Novel Design Strategy for Checkpoint Kinase 2 Inhibitors Using Pharmacophore Modeling, Combinatorial Fusion, and Virtual Screening

Abstract

Checkpoint kinase 2 (Chk2) has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. In this study, we will concentrate on Chk2 and the purpose is to find the potential inhibitors by the pharmacophore hypotheses (PhModels), combinatorial fusion, and virtual screening techniques. Applying combinatorial fusion into PhModels and virtual screening techniques is a novel design strategy for drug design. We used combinatorial fusion to analyze the prediction results and then obtained the best correlation coefficient of the testing set (r test) with the value 0.816 by combining the Best(train)Best(test) and Fast(train)Fast(test) prediction results. The potential inhibitors were selected from NCI database by screening according to Best(train)Best(test) + Fast(train)Fast(test) prediction results and molecular docking with CDOCKER docking program. Finally, the selected compounds have high interaction energy between a ligand and a receptor. Through these approaches, 23 potential inhibitors for Chk2 are retrieved for further study.

DOI: 10.1155/2014/359494

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Cite this paper

@inproceedings{Lin2014NovelDS, title={Novel Design Strategy for Checkpoint Kinase 2 Inhibitors Using Pharmacophore Modeling, Combinatorial Fusion, and Virtual Screening}, author={Chun-Yuan Lin and Yen-Ling Wang}, booktitle={BioMed research international}, year={2014} }