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<p>Cancer continues to be a major global health challenge due to the limited availability of highly specific and effective targeted therapies. Vascular Endothelial Growth Factor Receptor-2 (VEGFR-2) plays a central role in angiogenesis, which support tumour growth. Therefore, inhibiting VEGFR-2 is considered an effective strategy for blocking tumour vascularisation. This study explores the potential of indoline-based compounds as VEGFR-2 inhibitors using a combined computational approach. More than 18,000 indoline-based molecules were virtually screened against VEGFR-2 (PDB ID: 2OH4). Molecular docking was performed to identify compounds with strong binding affinity. ADME studies were used to evaluate drug-likeness and pharmacokinetic suitability. Molecular Dynamics (MD) simulations of 100&#xa0;ns were then carried out for the top three candidates (IP-1, IP-2, and IP-3) along with the co-crystallised ligand to assess their stability and interactions within the binding pocket.</p><p>Docking results identified IP-1, IP-2, and IP-3 as strong VEGFR-2 binders. ADME analysis showed moderate solubility (Log S: − 6.24 to − 9.20), acceptable SASA values (607–819), and controlled BBB permeability (QPlogBB: 0.48, 0.24, 0.08), which aligns with typical kinase inhibitor characteristics. Most other parameters, including dipole moment and logKhsa, were within recommended ranges. MD simulations revealed that IP-1 formed stable hydrogen bonds with key residues ASP1044 (43.42%) and GLU883 (10.84%), similar to the reference ligand. IP-2 and IP-3 also interacted with these residues but with lower occupancy.</p><p>Overall, IP-1 demonstrated the most stable and favourable interaction profile, suggesting strong VEGFR-2 inhibitory potential. IP-2 and IP-3 also showed promising characteristics. These findings support further in vitro and in vivo evaluation of these molecules as potential anti-angiogenic and anti-cancer agents.</p> Graphical abstract <p></p>

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Computational identification of lead compounds against cancer through screening of an indoline-pyrimidine-based library

  • 期刊论文

  • 发表日期：

    2026年4月10日

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  • Madhukar Prabhash,
  • Volkan Eyupoglu,
  • Ravi Rawat

摘要

Cancer continues to be a major global health challenge due to the limited availability of highly specific and effective targeted therapies. Vascular Endothelial Growth Factor Receptor-2 (VEGFR-2) plays a central role in angiogenesis, which support tumour growth. Therefore, inhibiting VEGFR-2 is considered an effective strategy for blocking tumour vascularisation. This study explores the potential of indoline-based compounds as VEGFR-2 inhibitors using a combined computational approach. More than 18,000 indoline-based molecules were virtually screened against VEGFR-2 (PDB ID: 2OH4). Molecular docking was performed to identify compounds with strong binding affinity. ADME studies were used to evaluate drug-likeness and pharmacokinetic suitability. Molecular Dynamics (MD) simulations of 100 ns were then carried out for the top three candidates (IP-1, IP-2, and IP-3) along with the co-crystallised ligand to assess their stability and interactions within the binding pocket.

Docking results identified IP-1, IP-2, and IP-3 as strong VEGFR-2 binders. ADME analysis showed moderate solubility (Log S: − 6.24 to − 9.20), acceptable SASA values (607–819), and controlled BBB permeability (QPlogBB: 0.48, 0.24, 0.08), which aligns with typical kinase inhibitor characteristics. Most other parameters, including dipole moment and logKhsa, were within recommended ranges. MD simulations revealed that IP-1 formed stable hydrogen bonds with key residues ASP1044 (43.42%) and GLU883 (10.84%), similar to the reference ligand. IP-2 and IP-3 also interacted with these residues but with lower occupancy.

Overall, IP-1 demonstrated the most stable and favourable interaction profile, suggesting strong VEGFR-2 inhibitory potential. IP-2 and IP-3 also showed promising characteristics. These findings support further in vitro and in vivo evaluation of these molecules as potential anti-angiogenic and anti-cancer agents.

Graphical abstract