3D-QSAR CoMFA Study on Aminothiazole Derivatives as Cyclin-Dependent Kinase 2 Inhibitors

Recent advances on CDK inhibitors: An insight by means of in silico methods

The cyclin dependent kinases (CDKs) are a small family of serine/threonine protein kinases that can act as a potential therapeutic target in several proliferative diseases, including cancer. This short review is a survey on the more recent research progresses in the field achieved by using in silico methods. All the "armamentarium" available to the medicinal chemists (docking protocols and molecular dynamics, fragment-based, de novo design, virtual screening, and QSAR) has been employed to the discovery of new, potent, and selective inhibitors of cyclin dependent kinases. The results cited herein can be useful to understand the nature of the inhibitor-target interactions, and furnish an insight on the structural/molecular requirements necessary to achieve the required selectivity against cyclin dependent kinases over other types of kinases.

Comparative analysis of various electrostatic potentials on docking precision against cyclin-dependent kinase 2 protein: a multiple docking approach

The fundamental of molecular modeling is the interaction and binding to form a complex, because it explains the action of most drugs to a receptor active site. In the present study, different semiempirical (RM1, AM1, PM3, MNDO) and ab initio (HF, DFT) charge models were investigated for their performance in prediction of docking pose against CDK2 proteins with their respective inhibitor. Further, multiple docking approaches and Prime/MM-GBSA calculations were applied to predict the binding mode with respective charge model against CDK2 inhibitors. A reliable docking result was obtained using RRD, which showed significance improvement on ligand binding poses and docking score accuracy to the IFD. The combined use of RRD and Prime/MM-GBSA method could give a high correlation between the predicted binding free energy and experimental biological activity. The preliminary results point out that AM1 could be a precious charge model for design of new drugs with enhanced success rate. As a very similar result was also found for a different system of the protein-ligand binding, the suggested scoring function based on AM1 method seems to be applicable in drug design. The results from this study can provide insights into highest success rate for design of potent and selective CDK2 inhibitors.

Investigation of the structural requirement for inhibiting HIV integrase: QSAR study

HIV integrase has emerged as a promising target for discovery of agents against the acquired immunodeficiency syndrome (AIDS) pandemic. With the purpose of designing new chemotypes with enhanced potencies against the HIV integrase enzyme, the QSAR study carried out on 37 novel phthalimide derivatives is presented. The developed QSAR model was validated by standard statistical parameters and through a detailed structural study of how it reproduces and explains the quantitative differences seen in experimentally known pharmacological data. The model showed a good correlative and predictive ability having a cross-validated correlation coefficient (r2 cv) of 0.709 and a conventional correlation coefficient (r2) of 0.949. The predictive correlation coefficient (r2 pred) was found to be 0.512. The study revealed that the antiretroviral activity is predominantly explained by the substituent size, shape and polarity and provided insights into how modulation of the steric bulkiness and polarities of the substituents could be made to optimize the integrase-inhibitor interaction chemistry. A detailed investigation was made of the structural basis for the antiretroviral activity and the findings from the study could be usefully employed to design antagonists with a much more enhanced potency and selectivity.