Evidence map›Paper›PMID 21463592›Full record

ArticleBiophysical journal2011

Models with energy penalty on interresidue rotation address insufficiencies of conventional elastic network models.

Lee-Wei Yang

Abstract read
In one paragraph

Article in Biophysical journal, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Functional Importance of Mobile Ribosomal Proteins.BioMed research international · 2015
    Review
  5. Article
  6. Elastic Network Models are Robust to Variations in Formalism.Journal of chemical theory and computation · 2012
    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

1 author.

Lee-Wei YangInstitute of Bioinformatics and Structural Biology, National Tsing-Hua University, Hsinchu, Taiwan. lwyang@life.nthu.edu.tw

Funding

Structural Dynamics of Biomolecular SystemsR01GM086238 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BAHAR, IVET · 2009 to 2012
$1.3M
NIGMS NIH HHS 1R01GM086238-01NIGMS NIH HHS R01 GM086238
6 · The paper itself

Abstract

In this study, I present a new elastic network model, to our knowledge, that addresses insufficiencies of two conventional models-the Gaussian network model (GNM) and the anisotropic network model (ANM). It has been shown previously that the GNM is not rotation-invariant due to its energy, which penalizes rigid-body rotation (external rotation). As a result, GNM models are found contaminated with rigid-body rotation, especially in the most collective ones. A new model (EPIRM) is proposed to remove such external component in modes. The extracted internal motions result from a potential that penalizes interresidue stretching and rotation in a protein. The new model is shown to pertinently describe crystallographic temperature factors (B-factors) and protein open↔closed transitions. Also, the capability of separating internal and external motions in GNM slow modes permits reexamining important mechanochemical properties in enzyme active sites. The results suggest that catalytic residues stay closer to rigid-body rotation axes than their immediate backbone neighbors. I show that the cumulative density of states for EPIRM and ANM follow different power laws as functions of low-mode frequencies. When using a cutoff distance of 7.5 Å, The cumulative density of states of EPIRM scales faster than that of all-atom normal mode analysis and slower than that of simple lattices.

Indexed as

ElasticityModels, MolecularRotationAmino AcidsAmino Acid SequenceAnisotropyCatalytic DomainMyoglobinNormal DistributionTemperatureThermodynamicsAmino AcidsMyoglobin

Identifiers

PMID21463592
PMCPMC3072623

What OpenQuestion holds

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Registered trials

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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.