Vascular Endothelial Growth Factor (VEGF) has a greater impact on carcinogenesis, and it is the most significant receptor in mediating the mutagenesis and permeability of endothelial cells. Here, we report the identification of potential VEGFR-2 inhibitors as new putative anti-cancer agents. In this regard, a pharmacophore model was generated, considering established potent VEGFR2 inhibitors. This model was further applied for the virtual screening of the ZINC database and the feature-based design of another eight molecules (B1–B8). Examining these molecules using sequential computational approaches including molecular docking, molecular dynamic simulation, and DFT analysis leads to the identification of compounds B3, B5, and B7 as potential inhibitors that showed better binding affinity, stability, and interaction mechanisms concerning the reference control, Sorafenib. Further, the Lipinski rule filters and ADMET analysis support the selected compounds as drug candidates subjected to experimental validation.
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