Document Detail

Reference energy extremal optimization: a stochastic search algorithm applied to computational protein design.
MedLine Citation:
PMID:  18351599     Owner:  NLM     Status:  MEDLINE    
We adapt a combinatorial optimization algorithm, extremal optimization (EO), for the search problem in computational protein design. This algorithm takes advantage of the knowledge of local energy information and systematically improves on the residues that have high local energies. Power-law probability distributions are used to select the backbone sites to be improved on and the rotamer choices to be changed to. We compare this method with simulated annealing (SA) and motivate and present an improved method, which we call reference energy extremal optimization (REEO). REEO uses reference energies to convert a problem with a structured local-energy profile to one with more random profile, and extremal optimization proves to be extremely efficient for the latter problem. We show in detail the large improvement we have achieved using REEO as compared to simulated annealing and discuss a number of other heuristics we have attempted to date.
Naigong Zhang; Chen Zeng
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, Non-P.H.S.    
Journal Detail:
Title:  Journal of computational chemistry     Volume:  29     ISSN:  1096-987X     ISO Abbreviation:  J Comput Chem     Publication Date:  2008 Aug 
Date Detail:
Created Date:  2008-06-16     Completed Date:  2008-08-11     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9878362     Medline TA:  J Comput Chem     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1762-71     Citation Subset:  IM    
Copyright Information:
2008 Wiley Periodicals, Inc.
Department of Physics, George Washington University, Washington, District of Columbia 20052, USA.
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MeSH Terms
Proteins / chemistry*
Stochastic Processes*
Reg. No./Substance:

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