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Updated: May 30, 2025
A Simple Bioassay for the Evaluation of Vascular Endothelial Growth Factors
Published on: March 15, 2016
Discovery of potential VEGFR-2 inhibitors from natural products by virtual screening and molecular dynamics
Qiong Xie1, Mengshi Luo1, Mingyan Liu1
1Chongqing Key Laboratory of Theoretical and Computational Chemistry, School of Chemistry and Chemical Engineering, Chongqing University, Chongqing 401331, P. R. China. chxh7@cqu.edu.cn.
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.
Insights
Researchers identified four natural compounds from the COCONUT database as potential inhibitors for vascular endothelial growth factor receptor-2 (VEGFR-2), offering new hope for liver cancer treatment.
Area of Science:
- Oncology
- Computational Chemistry
- Drug Discovery
Background:
- Hepatocellular carcinoma (HCC) is a prevalent global cancer.
- Vascular endothelial growth factor receptor-2 (VEGFR-2) is a key therapeutic target for liver cancer.
- Current treatments targeting VEGFR-2 lack complete efficacy.
Purpose of the Study:
- To identify novel natural product inhibitors of VEGFR-2 from the COCONUT database.
- To evaluate the binding potential and stability of these inhibitors using computational methods.
- To provide theoretical guidance for the development of new anti-cancer drugs.
Main Methods:
- Molecular docking of 13,743 natural compounds against VEGFR-2.
- Molecular dynamics (MD) simulations to assess system stability (100 ns).
- Steered molecular dynamics (SMD) simulations to determine binding affinities.
- QM/MM and MM-GBSA calculations for detailed binding analysis.
Main Results:
- 96 potential VEGFR-2 inhibitors were identified via molecular docking.
- 5 compounds demonstrated stable interactions in MD simulations.
- Four compounds (CNP0076764, CNP0028810, CNP0177683, CNP0107283) exhibited higher binding potential than sorafenib in SMD simulations.
- Key amino acid residues (Leu840, Val848, Lys868, etc.) were identified as crucial for inhibitor binding.
Conclusions:
- Four natural products from the COCONUT database show significant potential as VEGFR-2 inhibitors.
- These compounds offer a promising basis for developing novel therapeutics against hepatocellular carcinoma.
- The study provides valuable theoretical insights for future drug design targeting VEGFR-2.
