Fragmented blind docking: a novel protein-ligand binding prediction protocol.

Area of Science:

• Computational chemistry
• Structural biology
• Drug discovery

Background:

• Accurate prediction of protein-ligand interactions is crucial for drug discovery.
• Identifying the binding site and pose is a prerequisite for effective virtual screening.
• Standard docking approaches often require prior knowledge of the binding site.

Purpose of the Study:

• To develop a novel blind docking protocol for simultaneous binding site identification and pose prediction.
• To enhance the accuracy of protein-ligand binding state prediction using MM/GBSA re-scoring.
• To evaluate the efficacy of the developed protocol in virtual screening pipelines.

Main Methods:

• Systematic exploration of protein volume using preliminary docking calculations.
• Application of Autodock-Vina for blind docking.
• Integration of MM/GBSA re-scoring for improved binding pose accuracy.
• Validation on diverse protein-ligand complexes including Heat Shock Protein 90 and HIV protease.

Main Results:

• The FRAD protocol successfully identified binding sites and predicted binding poses concurrently.
• MM/GBSA re-scoring significantly improved the accuracy of protein-ligand complex scoring.
• The combined approach demonstrated increased accuracy and efficiency compared to standard docking methods.
• Successful testing on over 300 protein-ligand systems from various datasets.

Conclusions:

• The FRAD protocol offers a powerful tool for blind docking, enabling simultaneous binding site identification and pose prediction.
• The integration with MM/GBSA re-scoring enhances the reliability of virtual screening, especially when the binding site is unknown.
• This approach streamlines the initial stages of drug discovery by reducing the need for manual intervention and prior structural information.