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Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
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3D-QSAR (CoMFA, CoMFA-RG, CoMSIA) and molecular docking study of thienopyrimidine and thienopyridine derivatives to
1Department of Pharmaceutical Chemistry, Institute of Pharmacy, Nirma University, Ahmedabad 382 481 India.
Abstract:
Aurora-B kinase plays a crucial role in cell cycle events and is identified as an important factor in regulation of spindle check point assembly. Thus, it can be proved as an important target in the field of oncology. 3D-QSAR model was generated using 54 molecules reported in literature containing thienopyrimidine and thienopyridine as scaffolds. All molecules were aligned using Distill function in Sybyl X1.2. This generated best model of CoMFA-RG (Region focusing) and CoMSIA were statistically significant with correlation coefficient r(2)ncv of 0.97, for both & Leave one out coefficient (LOO) q(2) of 0.70 and 0.72, respectively. Best CoMSIA model was built up using various combination of descriptors and proved statistical significant among all models. Best CoMFA-RG and CoMSIA models were validated by 12 test set molecules giving satisfactory prediction (r(2)pred) values of 0.86 and 0.88, respectively. External test set validation was performed using 20 molecules and satisfactory prediction of their biological activity was found. Active compounds were docked on protein (PDB ID: 4C2V) by GOLD module and revealed important interactions with amino acids at ATP-binding region. These data explored insight requirements for Aurora-B inhibition which might be fruitful for understanding mechanisms with kinase ligand interactions.
Insights
This study developed 3D-QSAR models for thienopyrimidine and thienopyridine compounds targeting Aurora-B kinase, a key factor in cell cycle regulation and cancer. The models accurately predict compound activity, aiding in the design of novel oncology drugs.
Area of Science:
- Medicinal Chemistry
- Computational Chemistry
- Oncology
Background:
- Aurora-B kinase is crucial for cell cycle regulation and spindle assembly checkpoint, making it a significant target in cancer therapy.
- Thienopyrimidine and thienopyridine scaffolds are recognized for their potential in developing kinase inhibitors.
Purpose of the Study:
- To develop and validate 3D-QSAR (3D Quantitative Structure-Activity Relationship) models for thienopyrimidine and thienopyridine derivatives as Aurora-B kinase inhibitors.
- To identify key structural requirements for Aurora-B kinase inhibition through computational modeling and molecular docking.
Main Methods:
- Generation of 3D-QSAR models (CoMFA-RG and CoMSIA) using 54 literature-reported molecules with thienopyrimidine and thienopyridine scaffolds.
- Molecular alignment using the Distill function in Sybyl X1.2.
- Statistical validation using Leave-One-Out (LOO) cross-validation and external test sets.
- Molecular docking of active compounds into the Aurora-B kinase active site (PDB ID: 4C2V) using the GOLD module.
Main Results:
- Statistically significant CoMFA-RG and CoMSIA models were generated with high predictive power (q²=0.70-0.72, r²pred=0.86-0.88).
- The best CoMSIA model, incorporating various descriptors, demonstrated significant statistical validity.
- Molecular docking revealed crucial interactions between active compounds and amino acids in the ATP-binding region of Aurora-B kinase.
Conclusions:
- The developed 3D-QSAR models provide reliable predictions for Aurora-B kinase inhibitory activity of thienopyrimidine and thienopyridine derivatives.
- These findings offer valuable insights into the structural features required for effective Aurora-B kinase inhibition.
- The study facilitates the rational design of novel and potent Aurora-B kinase inhibitors for cancer treatment.
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