Discovery of new small-molecule cyclin-dependent kinase 6 inhibitors through computational approaches.

Excessive cell proliferation due to cell cycle disorders is one of the hallmarks of breast cancer. Cyclin-dependent kinases (CDKs), which are involved in the transition of the cell cycle from G1 phase to S phase by combining CDKs with cyclin, are considered promising targets with broad therapeutic potential based on their critical role in cell cycle regulation. Pharmacological evidence has shown that abnormal cell cycle due to the overexpression of CDK6 is responsible for the hyperproliferation of cancer cells. Blocking CDK6 expression inhibits tumour survival and growth. Therefore, CDK6 can be regarded as a potential target for anticancer therapeutics. Thus, small molecules that can be considered CDK inhibitors have been developed into promising anticancer drugs. In this study, combined structure-based and ligand-based in silicon models were created to identify new chemical entities against CDK6 with the appropriate pharmacokinetic properties. The database used to screen drug-like compounds in this thesis was based on the best E-pharmacophore hypothesis and the best ligand-based drug hypothesis. As a result, 147 common compounds were identified by further molecular docking. Surprisingly, the in vitro evaluation results of 20 of those compounds showed that the two had good CDK6 inhibitory effects. The best compound was subjected to kinase panel screening, followed by molecular dynamic simulations. The 50-ns MD studies revealed the pivotal role of VAL101 in the binding of inhibitors to CDK6. Overall, the identification of two new chemical entities with CDK6 inhibitory activity demonstrated the feasibility and potential of the new method.