Evidence map›Paper›PMID 24089724›Full record

ArticleThe Journal of chemical physics2013

Global motions exhibited by proteins in micro- to milliseconds simulations concur with anisotropic network model predictions.

M Gur, E Zomot, I Bahar

Abstract read
In one paragraph

Article in The Journal of chemical physics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

40 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Structural basis ofScience advances · 2025
    Article
  7. Engineering Protein Dynamics through Mutational Energy Landscape Traps.Journal of chemical information and modeling · 2025
    Article
  8. Article
  9. Article
  10. The mechanism and energetics of the dynein priming stroke.Structure (London, England : 1993) · 2024
    Article
  11. Article
  12. Article
  13. Protein dynamics developments for the large scale and cryoEM: case study of ProDy 2.0.Acta crystallographica. Section D, Structural biology · 2022
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Spectral analysis of molecular dynamics simulations on PDZ: MD sectors.Journal of biomolecular structure & dynamics · 2020
    Article
  19. Article
  20. Review
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

3 authors.

M GurDepartment of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, Pennsylvania 15260, USA.
E Zomot
I Bahar

Funding

TrainingP41GM103712 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI FAEDER, JAMES · 2012 to 2021
$16.3M
Structural Dynamics of Biomolecular SystemsR01GM086238 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BAHAR, IVET · 2009 to 2012
$1.3M
NIGMS NIH HHS P41 GM103712NIGMS NIH HHS P41 GM103712-01NIGMS NIH HHS R01 GM086238NIGMS NIH HHS R01GM086238NIGMS NIH HHS RC2GM09337
6 · The paper itself

Abstract

The Anton supercomputing technology recently developed for efficient molecular dynamics simulations permits us to examine micro- to milli-second events at full atomic resolution for proteins in explicit water and lipid bilayer. It also permits us to investigate to what extent the collective motions predicted by network models (that have found broad use in molecular biophysics) agree with those exhibited by full-atomic long simulations. The present study focuses on Anton trajectories generated for two systems: the bovine pancreatic trypsin inhibitor, and an archaeal aspartate transporter, GltPh. The former, a thoroughly studied system, helps benchmark the method of comparative analysis, and the latter provides new insights into the mechanism of function of glutamate transporters. The principal modes of motion derived from both simulations closely overlap with those predicted for each system by the anisotropic network model (ANM). Notably, the ANM modes define the collective mechanisms, or the pathways on conformational energy landscape, that underlie the passage between the crystal structure and substates visited in simulations. In particular, the lowest frequency ANM modes facilitate the conversion between the most probable substates, lending support to the view that easy access to functional substates is a robust determinant of evolutionarily selected native contact topology.

Indexed as

AlgorithmsModels, ChemicalMolecular Dynamics SimulationAmino Acid Transport SystemsAnimalsAnisotropyAprotininAspartic AcidCattleKineticsLipid BilayersModels, MolecularPrincipal Component AnalysisTime FactorsWaterAmino Acid Transport SystemsAprotininAspartic AcidLipid BilayersWater

Identifiers

PMID24089724
PMCPMC3739829

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.