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Optimization of compound ranking for structure-based virtual ligand screening using an established FRED-Surflex
Jiangfeng Du1, Ivo W M Bleylevens, Albert V Bitorina
1Department of Biochemistry, Cardiovascular Research Institute Maastricht, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands.
Chemical Biology & Drug Design
|August 15, 2013
Summary
Combining scores from multiple protein targets using consensus weighted scoring improves virtual ligand screening enrichment. This hierarchical method, using FRED and Surflex, optimizes ensemble docking for better drug discovery outcomes.
Area of Science:
- Computational chemistry
- Drug discovery
- Molecular modeling
Background:
- Virtual screening campaigns often use multiple target conformers.
- Optimizing scoring combinations for hierarchical docking methods remains understudied.
Purpose of the Study:
- To develop and optimize a hierarchical method for combining scores from multiple protein targets in virtual screening.
- To evaluate consensus scoring strategies for ensemble docking using FRED and Surflex programs.
Main Methods:
- Screened 59,479 compounds against multiple conformers of four protein targets.
- Applied and adapted an established hierarchical method using FRED and Surflex.
- Validated the protocol on ten diverse datasets from the Directory of Useful Decoys (DUD).
Main Results:
- Consensus weighted scoring of multiple target conformers consistently outperformed other methods.
- A hierarchical approach involving FRED consensus followed by Surflex screening yielded optimal ensemble docking performance.
- Identified target-specific optimal methods and strategies for enrichment optimization.
Conclusions:
- Consensus weighted scoring is crucial for improving virtual ligand screening enrichment.
- A hierarchical FRED-Surflex protocol offers superior performance in ensemble docking.
- The study provides a framework for optimizing virtual screening enrichment for diverse targets.
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