Constructing effective energy functions for protein structure prediction through broadening attraction-basin and reverse Monte Carlo sampling
文献类型：会议论文
| 作者 | Wang, C; Wei, Y; Zhang, HC; Kong, LP; Sun, SW; Zheng, WM ; Bu, DB
|
| 出版日期 | 2019 |
| 会议日期 | JAN 14-16, 2019 |
| 会议地点 | Wuhan, PEOPLES R CHINA |
| 关键词 | TERTIARY STRUCTURES FRAGMENTS |
| 卷号 | 20 |
| DOI | 10.1186/s12859-019-2652-5 |
| 页码 | 135 |
| 英文摘要 | 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. |
| 会议录 | BMC BIOINFORMATICS
 |
| 会议录出版者 | BMC |
| 会议录出版地 | LONDON |
| 语种 | 英语 |
| URL标识 | 查看原文 |
| ISSN号 | 1471-2105 |
| WOS研究方向 | Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology |
| 源URL | [http://ir.itp.ac.cn/handle/311006/23548]  |
| 专题 | SCI会议论文 |
| 作者单位 | 1.Univ Chinese Acad Sci, 19-1 Yuquan Rd, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, 6 Kexueyuan South Rd, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Inst Theoret Phys, 55 Zhongguancun East Rd, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, C,Wei, Y,Zhang, HC,et al. Constructing effective energy functions for protein structure prediction through broadening attraction-basin and reverse Monte Carlo sampling[C]. 见:. Wuhan, PEOPLES R CHINA. JAN 14-16, 2019. |
入库方式： OAI收割
来源：理论物理研究所
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