標題: Soft energy function and generic evolutionary method for discriminating native from nonnative protein conformations
作者: Chiu, Yi-Yuan
Hwang, Jenn-Kang
Yang, Jinn-Moon
生物科技學系
生物資訊及系統生物研究所
Department of Biological Science and Technology
Institude of Bioinformatics and Systems Biology
關鍵字: energy function;protein structure prediction;structural bioinformatics;evolutionary computation
公開日期: 15-七月-2008
摘要: We have developed a soft energy function, termed GEMSCORE, for the protein structure prediction, which is one of emergent issues in the computational biology. The GEMSORE consists of the van der Waals, the hydrogen-bonding potential and the solvent potential with 12 parameters which are optimized by using a generic evolutionary method. The GEMSCORE is able to successfully identify 86 native proteins among 96 target proteins on six decoy sets from more 70,000 near-native structures. For these six benchmark datasets, the predictive performance of the GEMSCORE, based on native structure ranking and Z-scores, was superior to eight other energy functions. Our method is based solely on a simple and linear function and thus is considerably faster than other methods that rely on the additional complex calculations. In addition, the GEMSCORE recognized 17 and 2 native structures as the first and the second rank, respectively, among 21 targets in CASP6 (Critical Assessment of Techniques for Protein Structure Prediction). These results suggest that the GEMSCORE is fast and performs well to discriminate between native and normative structures from thousands of protein structure candidates. We believe that GEMSCORE is robust and should be a useful energy function for the protein structure prediction. (C) 2008 Wiley Periodicals, Inc.
URI: http://dx.doi.org/10.1002/jcc.20897
http://hdl.handle.net/11536/8574
ISSN: 0192-8651
DOI: 10.1002/jcc.20897
期刊: JOURNAL OF COMPUTATIONAL CHEMISTRY
Volume: 29
Issue: 9
起始頁: 1364
結束頁: 1373
顯示於類別:期刊論文


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