Structural Determinants of CX-4945 Derivatives as Protein Kinase CK2 Inhibitors: A Computational Study

Hongbo Liu,Xia Wang,Guohui Li,Jinghui Wang,Ling Yang,Yan Li,Jian Wang

doi:10.3390/ijms12107004

Abstract

Protein kinase CK2, also known as casein kinase-2, is involved in a broad range of physiological events including cell growth, proliferation and suppression of apoptosis which are related to human cancers. A series of compounds were identified as CK2 inhibitors and their inhibitory activities varied depending on their structures. In order to explore the structure-activity correlation of CX-4945 derivatives as inhibitors of CK2, in the present study, a set of ligand- and receptor-based 3D-QSAR models were developed employing Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA). The optimum CoMFA (Rcv2 = 0.618, Rpred2 = 0.892) and CoMSIA (Rcv2 = 0.681, Rpred2 = 0.843) models exhibited reasonable statistical characteristics for CX-4945 derivatives. The results indicated that electrostatic effects contributed the most to both CoMFA and CoMSIA models. The combination of docking analysis and molecular dynamics (MD) simulation showed that Leu45, Lys68, Glu81, Val116, Asp175 and Trp176 of CK2 which formed several direct or water-bridged H-bonds with CX-4945 are crucial for CX-4945 derivatives recognition to CK2. These results can offer useful theoretical references for designing more potent CK2 inhibitors.

Highlights

The casein kinase-2 (CK2) is a pleiotropic, highly conserved serine/threonine protein kinase ubiquitously expressed in both the cytoplasm and the nucleus of eukaryotic cells [1,2,3]
The selected test set, which was not included in the model training process, was used to evaluate the predictive power of the Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA) models
There are several statistical parameters, i.e., the cross-validated correlation coefficient, non-cross-validated correlation coefficient, standard error of estimate (SEE) and F-statistic values (F) that are inherent in appraising a QSAR model for the compounds to be studied

Summary

Introduction

The casein kinase-2 (CK2) is a pleiotropic, highly conserved serine/threonine protein kinase ubiquitously expressed in both the cytoplasm and the nucleus of eukaryotic cells [1,2,3]. CK2 possesses constitutive catalytic activity with the ability to phosphorylate more than 300 physiological substrates and does not require phosphorylation by other kinases for activation [2] These features make CK2 appear at extremely diverse points of cell signaling pathways, including PI3K/Akt and Wnt signaling cascades, NF-κB transcription, and the DNA damage response [1] and [4]), and be involved in a number of cellular events contributing to the development of various disorders, cancer These data, in conjunction with the observation that many viruses exploit CK2 as phosphorylating agent of proteins essential to their life cycle [2], have made CK2 an attractive yet underexploited new therapeutic target for the treatment of cancer [5].

Methods

Results

Conclusion