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Docking by structural similarity at protein-protein interfaces
Rohita Sinha1, Petras J Kundrotas, Ilya A Vakser
1Center for Bioinformatics, The University of Kansas, Lawrence, Kansas 66047-1620, USA.
Proteins
|August 18, 2010
Summary
Structural alignment improves protein docking accuracy when sequence homology is low. This method identifies novel protein-protein interactions missed by traditional sequence-based approaches, enhancing computational biology tools.
Area of Science:
- Computational Biology
- Structural Bioinformatics
- Biochemistry
Background:
- Protein-protein interactions are crucial for cellular functions.
- Template-free docking methods have limitations.
- Template-based methods rely on sequence similarity, which is often insufficient.
Purpose of the Study:
- To develop and validate a novel protein docking algorithm based on local structural alignment.
- To improve the accuracy of protein complex modeling, especially when sequence homology is low.
Main Methods:
- Developed a partial structure alignment algorithm comparing monomer structures to known interfaces.
- Generated a library of interfaces from Protein Data Bank (PDB) cocrystallized complexes.
- Validated the algorithm on DOCKGROUND benchmark sets, optimizing interface residue definition.
Main Results:
- Partial structure alignment yielded more accurate protein docking models than full structure alignment.
- Identified effective templates with low sequence identity, often missed by sequence-based methods.
- Optimized performance with interface residues defined within a 12 Å distance.
Conclusions:
- Structural alignment techniques significantly enhance the protein docking toolkit.
- Combining structural alignment with template-free docking substantially increases success rates.
- This approach offers a valuable alternative for modeling protein-protein interactions with limited sequence homology.
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