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Accurately Predicting Disordered Regions of Proteins Using Rosetta ResidueDisorder Application
Stephanie S Kim1, Justin T Seffernick1, Steffen Lindert1
1Department of Chemistry and Biochemistry , Ohio State University , Columbus , Ohio 43210 , United States.
The Journal of Physical Chemistry. B
|March 30, 2018
Summary
Predicting intrinsically disordered protein regions is crucial for understanding disease and developing therapeutics. A new Rosetta-based method accurately identifies these disordered regions, outperforming existing tools.
Area of Science:
- Biochemistry and Structural Biology
- Computational Biology and Bioinformatics
Background:
- Many functional proteins contain intrinsically disordered regions (IDRs) essential for biological processes like gene regulation and signal transduction.
- IDRs are implicated in various human diseases, making them significant targets for therapeutic development.
- Accurate prediction of protein disorder is vital for understanding protein function and disease mechanisms.
Purpose of the Study:
- To introduce a novel, user-friendly computational method for predicting intrinsically disordered protein regions.
- To evaluate the performance of this new method against established disorder prediction tools.
- To demonstrate the utility of protein structure prediction software, Rosetta, in identifying disordered protein segments.
Main Methods:
- Utilized the Rosetta software to predict global protein structures for benchmark and test datasets.
- Analyzed Rosetta energy scores to identify statistically significant differences between ordered and disordered protein regions.
- Developed the Rosetta ResidueDisorder method for predicting disordered protein regions based on Rosetta scores.
Main Results:
- Demonstrated a statistically significant difference in Rosetta scores between disordered and ordered protein regions, with lower scores in disordered regions.
- Achieved prediction accuracies of 71.77% on a benchmark dataset and 65.37% on an independent test dataset.
- Showcased that the Rosetta ResidueDisorder method outperformed other established disorder prediction tools.
Conclusions:
- The Rosetta ResidueDisorder method provides a reliable and accurate approach for predicting intrinsically disordered protein regions.
- Protein structure prediction scores from Rosetta can effectively distinguish between ordered and disordered protein segments.
- This method offers a valuable tool for researchers studying protein function, disease, and drug discovery.
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