Bridging between NMA and Elastic Network Models: Preserving All-Atom Accuracy in Coarse-Grained Models

Hyuntae Na, Robert L. Jernigan, Guang Song

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

Dynamics can provide deep insights into the functional mechanisms of proteins and protein complexes. For large protein complexes such as GroEL/GroES with more than 8,000 residues, obtaining a fine-grained all-atom description of its normal mode motions can be computationally prohibitive and is often unnecessary. For this reason, coarse-grained models have been used successfully. However, most existing coarse-grained models use extremely simple potentials to represent the interactions within the coarse-grained structures and as a result, the dynamics obtained for the coarse-grained structures may not always be fully realistic. There is a gap between the quality of the dynamics of the coarse-grained structures given by all-atom models and that by coarse-grained models. In this work, we resolve an important question in protein dynamics computations—how can we efficiently construct coarse-grained models whose description of the dynamics of the coarse-grained structures remains as accurate as that given by all-atom models? Our method takes advantage of the sparseness of the Hessian matrix and achieves a high efficiency with a novel iterative matrix projection approach. The result is highly significant since it can provide descriptions of normal mode motions at an all-atom level of accuracy even for the largest biomolecular complexes. The application of our method to GroEL/GroES offers new insights into the mechanism of this biologically important chaperonin, such as that the conformational transitions of this protein complex in its functional cycle are even more strongly connected to the first few lowest frequency modes than with other coarse-grained models.

Original languageEnglish (US)
Article numbere1004542
JournalPLoS computational biology
Volume11
Issue number10
DOIs
StatePublished - Jan 1 2015

Fingerprint

Network Model
Atoms
Proteins
Protein
protein
Normal Modes
Chaperonins
proteins
Model
chaperonins
Projection Matrix
matrix
Hessian matrix
Motion
application methods
High Efficiency
Low Frequency
Resolve
Cycle
Interaction

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Ecology
  • Molecular Biology
  • Genetics
  • Cellular and Molecular Neuroscience
  • Computational Theory and Mathematics

Cite this

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Bridging between NMA and Elastic Network Models : Preserving All-Atom Accuracy in Coarse-Grained Models. / Na, Hyuntae; Jernigan, Robert L.; Song, Guang.

In: PLoS computational biology, Vol. 11, No. 10, e1004542, 01.01.2015.

Research output: Contribution to journalArticle

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