A physical approach to protein structure prediction: CASP4 results
We describe our global optimization method called Stochastic Perturbation with Soft Constraints (SPSC), which uses information from known proteins to predict secondary structure, but not in the tertiary structure predictions or in generating the terms of the physics-based energy function. Our approach is also characterized by the use of an all atom energy function that includes a novel hydrophobic solvation function derived from experiments that shows promising ability for energy discrimination against misfolded structures. We present the results obtained using our SPSC method and energy function for blind prediction in the 4th Critical Assessment of Techniques for Protein Structure Prediction (CASP4) competition, and show that our approach is more effective on targets for which less information from known proteins is available. In fact our SPSC method produced the best prediction for one of the most difficult targets of the competition, a new fold protein of 240 amino acids.
- Research Organization:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Director, Office of Science. Office of Advanced Scientific Computing Research. Mathematical, Information, and Computational Sciences Division (US)
- DOE Contract Number:
- AC03-76SF00098
- OSTI ID:
- 821004
- Report Number(s):
- LBNL-47555; BIOJAU; R&D Project: 366843; TRN: US200407%%127
- Journal Information:
- Biophysical Journal, Vol. 82, Issue 1; Other Information: Journal Publication Date: 01/2002; PBD: 27 Feb 2001; ISSN 0006-3495
- Country of Publication:
- United States
- Language:
- English
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