Computational identification of potential VEGFR2 inhibitors using integrated pharmacophore modeling, QSAR analysis, molecular docking, dynamics simulation, and virtual screening followed by in vitro bioassays.

Angiogenesis plays a crucial role in tumor growth, progression, and metastasis, making the vascular endothelial growth factor receptor-2 (VEGFR2) a key therapeutic target in anticancer drug development. In this study, an integrated in silico and in vitro strategy was applied to identify novel potential inhibitors of VEGFR2. Initially, a dataset of VEGFR2 inhibitors with reported biological activities was collected from the ChEMBL database. Pharmacophore models were generated using a ligand-based approach, and the most relevant hypotheses were selected to construct three-dimensional quantitative structure-activity relationship (3D-QSAR) models. Subsequently, a virtual screening workflow including pharmacophore mapping, QSAR modeling, and molecular docking using the VEGFR2 crystal structure (PDB ID: 3WZD), followed by Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) filtering, was performed to identify the most promising hits. Based on the computational screening results, ten compounds were purchased and experimentally evaluated for their antiproliferative activity using the MTT cytotoxicity assay on three human cancer cell lines known to express VEGFR2: MCF-7 and MDA-MB-231 (breast cancer) and HepG2 (hepatocellular carcinoma). Four hits exhibited moderate antiproliferative activity against HepG2 cells (IC