Issue 1, 2015

Structural insights into flavones as protein kinase CK2 inhibitors derived from a combined computational study

Abstract

Flavones, which belong to the large group of flavonoids, have attracted considerable attention in relation to their therapeutic potential. Recently, this series of compounds has been shown to inhibit CK2 with outstanding efficiency and safety. However, to date, the exact binding modes between CK2 and flavones, as well as the basis of their effects on the biological activities remain unclear. In this study, we report the detailed account of the interactions between CK2 and flavones at the atomic level through computational approaches. Starting from four different molecular docking protocols, we obtained the relatively reliable initial complex structures by comparing docking scores. With subsequent molecular dynamic simulations and binding free energy calculations and decompositions, we found that the predicted binding free energies correlated well with pIC50 (R = 0.86), shedding light on the necessity of MD studies. Moreover, the results clearly confirmed that hydrophobic residues such as Val39, Val47, Ile60, Phe107, Asn112, Met157 and Ile168 were responsible for flavones binding and identified the key structural elements necessary for their bioactivities. Based on the structural and energetic features of receptor–ligand interaction mechanism, we designed a series of novel compounds and their higher inhibitory activities were confirmed by a comprehensive modeling study. We expect that these findings could serve as a paradigm for facilitating the process of developing novel and more promising inhibitors targeting CK2.

Graphical abstract: Structural insights into flavones as protein kinase CK2 inhibitors derived from a combined computational study

Supplementary files

Article information

Article type
Paper
Submitted
13 Sep 2014
Accepted
12 Nov 2014
First published
13 Nov 2014

RSC Adv., 2015,5, 462-476

Structural insights into flavones as protein kinase CK2 inhibitors derived from a combined computational study

M. Lv, S. Ma, Y. Tian, X. Zhang, H. Zhai and W. Lv, RSC Adv., 2015, 5, 462 DOI: 10.1039/C4RA10381E

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