Issue 71, 2017, Issue in Progress

Discriminatory analysis based molecular docking study for in silico identification of epigallocatechin-3-gallate (EGCG) derivatives as B-RafV600E inhibitors

Abstract

Virtual screening and biological testing were utilized to identify novel B-RafV600E inhibitors. The employed LigandFit program was evaluated by examining the accuracy of the binding conformation prediction and binding affinity estimation (scoring function) via discriminative analysis training. Ten novel compound hits from the database screening were selected and subjected to in vitro biological tests. The natural product EGCG (A8) was discovered to have promising B-RafV600E inhibitory, and then we evaluated six structurally similar compounds (B1, B2, B3, C1, C2, and C3) for their B-RafV600E inhibitory activities in order to establish a structure–activity relationship. One of these compounds, B2, demonstrated a promising B-RafV600E inhibitory activity with an IC50 value of 9.1 μM, providing a theoretical basis for the development of novel agents as B-RafV600E inhibitors.

Graphical abstract: Discriminatory analysis based molecular docking study for in silico identification of epigallocatechin-3-gallate (EGCG) derivatives as B-RafV600E inhibitors

Supplementary files

Article information

Article type
Paper
Submitted
28 Apr 2017
Accepted
04 Sep 2017
First published
19 Sep 2017
This article is Open Access
Creative Commons BY license

RSC Adv., 2017,7, 44820-44826

Discriminatory analysis based molecular docking study for in silico identification of epigallocatechin-3-gallate (EGCG) derivatives as B-RafV600E inhibitors

H. Ying, J. Xie, X. Liu, T. Yao, X. Dong and C. Hu, RSC Adv., 2017, 7, 44820 DOI: 10.1039/C7RA04788F

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