In Silico Drug Design of Potential Direct Inhibitors of Vascular Endothelial Growth Factor a (VEGF-A)

Abstract

Cancer is a disease characterized by uncontrolled cell growth forming tumors. A key pathway supporting cancerous growth is angiogenesis, the neovascularization from existing blood vessels. This study addresses the need for alternative cancer treatments by targeting angiogenesis through inhibiting the VEGFA (Vascular Endothelial Growth Factor A) pathway. Current therapies are costly, mainly utilizing monoclonal antibodies. As such, the study aimed identify potential direct inhibitors of active VEGFA from FDA-approved drugs and metabolites of DOH-endorsed medicinal plants. This study utilized structure-based drug design (SBDD) which included protein structure preparation, ligand library creation, molecular docking, interaction visualization, safety and efficacy prediction, and hit optimization, utilizing tools like Vina-GPU 2.0, ODDT, ProLIF, LigPlot+, ADMETLab 2.0, and ADMETopt. Among the four predicted binding sites, the study focused on the site with known receptor-binding function. Docking simulations revealed 28 compounds with strong binding affinities, 7 of which have known anti-cancer activities. Upon further optimization, two manually redesigned molecules, MD4 and MD7, showed the strongest interactions with VEGFA. However, their suboptimal physicochemical and ADMET properties imply the need for further manual optimization (e.g., improve toxicity values). Among the ADMETopt-generated compounds, G2OPT1267 and G3OPT2958 showed good binding affinities and significant residue interactions, with acceptable physicochemical and ADMET properties. In conclusion, this study contributed to angiogenic pathway-targeted therapeutics research. Further research should refine compound redesign methodologies, explore prediction model-based optimization, and conduct in vitro experiments to validate anti-angiogenic efficacy of the identified compounds.