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Correlation between performance of QM/MM docking and simple classification of binding sites
Jae Yoon Chung1, Jung-Mi Hah, Art E Cho
1Department of Bioinformatics and Biotechnology, Korea University, Jochiwon, Chungnam, Korea.
Journal of Chemical Information and Modeling
|October 6, 2009
Summary
Quantum mechanics/molecular mechanics (QM/MM) docking shows improved performance over conventional docking, especially for hydrophobic binding sites with hydrophilic interactions. SiteMap classification helps predict optimal docking strategies.
Area of Science:
- Computational chemistry
- Structural biology
- Drug discovery
Background:
- Molecular docking is crucial for drug discovery, predicting ligand-protein interactions.
- Quantum mechanics/molecular mechanics (QM/MM) methods offer higher accuracy but are computationally intensive.
- SiteMap provides binding site classification based on physicochemical properties.
Purpose of the Study:
- To investigate the utility of SiteMap for classifying binding sites.
- To evaluate the performance of QM/MM docking (QPLD) versus conventional docking (Glide) based on SiteMap classifications.
- To establish correlations between binding site characteristics and docking performance.
Main Methods:
- Classified 455 protein data bank cocrystal complexes into three groups using SiteMap's hydrophilic/hydrophobic balance.
- Tested Glide and QPLD docking programs on these classified groups.
- Analyzed docking performance differences and correlated them with binding site properties.
Main Results:
- QPLD consistently outperformed Glide across all binding site classifications.
- QM/MM docking demonstrated the most significant improvements for sites that are primarily hydrophobic yet possess substantial hydrophilic interactions.
- SiteMap classification effectively differentiated binding sites, influencing docking outcomes.
Conclusions:
- QM/MM docking is a valuable advancement, particularly for complex binding site environments.
- SiteMap classification can guide the selection of appropriate docking methods for enhanced accuracy.
- Further research should explore refining QM/MM protocols and SiteMap's predictive capabilities.
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