Journal
BIOCHIMICA ET BIOPHYSICA ACTA-BIOMEMBRANES
Volume 1858, Issue 7, Pages 1635-1651Publisher
ELSEVIER
DOI: 10.1016/j.bbamem.2015.12.032
Keywords
Generalized Born (GB) model; Generalized-ensemble algorithm; Replica-exchange molecular dynamics (REMD); Replica-exchange umbrella sampling (REUS); Surface-tension REMD; Replica exchange with solute tempering (REST)
Categories
Funding
- High Performance Computing Infrastructure (HPCI) Strategic Program of the Ministry of Education, Culture, Sports, Science and Technology (MEXT)
- MEXT/JSPS KAKENHI [15H05594]
- NSF [MCB-1157677, MCB 1330560, CBET 0941055]
- NIH [GM092950, U54GM087519, GM092949, GM084953]
- HPCI System Research project [ra000009, hp120060, hp120309, hp130003, hp140091, hp140169, hp140229, hp150060]
- [26119006]
- Grants-in-Aid for Scientific Research [26330341, 15H05594, 26119006] Funding Source: KAKEN
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This paper reviews various enhanced conformational sampling methods and explicit/implicit solvent/membrane models, as well as their recent applications to the exploration of the structure and dynamics of membranes and membrane proteins. Molecular dynamics simulations have become an essential tool to investigate biological problems, and their success relies on proper molecular models together with efficient conformational sampling methods. The implicit representation of solvent/membrane environments is reasonable approximation to the explicit all-atom models, considering the balance between computational cost and simulation accuracy. Implicit models can be easily combined with replica-exchange molecular dynamics methods to explore a wider conformational space of a protein. Other molecular models and enhanced conformational sampling methods are also briefly discussed. As application examples, we introduce recent simulation studies of glycophorin A, phospholamban, amyloid precursor protein, and mixed lipid bilayers and discuss the accuracy and efficiency of each simulation model and method. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov. (C) 2016 The Authors. Published by Elsevier B.V.
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