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Constructing effective energy functions for protein structure prediction through broadening attraction-basin and reverse Monte Carlo sampling
Wang, Chao1,2; Wei, Yi1,2; Zhang, Haicang1,2; Kong, Lupeng1,2; Sun, Shiwei1,2; Zheng, Wei-Mou2,3; Bu, Dongbo1,2
2019-03-29
发表期刊BMC BIOINFORMATICS
ISSN1471-2105
卷号20页码:10
摘要BackgroundThe ab initio approaches to protein structure prediction usually employ the Monte Carlo technique to search the structural conformation that has the lowest energy. However, the widely-used energy functions are usually ineffective for conformation search. How to construct an effective energy function remains a challenging task.ResultsHere, we present a framework to construct effective energy functions for protein structure prediction. Unlike existing energy functions only requiring the native structure to be the lowest one, we attempt to maximize the attraction-basin where the native structure lies in the energy landscape. The underlying rationale is that each energy function determines a specific energy landscape together with a native attraction-basin, and the larger the attraction-basin is, the more likely for the Monte Carlo search procedure to find the native structure. Following this rationale, we constructed effective energy functions as follows: i) To explore the native attraction-basin determined by a certain energy function, we performed reverse Monte Carlo sampling starting from the native structure, identifying the structural conformations on the edge of attraction-basin. ii) To broaden the native attraction-basin, we smoothened the edge points of attraction-basin through tuning weights of energy terms, thus acquiring an improved energy function. Our framework alternates the broadening attraction-basin and reverse sampling steps (thus called BARS) until the native attraction-basin is sufficiently large. We present extensive experimental results to show that using the BARS framework, the constructed energy functions could greatly facilitate protein structure prediction in improving the quality of predicted structures and speeding up conformation search.ConclusionUsing the BARS framework, we constructed effective energy functions for protein structure prediction, which could improve the quality of predicted structures and speed up conformation search as well.
关键词Protein structure prediction Energy function Attraction-basin Reverse Monte Carlo sampling Monte Carlo search Linear program
DOI10.1186/s12859-019-2652-5
收录类别SCI
语种英语
资助项目National Key Research and Development Program of China[2018YFC0910405] ; National Natural Science Foundation of China[31671369] ; National Natural Science Foundation of China[31770775]
WOS研究方向Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology
WOS类目Biochemical Research Methods ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology
WOS记录号WOS:000462857100009
出版者BMC
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被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://119.78.100.204/handle/2XEOYT63/4142
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Zheng, Wei-Mou; Bu, Dongbo
作者单位1.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, 6 Kexueyuan South Rd, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, 19-1 Yuquan Rd, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Inst Theoret Phys, 55 Zhongguancun East Rd, Beijing 100190, Peoples R China
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Wang, Chao,Wei, Yi,Zhang, Haicang,et al. Constructing effective energy functions for protein structure prediction through broadening attraction-basin and reverse Monte Carlo sampling[J]. BMC BIOINFORMATICS,2019,20:10.
APA Wang, Chao.,Wei, Yi.,Zhang, Haicang.,Kong, Lupeng.,Sun, Shiwei.,...&Bu, Dongbo.(2019).Constructing effective energy functions for protein structure prediction through broadening attraction-basin and reverse Monte Carlo sampling.BMC BIOINFORMATICS,20,10.
MLA Wang, Chao,et al."Constructing effective energy functions for protein structure prediction through broadening attraction-basin and reverse Monte Carlo sampling".BMC BIOINFORMATICS 20(2019):10.
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