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Computational Prediction of Protein Secondary Structure from Sequence
1Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada.
Current Protocols in Protein Science
|November 2, 2016
Summary
Predicting protein secondary structure, like alpha-helices and beta-strands, is crucial. Modern computational methods achieve 70-80% accuracy and are accessible via web servers.
Area of Science:
- Biochemistry
- Structural Biology
- Bioinformatics
Background:
- Protein secondary structure refers to local, repetitive conformations like alpha-helices and beta-strands.
- Computational prediction of protein secondary structure has evolved through three generations of methods.
Purpose of the Study:
- To summarize recent third-generation computational predictors for protein secondary structure.
- To discuss their inputs, outputs, availability, performance, and interpretation.
Main Methods:
- Review of recent third-generation secondary structure prediction methods.
- Analysis of 3-class (helix, strand, coil) and 8-class secondary structure state predictions.
- Evaluation of predictor accuracy and accessibility.
Main Results:
- Third-generation predictors demonstrate high accuracy, ranging from 70% to 80%.
- These advanced prediction tools are readily available as user-friendly web servers and standalone software.
Conclusions:
- Modern computational methods provide accurate and accessible predictions of protein secondary structure.
- End-users can easily perform and interpret secondary structure predictions using available software.
