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The power of coarse graining in biomolecular simulations
Author(s) -
Ingólfsson Helgi I.,
Lopez Cesar A.,
Uusitalo Jaakko J.,
de Jong Djurre H.,
Gopal Srinivasa M.,
Periole Xavier,
Marrink Siewert J.
Publication year - 2013
Publication title -
wiley interdisciplinary reviews: computational molecular science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.126
H-Index - 81
eISSN - 1759-0884
pISSN - 1759-0876
DOI - 10.1002/wcms.1169
Subject(s) - granularity , monte carlo method , molecular dynamics , folding (dsp implementation) , statistical physics , computer science , biological system , nanotechnology , physics , chemistry , materials science , computational chemistry , biology , mathematics , engineering , statistics , electrical engineering , operating system
Computational modeling of biological systems is challenging because of the multitude of spatial and temporal scales involved. Replacing atomistic detail with lower resolution, coarse grained ( CG ), beads has opened the way to simulate large‐scale biomolecular processes on time scales inaccessible to all‐atom models. We provide an overview of some of the more popular CG models used in biomolecular applications to date, focusing on models that retain chemical specificity. A few state‐of‐the‐art examples of protein folding, membrane protein gating and self‐assembly, DNA hybridization, and modeling of carbohydrate fibers are used to illustrate the power and diversity of current CG modeling. This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods