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A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
Defining and predicting structurally conserved regions in protein superfamilies
Ivan K Huang1, Jimin Pei, Nick V Grishin
1Department of Mathematics, Rice University, Houston, TX 77005, USA. 91huangi@gmail.com
Bioinformatics (Oxford, England)
|November 30, 2012
Summary
Structurally conserved regions (SCRs) in proteins can be predicted using sequence and single structure data. Combining these features optimizes prediction accuracy for identifying SCRs in protein families.
Area of Science:
- Structural bioinformatics
- Computational biology
- Protein structure analysis
Background:
- Protein structures are more conserved than sequences, with structurally conserved regions (SCRs) present even in divergent families.
- Defining SCRs typically requires multiple homologous structures, which are not always available.
- Predicting SCRs from limited data (single structure, homologous sequences) is crucial for applications like homology modeling.
Purpose of the Study:
- To develop and evaluate methods for predicting structurally conserved regions (SCRs) in proteins using limited structural and sequence information.
- To assess the performance of predictions based on single structures versus homologous sequences.
- To identify optimal feature combinations for accurate SCR prediction.
Main Methods:
- Devised a structural conservation index (SCI) using pairwise DaliLite alignments of homologous structures.
- Compiled a database of SCRs from 386 SCOP superfamilies (6489 protein domains).
- Trained artificial neural networks using features from single structures and homologous sequences, employing 5-fold cross-validation.
Main Results:
- Predictions using single structure features performed similarly to those using homologous sequences.
- Combining sequence and structural features yielded optimal prediction accuracy (0.755) and Matthews correlation coefficient (0.476).
- The study demonstrates the feasibility of effective SCR prediction even without multiple homologous structures.
Conclusions:
- Predicting structurally conserved regions (SCRs) is achievable using sequence data and a single protein structure.
- Integrating both sequence and structural features significantly improves SCR prediction accuracy.
- The developed methods and database facilitate further research in protein structure-sequence relationships.
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