Wavelet transformed Gaussian network model
文献类型:期刊论文
作者 | Zhan, Meng1; Li, Suhong1,2; Li, Fan1,2 |
刊名 | JOURNAL OF THEORETICAL & COMPUTATIONAL CHEMISTRY
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出版日期 | 2014-09-01 |
卷号 | 13期号:6 |
关键词 | Protein modeling Gaussian network model wavelet transform B-factors correlation coefficient |
英文摘要 | Accurate prediction of the Debye-Waller temperature factor of proteins is of significant importance in the study of protein dynamics and function. This work explores the utility of wavelets for improving the performance of Gaussian network model (GNM). We propose two wavelet transformed Gaussian network models (wtGNM), namely a scale-one wtGNM and a scale-two wtGNM. Based on a set of 113 protein structures, it shows that the mean correlation with experimental results for the scale-one wtGNM is 0.714 and that for the scale-two wtGNM is 0.738. In contrast, the mean correlation for the original GNM is 0.594. Therefore, the wtGNM is a potential algorithm for improving the GNM prediction of protein B-factors. |
WOS标题词 | Science & Technology ; Physical Sciences |
类目[WOS] | Chemistry, Multidisciplinary |
研究领域[WOS] | Chemistry |
关键词[WOS] | MOLECULAR-DYNAMICS SIMULATIONS ; PROTEIN DYNAMICS ; FLUCTUATION DYNAMICS ; TRYPSIN-INHIBITOR ; SINGLE-PARAMETER ; COMMUNICATION ; LYSOZYME ; MOTIONS |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000343992800008 |
公开日期 | 2015-07-14 |
源URL | [http://ir.wipm.ac.cn/handle/112942/1332] ![]() |
专题 | 武汉物理与数学研究所_理论与交叉研究部 |
作者单位 | 1.Chinese Acad Sci, Wuhan Ctr Magnet Resonance, Wuhan Inst Phys & Math, State Key Lab Magnet Resonance & Atom & Mol Phys, Wuhan 430071, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
推荐引用方式 GB/T 7714 | Zhan, Meng,Li, Suhong,Li, Fan. Wavelet transformed Gaussian network model[J]. JOURNAL OF THEORETICAL & COMPUTATIONAL CHEMISTRY,2014,13(6). |
APA | Zhan, Meng,Li, Suhong,&Li, Fan.(2014).Wavelet transformed Gaussian network model.JOURNAL OF THEORETICAL & COMPUTATIONAL CHEMISTRY,13(6). |
MLA | Zhan, Meng,et al."Wavelet transformed Gaussian network model".JOURNAL OF THEORETICAL & COMPUTATIONAL CHEMISTRY 13.6(2014). |
入库方式: OAI收割
来源:武汉物理与数学研究所
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