Ligand-based pharmacophore filtering, atom based 3D-QSAR, virtual screening and ADME studies for the discovery of potential ck2 inhibitors

Abstract

In the era of druggable genome, the assessment of the numerous molecular targets represents remarkable therapeutic opportunities in the pharmaceutical and chemical biology, simultaneously understanding the properties required for the small molecules to emerge as good drug candidate. Incorporation of readily amenable biological properties and pharmaceutical modulation is the core key for the small molecule driven target studies in cancer related disease, especially in the case of inhibitory type mechanisms. Among huge protein targets, CK2 which is a protein serine/threonine kinase, also called the “Predominant monitor” of the cell plays comprehensive role in the various cellular machinery pertaining to cell growth and cell death. Due to its ubiquitous nature and its activity to block its activity by small molecules resulting in favorably targeting prostate cancer, CK2 was identified to be the distinct element of our study. In this study, we invested rapid computational techniques to uncover the new CK2 inhibitors with promising pharmaceutical traits and advantages when matched with existing drugs. Initially, pharmacophore modeling and atom-based 3Dimensional-Quantitative structure activity relationship of 45 known CK2 inhibitors resulted in over few hundred hypotheses. The most excellent five point pharmacophore model (AAHHR) with two hydrogen bond acceptor (A), two hydrophobic groups (H), and one aromatic ring (R) was built. 3D-QSAR studies of the finest model yielded correlation co-efficient, R2 (0.9728) and Q2 (0.7965) for training and test set compounds respectively. Our effort of externally validating the generated QSAR model was quite momentous and encouraging with rm2 = 0.682, rcv2 = 0.779, k = 1.027 and r02 = 0.817 values points out the profoundness in predicting preeminence of model. The robust model was further employed as 3D query for virtual screening against ZINC database. The lead molecules were selected based on the fitness score, and then the lead molecules subsequently taken to molecular docking studies using Glide. Finally we identified six potential lead molecules were further subjected into ADME properties prediction by engaging Qikprop module. The ADME properties of six lead molecules ZINC15955420, Zinc13412605, Zinc40763681, Zinc40763677, Zinc26178676 and Zinc01536721 are under satisfactory range with desired ADME properties. On the whole, we believe our design of the new CK2 inhibitor serves as the approachable end resultant hits the can be researched further for clinical trials evaluation in prostate cancer and emphasize on choosing CK2 as the target that holds true protential for the genesis and proliferation of anti-CK2 agents to address prostate cancer therapeutics.