Cyclin-dependent kinase 2 (CDK2) is one of the most promising therapeutic targets in the treatment of cancer, especially colorectal cancer. However, it has been quite challenging to develop selective inhibitors because of the high structural similarity among the CDK family members. This in silico research has adopted an integrated strategy involving pharmacophore modeling, 3D-QSAR analysis, molecular docking, molecular dynamics (MD) simulation, and ADMET prediction to discover new CDK2 inhibitors.A 3D-QSAR model (R² = 0.8594, Q² = 0.8014, based on 24 compounds with 1.5 log unit activity range) was successfully validated and used to establish quantitative structure-activity relationships. The robustness of the model was also supported by an external validation through Y-randomization. The pharmacophore hypothesis AHRRR1 was the model that best represented the key features of the interaction and was therefore used for validation by molecular docking studies. Nine compounds were predicted to bind with higher affinity than the clinical standard AT7519, and among them, compound 7e was the one with the highest docking score (-8.012 kcal/mol vs. -6.478 kcal/mol). The binding stability was also confirmed by the MD simulations for 100 ns. The compounds discovered have, in general, good predicted ADMET properties, although some of them do not meet the molecular weight criteria. As a matter of fact, all these results are purely computational and ought to be experimentally validated to assess biological activity, selectivity profiles, safety, and pharmacokinetic properties. This research is a stepping stone for further synthetic and biological exploration of these in silico optimized CDK2 inhibitor candidates.
Gawande et al. (Sun,) studied this question.