The power of coarse graining in biomolecular simulations

Helgi I. Ingólfsson, César A. López, Jaakko J. Uusitalo, Djurre H. de Jong, Srinivasa M. Gopal, Xavier Périole, ‪Siewert J. Marrink

Wiley Interdisciplinary Reviews Computational Molecular Science · 2013 · 588 citations · 152 references

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TL;DR

Computational modeling of biological systems is challenged by multiple spatial and temporal scales, but coarse‑grained beads enable simulation of large‑scale biomolecular processes beyond all‑atom reach. The paper reviews popular coarse‑grained models in biomolecular applications that retain chemical specificity. The authors survey chemically specific coarse‑grained models applied to biomolecular systems. Examples of protein folding, membrane protein gating, self‑assembly, DNA hybridization, and carbohydrate fiber modeling illustrate the power and diversity of current coarse‑grained approaches. Article categorized under Molecular and Statistical Mechanics > Molecular Dynamics and Monte‑Carlo Methods.

Abstract

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

References

152