Heterogeneous elastic network model improves description of slow motions of proteins in solution

Min Li; John Z.H. Zhang; Fei Xia

doi:10.1016/j.cplett.2014.11.006

Heterogeneous elastic network model improves description of slow motions of proteins in solution

Min Li, John Z.H. Zhang, Fei Xia

Chemistry

Research output: Contribution to journal › Article › peer-review

Abstract

Elastic network models are widely used in the study of function-related slow motions of proteins. To reflect the correct fluctuations of proteins in solution, the heterogeneous interactions in proteins could be considered. In this work, the heterogeneous anisotropic network model (HANM) is applied to study the protein dynamics in solutions. HANM could generate the accurate fluctuations of proteins and predict the important conformational changes related with their biological functions. By comparison of modes of HANM and principal components of NMR structures, it demonstrates that HANM can improve the description of slow motions of proteins in solution.

Original language	English (US)
Pages (from-to)	102-107
Number of pages	6
Journal	Chemical Physics Letters
Volume	618
DOIs	https://doi.org/10.1016/j.cplett.2014.11.006
State	Published - Jan 2 2015

ASJC Scopus subject areas

Physics and Astronomy(all)
Physical and Theoretical Chemistry

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10.1016/j.cplett.2014.11.006

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title = "Heterogeneous elastic network model improves description of slow motions of proteins in solution",

abstract = "Elastic network models are widely used in the study of function-related slow motions of proteins. To reflect the correct fluctuations of proteins in solution, the heterogeneous interactions in proteins could be considered. In this work, the heterogeneous anisotropic network model (HANM) is applied to study the protein dynamics in solutions. HANM could generate the accurate fluctuations of proteins and predict the important conformational changes related with their biological functions. By comparison of modes of HANM and principal components of NMR structures, it demonstrates that HANM can improve the description of slow motions of proteins in solution.",

author = "Min Li and Zhang, {John Z.H.} and Fei Xia",

note = "Funding Information: This work was supported by the National Natural Science Foundation of China (Grants Nos. 21433004 and 21473056 ), Shanghai Natural Science Foundation ( 14ZR1411800 ) and a start-up grant of ECNU (Grant no. 41500-515430-14100/001/136 ). We also thank the supercomputer center of ECNU for providing computer time. Publisher Copyright: {\textcopyright} 2014 Elsevier B.V. All rights reserved.",

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doi = "10.1016/j.cplett.2014.11.006",

language = "English (US)",

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AU - Li, Min

AU - Zhang, John Z.H.

AU - Xia, Fei

N1 - Funding Information: This work was supported by the National Natural Science Foundation of China (Grants Nos. 21433004 and 21473056 ), Shanghai Natural Science Foundation ( 14ZR1411800 ) and a start-up grant of ECNU (Grant no. 41500-515430-14100/001/136 ). We also thank the supercomputer center of ECNU for providing computer time. Publisher Copyright: © 2014 Elsevier B.V. All rights reserved.

PY - 2015/1/2

Y1 - 2015/1/2

N2 - Elastic network models are widely used in the study of function-related slow motions of proteins. To reflect the correct fluctuations of proteins in solution, the heterogeneous interactions in proteins could be considered. In this work, the heterogeneous anisotropic network model (HANM) is applied to study the protein dynamics in solutions. HANM could generate the accurate fluctuations of proteins and predict the important conformational changes related with their biological functions. By comparison of modes of HANM and principal components of NMR structures, it demonstrates that HANM can improve the description of slow motions of proteins in solution.

AB - Elastic network models are widely used in the study of function-related slow motions of proteins. To reflect the correct fluctuations of proteins in solution, the heterogeneous interactions in proteins could be considered. In this work, the heterogeneous anisotropic network model (HANM) is applied to study the protein dynamics in solutions. HANM could generate the accurate fluctuations of proteins and predict the important conformational changes related with their biological functions. By comparison of modes of HANM and principal components of NMR structures, it demonstrates that HANM can improve the description of slow motions of proteins in solution.

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Heterogeneous elastic network model improves description of slow motions of proteins in solution

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