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De-orphaning the structural proteome through reciprocal comparison of evolutionarily important structural features.
R Matthew Ward1, Serkan Erdin, Tuan A Tran
1Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States of America.
Plos One
|May 8, 2008
Summary
This study introduces Evolutionary Trace Annotation (ETA), a new method for predicting protein function by analyzing structural features. ETA achieves 100% accuracy in controls and reliably predicts functions for unannotated proteins.
Area of Science:
- Structural biology
- Bioinformatics
- Computational biology
Background:
- Protein function prediction is crucial but challenging due to the growing number of unannotated structures.
- Current methods often rely on sequence or structural similarity, which can be limited.
Purpose of the Study:
- To develop and validate a novel algorithm for accurate protein function prediction using evolutionary and structural information.
- To improve the scalability and accuracy of identifying functional sites in protein structures.
Main Methods:
- Developed algorithms to extract 3D structural motifs (templates) based on Evolutionary Trace (ET) residue importance.
- Implemented a fast matching algorithm for large-scale reciprocal searches of structural motifs.
- Applied the Evolutionary Trace Annotation (ETA) pipeline to structural genomics datasets.
Main Results:
- Achieved 100% specificity and ~60% sensitivity in controlled enzyme datasets.
- ETA pipeline demonstrated 92% accuracy on a large set of structural genomics enzymes.
- Successfully predicted enzymatic functions for 320 unannotated proteins from structural genomics data.
Conclusions:
- The ETA pipeline offers a reliable, scalable, and accurate method for predicting protein function without prior mechanistic knowledge.
- This approach significantly aids in annotating the structural proteome by integrating sequence-structure-function data.
- ETA has the potential to accelerate functional characterization of newly discovered proteins.
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