Communication: Capturing protein multiscale thermal fluctuations.

Content Provider	Europe PMC
Author	Opron, Kristopher Xia, Kelin Wei, Guo-Wei
Copyright Year	2015
Abstract	Existing elastic network models are typically parametrized at a given cutoff distance and often fail to properly predict the thermal fluctuation of many macromolecules that involve multiple characteristic length scales. We introduce a multiscale flexibility-rigidity index (mFRI) method to resolve this problem. The proposed mFRI utilizes two or three correlation kernels parametrized at different length scales to capture protein interactions at corresponding scales. It is about 20% more accurate than the Gaussian network model (GNM) in the B-factor prediction of a set of 364 proteins. Additionally, the present method is able to deliver accurate predictions for some large macromolecules on which GNM fails to produce accurate predictions. Finally, for a protein of N residues, mFRI is of linear scaling (O(N)) in computational complexity, in contrast to the order of O(N3) for GNM.
Related Links	https://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC4457655&blobtype=pdf
Page Count	5
ISSN	00219606
Volume Number	142
DOI	10.1063/1.4922045
PubMed Central reference number	PMC4457655
Issue Number	21
PubMed reference number	26049417
Journal	The Journal of Chemical Physics [J Chem Phys]
e-ISSN	10897690
Language	English
Publisher	AIP Publishing LLC
Publisher Date	2015-06-01
Access Restriction	Open
Rights License	0021-9606/2015/142(21)/211101/5/$30.00 Copyright © 2015 AIP Publishing LLC
Content Type	Text
Resource Type	Article
Subject	Physics and Astronomy Medicine Physical and Theoretical Chemistry