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<p>Vascular Endothelial Growth Factor Receptor 2 (VEGFR2) tyrosine kinase plays a pivotal role in angiogenesis, a biological process essential for tumor growth and metastasis. As a central mediator of endothelial cell proliferation, migration, and survival, VEGFR2 is considered a major therapeutic target in anticancer drug development. The aim of this study was to employ a comprehensive in silico approach to identify novel VEGFR2 inhibitors with the potential to improve current anticancer strategies. This study led to the generation of 470 pharmacophore models based on a curated dataset of known VEGFR2 inhibitors. To identify the most predictive model, a Quantitative Structure–Activity Relationship (QSAR) analysis was subsequently conducted, leading to the selection of an optimal pharmacophore. Subsequently, a virtual screening workflow was applied to two distinct chemical libraries, a library of cabozantinib analogues and a library of natural compounds. This integrated approach, combining pharmacophore mapping, QSAR modeling, and molecular docking (PDB ID: 3WZD), followed by Absorption, Distribution, Metabolism, Excretion, and Toxicity profiling, resulted in the identification of two promising hits. Notably, the first hit represents a structurally novel candidate, while the second hit was identified as a structural analogue of Cabozantinib.The identification of this analogue through our workflow further supports the reliability and internal consistency of the screening strategy. Both compounds displayed favorable binding affinities and interaction profiles compared to Sorafenib used as the reference inhibitor. Finally, 100 ns molecular dynamics simulation validated the stable interactions of these hits within the VEGFR2 active site, reinforcing their potential as lead compounds for further development in cancer treatment.</p> Graphical abstract <p></p>

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Discovery of potent VEGFR2 inhibitors as anticancer target, using pharmacophore based virtual screening, molecular docking and molecular dynamics simulation

  • 期刊论文

  • 发表日期：

    2026年6月16日

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  • Ouafa Meziani,
  • Fouad Ferkous,
  • Samira Ait Kaki,
  • Khairedine Kraim,
  • Youcef Saihi,
  • Magdy M. D. Mohammed,
  • Amany M. A. Osman

摘要

Vascular Endothelial Growth Factor Receptor 2 (VEGFR2) tyrosine kinase plays a pivotal role in angiogenesis, a biological process essential for tumor growth and metastasis. As a central mediator of endothelial cell proliferation, migration, and survival, VEGFR2 is considered a major therapeutic target in anticancer drug development. The aim of this study was to employ a comprehensive in silico approach to identify novel VEGFR2 inhibitors with the potential to improve current anticancer strategies. This study led to the generation of 470 pharmacophore models based on a curated dataset of known VEGFR2 inhibitors. To identify the most predictive model, a Quantitative Structure–Activity Relationship (QSAR) analysis was subsequently conducted, leading to the selection of an optimal pharmacophore. Subsequently, a virtual screening workflow was applied to two distinct chemical libraries, a library of cabozantinib analogues and a library of natural compounds. This integrated approach, combining pharmacophore mapping, QSAR modeling, and molecular docking (PDB ID: 3WZD), followed by Absorption, Distribution, Metabolism, Excretion, and Toxicity profiling, resulted in the identification of two promising hits. Notably, the first hit represents a structurally novel candidate, while the second hit was identified as a structural analogue of Cabozantinib.The identification of this analogue through our workflow further supports the reliability and internal consistency of the screening strategy. Both compounds displayed favorable binding affinities and interaction profiles compared to Sorafenib used as the reference inhibitor. Finally, 100 ns molecular dynamics simulation validated the stable interactions of these hits within the VEGFR2 active site, reinforcing their potential as lead compounds for further development in cancer treatment.

Graphical abstract