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A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
Physics-based protein-structure prediction using a hierarchical protocol based on the UNRES force field: assessment
S Ołdziej1, C Czaplewski, A Liwo
1Baker Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853-1301, USA.
Summary
We improved a physics-based protein structure prediction method using conformational space annealing. This method accurately predicts protein structures, including large alpha+beta proteins, advancing computational structural biology.
Area of Science:
- Computational Biology
- Structural Biology
- Biophysics
Background:
- Protein structure prediction is crucial for understanding biological function.
- Physics-based methods offer a promising avenue for accurate structure determination.
- Previous methods faced challenges with topological accuracy, especially for alpha+beta proteins.
Purpose of the Study:
- To describe recent improvements in a physics-based protein structure prediction method.
- To evaluate the enhanced method's performance in blind tests of protein structure prediction.
- To demonstrate progress in accurately predicting protein structures from amino acid sequences.
Main Methods:
- Utilizing a physics-based UNRES energy function for conformational space search.
- Employing conformational space annealing for global optimization.
- Converting coarse-grained structures to all-atom representation and energy minimization using ECEPP/3 force field.
Main Results:
- Successful prediction of large protein fragments (60-70 residues) with C(alpha) rmsd <6 A in the first blind test.
- Accurate prediction of whole protein structures (53-235 residues) in the second blind test, including a 102-residue alpha+beta protein (TM0487) with 7.3-A C(alpha) rmsd.
- Correct prediction of the topology for a 235-residue alpha-helical protein (PhoU) within 8 A rmsd.
Conclusions:
- The improved physics-based method shows significant progress in protein structure prediction accuracy.
- The method demonstrates capability in predicting complex protein topologies, including large alpha+beta proteins.
- This work advances the field of ab initio protein structure prediction using computational approaches.
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