molecular dynamics simulations, and molecular docking studies on pyridoaminotropanes and
1Department of Pharmaceutical Chemistry, Institute of Pharmacy, Nirma University, S. G. Highway, Chharodi, Ahmedabad, 382 481, India.
Abstract:
Cancer is a second major disease after metabolic disorders where the number of cases of death is increasing gradually. Mammalian target of rapamycin (mTOR) is one of the most important targets for treatment of cancer, specifically for breast and lung cancer. In the present research work, Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) studies were performed on 50 compounds reported as mTOR inhibitors. Three different alignment methods were used, and among them, distill method was found to be the best method. In CoMFA, leave-one-out cross-validated coefficients [Formula: see text], conventional coefficient [Formula: see text], and predicted correlation coefficient [Formula: see text] values were found to be 0.664, 0.992, and 0.652, respectively. CoMSIA study was performed in 25 different combinations of features, such as steric, electrostatic, hydrogen bond donor, hydrogen bond acceptor, and hydrophobic. From this, a combination of steric, electrostatic, hydrophobic (SEH), and a combination of steric, electrostatic, hydrophobic, donor, and acceptor (SEHDA) were found as best combinations. In CoMSIA (SEHDA), [Formula: see text], [Formula: see text] and [Formula: see text] were found to be 0.646, 0.977, and 0.682, respectively, while in the case of CoMSIA (SEH), the values were 0.739, 0.976, and 0.779, respectively. Contour maps were generated and validated by molecular dynamics simulation-assisted molecular docking study. Highest active compound 19, moderate active compound 15, and lowest active compound 42 were docked on mTOR protein to validate the results of our molecular docking study. The result of the molecular docking study of highest active compound 19 is in line with the outcomes generated by contour maps. Based on the features obtained through this study, six novel mTOR inhibitors were designed and docked. This study could be useful for designing novel molecules with increased anticancer activity.
Insights
This study used computational methods to analyze 50 compounds inhibiting mammalian target of rapamycin (mTOR), a key target in cancer therapy. The findings aid in designing new, more effective anticancer drugs.
Area of Science:
- Medicinal Chemistry
- Computational Chemistry
- Oncology
Background:
- Cancer remains a leading cause of death, with increasing incidence.
- Mammalian target of rapamycin (mTOR) is a crucial target for treating cancers like breast and lung cancer.
Purpose of the Study:
- To perform Quantitative Structure-Activity Relationship (QSAR) studies on 50 known mTOR inhibitors.
- To identify key molecular features for designing novel mTOR inhibitors with enhanced anticancer activity.
Main Methods:
- Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were employed.
- The distill method was identified as the optimal alignment strategy.
- Molecular docking and dynamics simulations were used for validation.
Main Results:
- CoMFA yielded significant predictive models (R²cv=0.664, R²=0.992).
- CoMSIA models, particularly using steric, electrostatic, hydrophobic, donor, and acceptor features (SEHDA), showed strong performance (R²cv=0.646, R²=0.977).
- The best CoMSIA model (SEH) achieved R²cv=0.739 and R²=0.976.
- Molecular docking validated the computational findings, aligning with experimental activity.
Conclusions:
- The study successfully identified key pharmacophoric features of mTOR inhibitors.
- Six novel mTOR inhibitors were designed based on these features.
- This research provides a foundation for developing next-generation anticancer therapeutics targeting mTOR.
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