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-Raf^V600E 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-Raf^V600E inhibitory, and then we evaluated six structurally similar compounds (B1, B2, B3, C1, C2, and C3) for their B-Raf^V600E inhibitory activities in order to establish a structure–activity relationship. One of these compounds, B2, demonstrated a promising B-Raf^V600E inhibitory activity with an IC₅₀ value of 9.1 μM, providing a theoretical basis for the development of novel agents as B-Raf^V600E inhibitors.