A framework for protein structure classification and identification of novel protein structures
2006
A Framework for Protein Structure Classification
Sample size: 5289
publication
Evidence: high
Author Information
Author(s): Kim You Jung, Patel Jignesh M
Primary Institution: University of Michigan
Hypothesis
Can an automated method accurately classify and identify novel protein structures?
Conclusion
The proCC method effectively classifies new protein domains and suggests new domain families with high accuracy.
Supporting Evidence
- The proCC method achieved 86.0%, 87.7%, and 90.5% classification accuracy at family, superfamily, and fold levels respectively.
- The method is about 15-19% more accurate than existing methods like SGM and comparable to SCOPmap.
- It produced clusters that closely correspond to new families in SCOP 1.69.
Takeaway
This study created a computer program that helps scientists sort and understand new proteins by comparing their shapes to known ones.
Methodology
The study used a three-component framework involving structure comparison, classification, and clustering to classify protein domains.
Limitations
The method cannot completely replace manual classification and may not capture all nuances of protein classification.
Digital Object Identifier (DOI)
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