AI Article Synopsis
- - Elastic networks are simplified models of proteins made up of point particles linked by springs, which help researchers analyze protein dynamics more easily.
- - These models are less computationally intensive than all-atom models, making them ideal for comparing different protein structures and conducting dynamic simulations.
- - The review highlights examples of studies using elastic network models, exploring nonlinear behaviors and their relevance to large macromolecular assemblies.
Article Abstract
Elastic networks have been used as simple models of proteins to study their slow structural dynamics. They consist of point-like particles connected by linear Hookean springs and hence are convenient for linear normal mode analysis around a given reference structure. Furthermore, dynamic simulations using these models can provide new insights. As the computational cost associated with these models is considerably lower compared to that of all-atom models, they are also convenient for comparative studies between multiple protein structures. In this review, we introduce examples of coarse-grained molecular dynamics studies using elastic network models and their derivatives, focusing on the nonlinear phenomena, and discuss their applicability to large-scale macromolecular assemblies.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6320916 | PMC |
| http://dx.doi.org/10.3390/ijms19123899 | DOI Listing |
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