CDK4 proteins using AutodockVina, a computational docking program. Before performing the docking analysis, ATP binding sites of the native CDK4 protein were identified. The amino acid residues present in the ATP binding clefts of CDK4 are ILE12, VAL20, ALA33, VAL77, PHE93, GLU94, HIS95, VAL96, GLN98, ASP99, THR102, GLU144, LEU147, ALA157 and ASP158. Computational docking analysis also indicated the inhibitory action of Diosgenin flavopiridol with CDK4, as observed in in vitro studies.e., the inhibitor flavopiridol binds exactly at the ATP binding site of the native CDK4 protein . However, flavopiridol binds residues outside of the ATP-binding cleft in mutant CDK4 structures . A change in the binding residues will indeed affect the complementarities between the mutant proteins and flavopiridol. Noncovalent interactions and shape complementarity are important factors for the maintenance of protein-ligand affinity. Non-covalent bonds, such as van der Waals contacts, electrostatic forces and hydrogen bonds, are the primary forces involved in protein-ligand interactions. Calculating the interaction energies of non-covalent bonds is vital to understanding the binding ability of the ligand molecule. The number of hydrogen bonds arising between the protein and ligand was computed using AutodockVina. The binding energies between the CDK4 proteins and the inhibitor molecule flavopiridol were calculated to be -8.8 kcal/mol, -7.7 kcal/mol, -7.1 kcal/mol, -7.3 kcal/mol, -7.4 kcal/mol and -7.1 kcal/mol for the native, R24C, Y180H, A205T, R210P and R246C complexes, respectively. The binding energy of the native complex MCE Chemical 221877-54-9 displayed the best interaction and complete inhibition by the flavopiridol compound. This docking analysis gives a ��theoretical quantitative�� assessment of the binding efficiencies of CDK4 native and mutant proteins with the cancer drug flavopiridol. Nonsynonymous SNPs play a vital role in the diverse responses to therapeutic treatment in human populations, influencing efficacy and toxicity by affecting the drug-binding pocket of target proteins. Virtual screening is the fastest and most accurate method for identifying novel drug-like compounds on the basis of tar
