Identification of effective cyclin-dependent kinase 3/cyclin E inhibitors using multi-level computational screening and simulation.

Introduction: Cyclin-dependent kinase 3 (CDK3) plays a crucial role in regulating cell cycle progression through the G0/G1 and G1/S phases. Although extensively lowered in normal tissue, CDK3 is overexpressed in multiple cancers, making it a promising target for anticancer therapy. Despite its significance, no established inhibitors of CDK3 are currently available.

Methods: We aimed to identify effective inhibitors of CDK3/cyclin E from a library of 204 derivatives of five potent CDK3 inhibitors-Purvalanol A, NU6102, R547, dinaciclib, and RO-3306, using a multi-tiered computational pipeline. Molecular docking was first used to screen these candidates which has emerged as an efficient technique to elucidate binding energies and interactions of compounds to target receptors, thereby playing indispensable roles in drug discovery. Five top-scoring candidates from docking were evaluated through ADMET profiling, global reactivity studies, 100ns duplicate molecular dynamics (MD) simulations and Our own N-layered Integrated molecular Orbital and molecular Mechanics (ONIOM) calculations. Two hits showing optimal inhibition were subjected to extended 1200ns MD simulations.

Results and discussion: Docking studies identified interactions of the five selected candidates with crucial residues of CDK3. Global reactivity suggested favourable electronic properties for receptor binding. MD simulations, MM-PBSA and ONIOM revealed stable ligand-receptor interactions and favourable binding energetics. Extended 1200ns simulations of the two hits, CID_11212010 and CID_25211747, demonstrated exceptional stability of CID_25211747 with minimal conformational fluctuation. Additional ONIOM calculations reproduced the strong binding affinity of CID_25211747 with CDK3. Collectively, these results nominate CID_25211747 as a promising lead towards the development of effective CDK3 antagonists, offering valuable insight for future drug design.