An integrated virtual screening approach for VEGFR-2 inhibitors

Area of Science:

• Computational Chemistry
• Drug Discovery
• Bioinformatics

Background:

• Virtual screening (VS) is crucial for identifying potential drug candidates.
• Current VS methods like molecular docking and pharmacophore screening have limitations in accuracy.
• The bottleneck in VS is the unreliable ranking of compounds by scoring functions.

Purpose of the Study:

• To evaluate and compare the performance of individual and integrated VS methods.
• To develop and validate a comprehensive, multi-layered VS workflow.
• To enhance the accuracy and effectiveness of virtual hit selection in drug discovery.

Main Methods:

• Retrospective VS study on Vascular Endothelial Growth Factor Receptor 2 (VEGFR-2) inhibitors.
• Evaluation of molecular docking, fingerprint-based 2D similarity (ECFP_4), and multicomplex pharmacophore methods.
• Development of an integrated two-layer workflow: ECFP_4, followed by molecular docking, then pharmacophore screening.

Main Results:

• The integrated two-layer workflow demonstrated significantly improved VS performance.
• The combined approach successfully identified VEGFR-2 inhibitors from the DUD-E database.
• Compared to 45 published methods, this integrated approach outperformed 43, showing high effectiveness.

Conclusions:

• Integrating diverse VS methods, particularly a ligand-based approach followed by docking and pharmacophore modeling, enhances hit identification.
• The developed integrated workflow offers a robust strategy for improving VS accuracy.
• This integrated VS approach is adaptable for screening inhibitors against other biological targets.