Development of Promising CDK5 Inhibitors Using Structure‐Based Pharmacophore Modeling, Molecular Docking, and Molecular Dynamics Approach

Cancer is highlighted as one of the deadliest diseases globally, with CDK5 identified as a key enzyme in cancer progression. Despite its potential as a therapeutic target, developing CDK5 inhibitors has been challenging. We used multicomplex‐based pharmacophore modeling on CDK5 complexes, identifying hydrophobic groups, hydrogen bond donors, and acceptors as crucial inhibition features. Validated models were used for the virtual screening of drug‐like natural product databases. Thereafter, the screened candidates were selected to study their binding pattern and binding efficiency in the enzyme. Four molecules were shortlisted and analyzed for electrostatic potential (ESP) energy maps. Molecular dynamic simulations and free energy calculations on the docked complexes revealed stable behavior for all, with three (CNP0299652, CNP0362830, and CNP0009633) showing higher Poisson Boltzmann surface area continuum solvation (MM‐PBSA) binding scores than the reference. These candidates demonstrated drug‐like characteristics, crucial amino acid interactions, favorable electron potentials in ESP plots, stable dynamicigher free energy, highlighting their potential as CDK5 inhibitors. Cancer is one of the deadliest diseases worldwide, with CDK5 playing a crucial role in its progression. This study utilises bioinformatics techniques like pharmacophore modelling, molecular docking, quantum descriptor calculations, molecular dynamics and binding free energy analyses to identify promising natural COCONUT compounds as CDK5 inhibitors, offering valuable insights into CDK5 binding and potential novel anticancer agents.