Evidence map›Paper›PMID 20483345›Full record

ArticleBiophysical journal2010

Instantaneous normal modes as an unforced reaction coordinate for protein conformational transitions.

Cheng Peng, Liqing Zhang, Teresa Head-Gordon

Open access · bronzeAbstract read
In one paragraph

Article in Biophysical journal, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.8field-weighted citation impact, top 16% of its field
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

14 citing papers in PubMed, 32 citations in OpenAlex.

  1. Reaction Coordinates Are Optimal Channels of Energy Flow.Annual review of physical chemistry · 2025
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  6. The anisotropic network model web server at 2015 (ANM 2.0).Bioinformatics (Oxford, England) · 2015
    Article
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  11. Biomolecular dynamics: order-disorder transitions and energy landscapes.Reports on progress in physics. Physical Society (Great Britain) · 2012
    Article
  12. Article
  13. Article
  14. Article
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 at 2 institutions in 2 countries.

Cheng PengDepartment of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China. chengpeng@berkeley.edu
Liqing Zhang
Teresa Head-Gordon
Shanghai Jiao Tong University · CNUniversity of California, Berkeley · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a novel sampling approach to explore large protein conformational transitions by determining unique substates from instantaneous normal modes calculated from an elastic network model, and applied to a progression of atomistic molecular dynamics snapshots. This unbiased sampling scheme allows us to direct the path sampling between the conformational end states over simulation timescales that are greatly reduced relative to the known experimental timescales. We use adenylate kinase as a test system to show that instantaneous normal modes can be used to identify substates that drive the structural fluctuations of adenylate kinase from its closed to open conformations, in which we observe 16 complete transitions in 4 mus of simulation time, reducing the timescale over conventional simulation timescales by two orders of magnitude. Analysis shows that the unbiased determination of substates is consistent with known pathways determined experimentally.

Indexed as

Adenylate KinaseAlgorithmsBinding SitesComputer SimulationMolecular ConformationMonte Carlo MethodNuclear Magnetic Resonance, BiomolecularPolymorphism, Single-Stranded ConformationalThermodynamicsTime FactorsAnimalsCrystallography, X-RayDatabases, ProteinKineticsMiceModels, MolecularAdenylate KinaseProteins

Identifiers

PMID20483345
PMCPMC2872262
OpenAlexW2033080474

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.