Discovery of potential VEGFR-2 inhibitors from natural products by virtual screening and molecular dynamics simulation

Abstract

Hepatocellular carcinoma (HCC) is the most common cancer worldwide and vascular endothelial growth factor receptor-2 (VEGFR-2) is an important target in the development of inhibitors for the treatment of liver cancer. So far, however, there are no effective drugs targeting VEGFR-2 to achieve complete treatment of liver cancer. In this study, we employed molecular docking, molecular dynamics simulations, molecular mechanics generalized Born surface area (MM-GBSA) method, quantum mechanics/molecular mechanics (QM/MM) calculations and steered molecular dynamics simulations to discover the potential inhibitors from COCONUT database targeting VEGFR-2. The molecular docking analyses of 13 743 natural compounds targeting VEGFR-2 identified 96 molecules as promising candidates. Our molecular dynamics simulations revealed that only 5 candidate-docking systems remained stable over 100 ns of production run. Then, steered molecular dynamics simulations showed that CNP0076764, CNP0028810, CNP0177683 and CNP0107283 had higher mean force values than that of sorafenib, reflecting the high potential of candidate molecules. A detailed analysis of the binding modes revealed that Leu840, Val848, Lys868, Glu885, Leu889, Val899, Val916, Leu1035, Cys1045, Asp1046 and Phe1047 play key roles in binding the inhibitors. Overall, this study shows evidence that the four natural products obtained from the COCONUT database could be further used as anti-cancer inhibitors, which provides theoretical guidance for designing new drugs.