Evidence map›Paper›PMID 23663843›Full record

ArticleBiophysical journal2013

Mapping conformational dynamics of proteins using torsional dynamics simulations.

Vamshi K Gangupomu, Jeffrey R Wagner, In-Hee Park, Abhinandan Jain, Nagarajan Vaidehi

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In one paragraph

Article in Biophysical journal, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Vamshi K GangupomuDivision of Immunology, Beckman Research Institute of the City of Hope, Duarte, California, USA.
Jeffrey R Wagner
In-Hee Park
Abhinandan Jain
Nagarajan Vaidehi

Funding

GNEIMO: Generalized Internal Coordinate Molecular Dynamics MethodsR01GM082896 · NIGMS · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI VAIDEHI, NAGARAJAN · 2008 to 2011
$1.2M
NIGMS NIH HHS R01 GM082896NIGMS NIH HHS R01-GM082896
6 · The paper itself

Abstract

All-atom molecular dynamics simulations are widely used to study the flexibility of protein conformations. However, enhanced sampling techniques are required for simulating protein dynamics that occur on the millisecond timescale. In this work, we show that torsional molecular dynamics simulations enhance protein conformational sampling by performing conformational search in the low-frequency torsional degrees of freedom. In this article, we use our recently developed torsional-dynamics method called Generalized Newton-Euler Inverse Mass Operator (GNEIMO) to study the conformational dynamics of four proteins. We investigate the use of the GNEIMO method in simulations of the conformationally flexible proteins fasciculin and calmodulin, as well as the less flexible crambin and bovine pancreatic trypsin inhibitor. For the latter two proteins, the GNEIMO simulations with an implicit-solvent model reproduced the average protein structural fluctuations and sample conformations similar to those from Cartesian simulations with explicit solvent. The application of GNEIMO with replica exchange to the study of fasciculin conformational dynamics produced sampling of two of this protein's experimentally established conformational substates. Conformational transition of calmodulin from the Ca(2+)-bound to the Ca(2+)-free conformation occurred readily with GNEIMO simulations. Moreover, the GNEIMO method generated an ensemble of conformations that satisfy about half of both short- and long-range interresidue distances obtained from NMR structures of holo to apo transitions in calmodulin. Although unconstrained all-atom Cartesian simulations have failed to sample transitions between the substates of fasciculin and calmodulin, GNEIMO simulations show the transitions in both systems. The relatively short simulation times required to capture these long-timescale conformational dynamics indicate that GNEIMO is a promising molecular-dynamics technique for studying domain motion in proteins.

Indexed as

Molecular Dynamics SimulationProtein ConformationSoftwareAmino Acid SequenceAnimalsAprotininCalmodulinElapid VenomsMolecular Sequence DataPlant ProteinsTorsion, MechanicalAprotininCalmodulincrambin protein, Crambe abyssinicaElapid VenomsfasciculinPlant Proteins

Identifiers

PMID23663843
PMCPMC3647154

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.