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Docking of protein molecular surfaces with evolutionary trace analysis.
Eiji Kanamori1, Yoichi Murakami, Yuko Tsuchiya
1Japan Biological Information Research Center, Japan Biological Informatics Consortium, 2-41-6 Aomi, Koto-ku, Tokyo 135-0064, Japan.
Proteins
|September 7, 2007
Summary
We developed a new computational method for predicting protein-protein complexes using shape complementarity and evolutionary trace analysis. This approach achieved native-like predictions for several targets in the CAPRI assessment.
Area of Science:
- Computational biology
- Structural biology
- Bioinformatics
Background:
- Predicting protein-protein interactions is crucial for understanding cellular functions.
- Existing methods often struggle with accuracy and efficiency in complex prediction.
- Molecular surface shape complementarity and residue conservation are key factors in complex formation.
Purpose of the Study:
- To develop and evaluate a novel computational method for predicting protein-protein complexes.
- To integrate shape complementarity and evolutionary trace analysis for improved docking accuracy.
- To assess the method's performance on standardized benchmark datasets like CAPRI targets.
Main Methods:
- Developed a docking approach optimizing an object function that combines shape complementarity and residue conservation.
- Utilized evolutionary trace (ET) analysis to identify conserved residues at interaction interfaces.
- Employed a genetic algorithm combined with Monte Carlo sampling for molecular docking optimization.
- Validated the method using targets from the Critical Assessment of PRedicted Interactions (CAPRI) benchmark.
Main Results:
- The developed method successfully generated native-like predictions for several CAPRI targets.
- The integration of shape complementarity and sequence conservation improved docking accuracy.
- Analysis revealed that evolutionary conservation information is most beneficial for specific protein categories, such as signaling proteins and enzymes.
Conclusions:
- The novel computational method shows promise for accurate protein-protein complex prediction.
- Combining geometric and evolutionary information enhances docking performance.
- The utility of evolutionary conservation in docking is context-dependent, particularly for signaling proteins and enzymes.
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