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A Fluorescence-based Lymphocyte Assay Suitable for High-throughput Screening of Small Molecules
Published on: March 10, 2017
Computational identification of lead compounds against cancer through screening of an indoline-pyrimidine-based
Madhukar Prabhash1, Volkan Eyupoglu2, Ravi Rawat3
1Department of Pharmaceutical Chemistry, Bhavdiya Institute of Pharmaceutical Sciences and Research, Ayodhya, U.P. 224126 India.
Abstract:
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.
Insights
This study identified novel indoline-based compounds as potential inhibitors of Vascular Endothelial Growth Factor Receptor-2 (VEGFR-2). Compound IP-1 showed the most promising stability and interaction profile for anti-cancer drug development.
Area of Science:
- Medicinal Chemistry
- Computational Drug Discovery
- Oncology
Background:
- Cancer treatment faces challenges due to limited targeted therapies.
- Vascular Endothelial Growth Factor Receptor-2 (VEGFR-2) is crucial for tumor angiogenesis and growth.
- Inhibiting VEGFR-2 is a key strategy for anti-cancer drug development.
Purpose of the Study:
- To computationally screen indoline-based compounds for VEGFR-2 inhibitory potential.
- To evaluate the drug-likeness and pharmacokinetic properties of top candidates.
- To assess the stability and binding interactions of lead compounds using molecular dynamics.
Main Methods:
- Virtual screening of over 18,000 indoline molecules against VEGFR-2 (PDB ID: 2OH4).
- Molecular docking to identify high-affinity binders.
- ADME analysis for drug-likeness and pharmacokinetic evaluation.
- 100 ns Molecular Dynamics (MD) simulations for top candidates (IP-1, IP-2, IP-3).
Main Results:
- Docking identified IP-1, IP-2, and IP-3 as potent VEGFR-2 binders.
- ADME analysis indicated moderate solubility and acceptable permeability for kinase inhibitors.
- MD simulations showed IP-1 formed stable interactions with key residues ASP1044 and GLU883, similar to the reference ligand.
- IP-1 exhibited the most stable binding profile, suggesting strong inhibitory potential.
Conclusions:
- Indoline-based compounds, particularly IP-1, show significant potential as VEGFR-2 inhibitors.
- These compounds warrant further in vitro and in vivo investigation as anti-angiogenic and anti-cancer agents.
- Computational approaches are effective for identifying novel drug candidates for cancer therapy.
