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Atomic Scale Structural Studies of Macromolecular Assemblies by Solid-state Nuclear Magnetic Resonance Spectroscopy
Published on: September 17, 2017
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Accessible surface area from NMR chemical shifts
Noor E Hafsa1, David Arndt, David S Wishart
1Department of Computing Science, University of Alberta, Edmonton, Canada.
Journal of Biomolecular NMR
|June 17, 2015
Summary
Accessible surface area (ASA) prediction for proteins is improved using the novel ShiftASA algorithm. This machine learning method combines chemical shifts and sequence data for accurate fractional ASA estimation.
Area of Science:
- Biochemistry and Structural Biology
- Computational Biology
- Biophysics
Background:
- Accessible surface area (ASA) quantifies solvent-exposed molecular surface area.
- ASA is crucial for understanding protein hydrophobicity, structure, and function.
- Predicting ASA from protein sequences is challenging but valuable for structural constraints.
Purpose of the Study:
- To develop a novel method for accurately estimating per-residue fractional ASA values in water-soluble proteins.
- To explore the relationship between protein chemical shifts and ASA.
- To create a tool for utilizing ASA estimates as structural constraints for NMR studies.
Main Methods:
- Developed the ShiftASA algorithm using machine learning, specifically a boosted tree regression model.
- Integrated chemical-shift and sequence-derived features for ASA prediction.
- Evaluated ShiftASA performance on independent test sets of proteins.
Main Results:
- ShiftASA achieved a correlation coefficient of 0.79 on a test set of 65 proteins, an 8.2% improvement over sequence-only methods.
- On a separate set of 92 proteins, ShiftASA reported a mean correlation coefficient of 0.82, 12.3% better than existing methods.
- The algorithm accurately estimates fractional ASA values for water-soluble proteins.
Conclusions:
- ShiftASA provides a significant advancement in predicting protein fractional ASA.
- The integration of chemical shifts with sequence data enhances prediction accuracy.
- ShiftASA is available as a web server, facilitating its use in structural biology research.
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