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A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
Assessing the accuracy of template-based structure prediction metaservers by comparison with structural genomics
Dominik Gront1, Marek Grabowski, Matthew D Zimmerman
1Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA 22908, USA.
Journal of Structural and Functional Genomics
|October 23, 2012
Summary
Automated protein structure prediction servers accurately modeled about a fourth of targets from structural genomics (SG) programs. Success depended heavily on sequence identity to known Protein Data Bank (PDB) structures.
Area of Science:
- Computational biology
- Structural biology
- Bioinformatics
Background:
- The rapid expansion of protein sequence data necessitates efficient methods for structural determination.
- Structural genomics (SG) aims to experimentally determine protein structures.
- Theoretical structure prediction offers a complementary approach to experimental methods.
Purpose of the Study:
- To evaluate the accuracy of automated template-based protein structure prediction metaservers (genesilico.pl and bioinfo.pl).
- To assess the performance of these metaservers using targets from structural genomics programs.
- To compare the accuracy of metaserver predictions with experimental structures and results from the CASP competition.
Main Methods:
- Assessed prediction accuracy by comparing automated models to experimentally determined structures.
- Utilized 199 targets from structural genomics programs.
- Defined "correct" prediction as >70% of alpha carbons within 2 Å of experimental positions.
- Analyzed the impact of sequence identity to Protein Data Bank (PDB) templates on prediction accuracy.
- Compared metaserver performance against CASP8 competition results.
Main Results:
- Metaservers accurately predicted the structures of approximately 25% of the tested SG targets.
- High accuracy was achieved primarily for targets with >25% sequence identity to existing PDB structures.
- Targets with lower sequence identity were generally not predicted with high accuracy.
- Models generated by CASP8 participants demonstrated significantly higher accuracy than those from the evaluated metaservers.
Conclusions:
- Automated template-based metaservers show moderate success in protein structure prediction, particularly for homologous sequences.
- Prediction accuracy is strongly correlated with the availability and similarity of template structures in the PDB.
- Human expert participation in competitions like CASP yields superior structure prediction models compared to current automated metaservers.
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