Exploring Natural Compounds as Potential CDK4 Inhibitors for Therapeutic Intervention in Neurodegenerative Diseases through Computational Analysis

CDK4 is a member of the serine-threonine kinase family, which has been found to be overexpressed in a plethora of studies related to neurodegenerative diseases. CDK4 is one of the most validated therapeutic targets for neurodegenerative diseases. Hence, the discovery of potent inhibitors of CDK4 is a promising candidate in the drug discovery field. Firstly, the reference drug Palbociclib was identified from the available literature as a potential candidate against target CDK4. In the present study, the Collection of Open Natural Products (COCONUT) database was accessed for determining potential CDK4 inhibitors using computational approaches based on the Tanimoto algorithm for similarity with the target drug, i.e., Palbociclib. The potential candidates were analyzed using SWISSADME, and the best candidates were filtered based on Lipinski’s Rule of 5, Brenk, blood–brain barrier permeability, and Pains parameter. Further, the molecular docking protocol was accessed for the filtered compounds to anticipate the CDK4-ligand binding score, which was validated by the fastDRH web-based server. Based on the best docking score so obtained, the best four natural compounds were chosen for further molecular dynamic simulation to assess their stability with CDK4. In this study, two natural products, with COCONUT Database compound ID—CNP0396493 and CNP0070947, have been identified as the most suitable candidates for neuroprotection. Graphical Abstract: Overexpression of CDK4 in NDDs has been considered as prominent target for therapeutics. Possible CDK4 inhibitors have been explored using computational techniques and the COCONUT database, which keeps Palbociclib as the reference drug. Using several criteria, such as molecular docking and Lipinski’s Rule of 5, 110 natural compounds have been obtained. In addition to molecular docking, this study utilized Molecular Mechanics Generalised Born Surface Area (MM-GBSA) analysis to further filter and assess the binding affinity and stability of the top 4 natural compounds. Further evaluation was carried out by molecular dynamic simulation, demonstrating CNP0396493 and CNP0070947 as the most promising candidates for neuroprotection. (Figure presented.)