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Updated: Jul 20, 2026
07:08
Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
Published on: July 14, 2015
Revealing divergent evolution, identifying circular permutations and detecting active-sites by protein structure
Luonan Chen1, Ling-Yun Wu, Yong Wang
1Institute of Systems Biology, Shanghai University, Shanghai 200444, China. chen@eic.osaka-sandai.ac.jp
BMC Structural Biology
|September 5, 2006
Summary
This study introduces a new multi-objective optimization method for accurate and efficient protein structure comparison. The approach effectively identifies divergent evolution, circular permutations, and active-sites, outperforming existing methods.
Area of Science:
- Computational Biology
- Structural Bioinformatics
Background:
- Protein structure comparison is crucial for various biological applications.
- Key applications include structure prediction, fold classification, motif discovery, and docking.
Purpose of the Study:
- To develop a novel, accurate, and efficient method for protein structure comparison.
- To enable the identification of evolutionary relationships, structural variations, and functional sites.
Main Methods:
- Formulated structure alignment as a multi-objective optimization problem.
- Maximized aligned atom count while minimizing root mean square distance.
- Employed a sequence order-independent strategy and a bipartite matching algorithm.
Main Results:
- Achieved significant improvements in quality and efficiency over existing methods.
- Demonstrated the ability to detect divergent evolution, circular permutations, and active-sites.
- The algorithm exhibits near-linear complexity with respect to the number of atoms.
Conclusions:
- A novel multi-objective optimization framework accurately aligns protein structures.
- A fast and efficient algorithm based on bipartite matching was developed.
- Computational convergence was theoretically proven and experimentally validated.
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