Abstract
Introduction: Lung cancer is presumed to be the most notable cause of morbidity and impermanency in human beings caused by uncontrolled cell proliferation of lung tissue which results in abrupt synthesis of DNA.
Methods: Prevention of DNA synthesis can show distinctive effect on lung cancer by utilizing Thymidylate synthase (TS), a key rate-limiting enzyme in the DNA synthesis process. However, the available finite aggregate of clinically approved blockers and their corresponding side effects lead to the urgent origination of novel inhibitors.
Results and Discussion: In silico approaches (QSAR and molecular docking) have been accomplished to discover new potential inhibitors of TS providing a new strategy to evolve novel thymidylate synthase inhibitors functional in lung cancer.
Conclusion: In the present study chemical features of a series of compounds alongside their activities alternating over numerous orders of magnitudes was utilized to generate QSAR models, and these could be further employed to predict the activity of new designed compounds. 3D‒QSAR kNNSW based model with decent statistical data having q2 approximately 95% (internal validation) and 80% (external validation) has validated the importance of steric feature. Further docking analysis using D‒score and ligand receptor interactions indicated that all the studied compounds are well accommodated in the binding pocket of TS and disparities in the activity are controlled by hydrogen and hydrophobic interactions.
Keywords: Docking, kNN-SW, lung cancer, QSAR, thymidylate synthase inhibitors, adenocarcinoma.
Graphical Abstract
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