1. A computational investigation of thymidylate synthase inhibitors through a combined approach of 3D-QSAR and pharmacophore modelling.
- Author
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Benny S, Rajappan Krishnendu P, Kumar S, Bhaskar V, Manisha DS, Abdelgawad MA, Ghoneim MM, Naguib IA, Pappachen LK, Mary Zachariah S, Mathew B, and Tp A
- Subjects
- Models, Molecular, Humans, Protein Binding, Drug Design, Pharmacophore, Thymidylate Synthase antagonists & inhibitors, Thymidylate Synthase chemistry, Thymidylate Synthase metabolism, Quantitative Structure-Activity Relationship, Enzyme Inhibitors chemistry, Enzyme Inhibitors pharmacology, Molecular Docking Simulation, Molecular Dynamics Simulation
- Abstract
Thymidylate synthase (TS) is a crucial target of cancer drug discovery and is mainly involved in the De novo synthesis of the DNA precursor thymine. In the present study, to generate reliable models and identify a few promising molecules, we combined QSAR modelling with the pharmacophore hypothesis-generating technique. Input molecules were clustered on their similarity, and a cluster of 74 molecules with a pyrimidine moiety was chosen as the set for 3D-QSAR and pharmacophore modelling. Atom-based and field-based 3D-QSAR models were generated and statistically validated with R
2 > 0.90 and Q2 > 0.75. The common pharmacophore hypothesis(CPH) generation identified the best six-point model ADHRRR. Using these best models, a library of FDA-approved drugs was screened for activity and filtered via molecular docking, ADME profiling, and molecular dynamics simulations. The top ten promising TS-inhibiting candidates were identified, and their chemical features profitable for TS inhibitors were explored.Communicated by Ramaswamy H. Sarma.- Published
- 2024
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