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作者:

Gong, Weikang (Gong, Weikang.) | Liu, Yang (Liu, Yang.) | Zhao, Yanpeng (Zhao, Yanpeng.) | Wang, Shihao (Wang, Shihao.) | Han, Zhongjie (Han, Zhongjie.) | Li, Chunhua (Li, Chunhua.) (学者:李春华)

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摘要:

Dynamical properties of proteins play an essential role in their function exertion. The elastic network model (ENM) is an effective and efficient tool in characterizing the intrinsic dynamical properties encoded in biomacromolecule structures. The Gaussian network model (GNM) and anisotropic network model (ANM) are the two often-used ENM models. Here, we introduce an equally weighted multiscale ENM (equally weighted mENM) based on the original mENM (denoted as mENM), in which fitting weights of Kirchhoff/Hessian matrixes in mENM are removed since they neglect the details of pairwise interactions. Then, we perform its comparison with the mENM, traditional ENM, and parameter-free ENM (pfENM) in reproducing dynamical properties for the six representative proteins whose molecular dynamics (MD) trajectories are available in http://mmb.pcb.ub.es/MoDEL/. In the results, for B-factor prediction, mENM performs best, while the equally weighted mENM performs also well, better than the traditional ENM and pfENM models. As to the dynamical cross-correlation map calculation, mENM performs worst, while the results produced from the equally weighted mENM and pfENM models are close to those from MD trajectories with the latter a little better than the former. Furthermore, encouragingly, the equally weighted mANM displays the best performance in capturing the functional motional modes, followed by pfANM and traditional ANM models, while the mANM fails in all the cases. This work is helpful for strengthening the understanding of the elastic network model and provides a valuable guide for researchers to utilize the model to explore protein dynamics. © 2021 American Chemical Society.

关键词:

Molecular dynamics Proteins

作者机构:

  • [ 1 ] [Gong, Weikang]Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Gong, Weikang]Beijing Intl. Sci. and Technol. Coop. Base for Intelligent Physiological Msrmt. and Clin. Transformation, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Liu, Yang]Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Liu, Yang]Beijing Intl. Sci. and Technol. Coop. Base for Intelligent Physiological Msrmt. and Clin. Transformation, Beijing University of Technology, Beijing; 100124, China
  • [ 5 ] [Zhao, Yanpeng]Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing; 100124, China
  • [ 6 ] [Zhao, Yanpeng]Beijing Intl. Sci. and Technol. Coop. Base for Intelligent Physiological Msrmt. and Clin. Transformation, Beijing University of Technology, Beijing; 100124, China
  • [ 7 ] [Wang, Shihao]Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing; 100124, China
  • [ 8 ] [Wang, Shihao]Beijing Intl. Sci. and Technol. Coop. Base for Intelligent Physiological Msrmt. and Clin. Transformation, Beijing University of Technology, Beijing; 100124, China
  • [ 9 ] [Han, Zhongjie]Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing; 100124, China
  • [ 10 ] [Han, Zhongjie]Beijing Intl. Sci. and Technol. Coop. Base for Intelligent Physiological Msrmt. and Clin. Transformation, Beijing University of Technology, Beijing; 100124, China
  • [ 11 ] [Li, Chunhua]Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing; 100124, China
  • [ 12 ] [Li, Chunhua]Beijing Intl. Sci. and Technol. Coop. Base for Intelligent Physiological Msrmt. and Clin. Transformation, Beijing University of Technology, Beijing; 100124, China

通讯作者信息:

  • 李春华

    [li, chunhua]faculty of environmental and life sciences, beijing university of technology, beijing; 100124, china;;[li, chunhua]beijing intl. sci. and technol. coop. base for intelligent physiological msrmt. and clin. transformation, beijing university of technology, beijing; 100124, china

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来源 :

Journal of Chemical Information and Modeling

ISSN: 1549-9596

年份: 2021

期: 2

卷: 61

页码: 921-937

5 . 6 0 0

JCR@2022

ESI学科: CHEMISTRY;

ESI高被引阀值:96

JCR分区:1

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 8

ESI高被引论文在榜: 0 展开所有

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