| Literature DB >> 28950183 |
Fangling Chen1, Zhuoya Wang2, Chaoyi Wang1, Qingliang Xu1, Jiazhen Liang1, Ximing Xu3, Jinbo Yang4, Changyun Wang1, Tao Jiang1, Rilei Yu5.
Abstract
A large number of structures of anti-cancer drug targets have been solved and deposited to the protein data bank already. Identification of the targets for marine compounds with anti-tumor activity presents a challenge for marine natural products scientists. In this study, fast and efficient computational reverse docking was applied to predict the probable targeting proteins of the marine compounds with anti-tumor activity. Crystal structures of the proteins involved in tumor genesis, growth and metastasis were collected from PDB to construct the anti-tumor protein database (APD) for reverse docking. Two non-commercial docking programs, AutoDock Vina and LeDock, were used to perform the docking. Our results suggest that reverse docking is efficient for target fishing of compounds with known anti-tumor activities. In addition, the results show that performance of reverse docking using LeDock is superior to that using AutoDock Vina. Overall, reverse docking is a fast and efficient computational method to identify the probable target of the compounds with anti-tumor activities, and it can be complementary to the biological testing methods.Entities:
Keywords: Anti-tumor compounds; Anti-tumor protein database; AutoDock vina; LeDock; Reverse docking; Target fishing; Target prediction
Mesh:
Substances:
Year: 2017 PMID: 28950183 DOI: 10.1016/j.jmgm.2017.09.015
Source DB: PubMed Journal: J Mol Graph Model ISSN: 1093-3263 Impact factor: 2.518