TY - JOUR
T1 - Relaxation mode analysis for molecular dynamics simulations of proteins
AU - Mitsutake, Ayori
AU - Takano, Hiroshi
N1 - Funding Information:
Funding information This work was supported by JST PRESTO (JPMJPR13LB). This work was also partially supported by a Grant-in-Aid for Scientific Research (C) (No. 24540441) from the Japan Society for the Promotion of Science.
Funding Information:
The authors would like to thank Mr. Toshiki Nagai, Mr. Taku Yamamoto, Mr. Yuta Koizumi, Mr. Satoshi Natori, and Mr. Naoyuki Karasawa at Keio University for fruitful discussions. This article is part of a Special Issue on ‘Biomolecules to Bio-nanomachines - Fumio Arisaka 70th Birthday’ edited by Damien Hall, Junichi Takagi and Haruki Nakamura.
Publisher Copyright:
© 2018, The Author(s).
PY - 2018/4/1
Y1 - 2018/4/1
N2 - Molecular dynamics simulation is a powerful method for investigating the structural stability, dynamics, and function of biopolymers at the atomic level. In recent years, it has become possible to perform simulations on time scales of the order of milliseconds using special hardware. However, it is necessary to derive the important factors contributing to structural change or function from the complicated movements of biopolymers obtained from long simulations. Although some analysis methods for protein systems have been developed using increasing simulation times, many of these methods are static in nature (i.e., no information on time). In recent years, dynamic analysis methods have been developed, such as the Markov state model and relaxation mode analysis (RMA), which was introduced based on spin and homopolymer systems. The RMA method approximately extracts slow relaxation modes and rates from trajectories and decomposes the structural fluctuations into slow relaxation modes, which characterize the slow relaxation dynamics of the system. Recently, this method has been applied to biomolecular systems. In this article, we review RMA and its improved versions for protein systems.
AB - Molecular dynamics simulation is a powerful method for investigating the structural stability, dynamics, and function of biopolymers at the atomic level. In recent years, it has become possible to perform simulations on time scales of the order of milliseconds using special hardware. However, it is necessary to derive the important factors contributing to structural change or function from the complicated movements of biopolymers obtained from long simulations. Although some analysis methods for protein systems have been developed using increasing simulation times, many of these methods are static in nature (i.e., no information on time). In recent years, dynamic analysis methods have been developed, such as the Markov state model and relaxation mode analysis (RMA), which was introduced based on spin and homopolymer systems. The RMA method approximately extracts slow relaxation modes and rates from trajectories and decomposes the structural fluctuations into slow relaxation modes, which characterize the slow relaxation dynamics of the system. Recently, this method has been applied to biomolecular systems. In this article, we review RMA and its improved versions for protein systems.
KW - Analysis
KW - Dynamics
KW - Protein
KW - Simulation
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U2 - 10.1007/s12551-018-0406-7
DO - 10.1007/s12551-018-0406-7
M3 - Review article
AN - SCOPUS:85045508199
SN - 1867-2450
VL - 10
SP - 375
EP - 389
JO - Biophysical Reviews
JF - Biophysical Reviews
IS - 2
ER -