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Barrel structures in proteins: automatic identification and classification including a sequence analysis of TIM
N Nagano1, E G Hutchinson, J M Thornton
1Biomolecular Structure and Modeling Group, Biochemistry & Molecular Biology Department, University College London, United Kingdom.
Protein Science : a Publication of the Protein Society
|November 5, 1999
Summary
Automated methods analyze protein beta-barrel structures using geometric parameters. Most identified barrels belong to enzyme families, with the triose phosphate isomerase (TIM) barrel fold being most frequent.
Area of Science:
- Structural bioinformatics
- Computational biology
- Protein structure analysis
Background:
- Protein beta-barrels are common structural motifs.
- Automated analysis is needed for large protein datasets.
Purpose of the Study:
- Develop automated methods to identify and classify beta-barrel structures.
- Analyze geometric parameters like strand and shear numbers.
- Investigate the prevalence and types of protein families with barrel structures.
Main Methods:
- Developed automated algorithms for beta-barrel identification from coordinate data.
- Classified barrels based on strand number (n) and shear number (S).
- Analyzed side chain layers and amino acid propensities for specific barrel types (e.g., TIM barrels).
Main Results:
- Identified 1,316 beta-barrels in the Protein Data Bank (January 1998).
- Found 68% of barrel structures are associated with enzymes.
- The triose phosphate isomerase (TIM) barrel fold is the most abundant nonhomologous entry.
Conclusions:
- Automated methods effectively classify protein beta-barrels.
- Enzymes represent the majority of protein families with barrel structures.
- Hydrophobic residues play a key role in the stability of eight-stranded parallel beta-barrels.