化学
虚拟筛选
血管内皮生长因子受体
组合化学
药理学
药物发现
生物化学
癌症研究
医学
生物
标识
DOI:10.2174/0115701808334488241121054542
摘要
Objective: The current use of Vascular Endothelial Growth Factor Receptor 2 (VEGFR-2) inhibitors is often limited by low selectivity and adverse side effects, highlighting the urgent need for novel, highly selective agents targeting this receptor. Methods: Based on existing VEGFR-2 inhibitors, we employed computer-aided drug design (CADD) techniques to develop a virtual compound library using active docking fragments. Molecular docking was performed using the configuration of VEGFR-2 as the receptor protein(PDB:4ASD). Comparative analysis and screening identified the most promising inhibitor, which was subsequently validated through molecular dynamics simulations. Results:: From the virtual library, 10 potential highly active inhibitors were identified. In particular, Compound 9 demonstrated strong binding affinity with the protein configuration, forming four hydrogen bonds during docking. The calculated CODOCKER energy was 39.7315 kcal/mol, with an RMSD of 0.4634 nm and RMSF of 0.3234 nm. Compared to Sorafenib, Compound 9 exhibited superior docking selectivity and activity. Conclusion: Computational analyses suggest that Compound 9 is a promising candidate as a highly selective VEGFR-2 inhibitor. Nonetheless, due to the inherent limitations of in silico docking studies, further chemical synthesis and experimental biological validation are required to confirm its potential.
科研通智能强力驱动
Strongly Powered by AbleSci AI