Evidence map›Paper›PMID 20626880›Full record

ArticleBMC structural biology2010

Prediction of protein motions from amino acid sequence and its application to protein-protein interaction.

Shuichi Hirose, Kiyonobu Yokota, Yutaka Kuroda, Hiroshi Wako, Shigeru Endo, Satoru Kanai, Tamotsu Noguchi

Open access · hybridAbstract read
In one paragraph

Article in BMC structural biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

7 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Protein flexibility in the light of structural alphabets.Frontiers in molecular biosciences · 2015
    Review
  5. Sequence-based Gaussian network model for protein dynamics.Bioinformatics (Oxford, England) · 2014
    Article
  6. Article
  7. 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

7 authors at 4 institutions in 1 country.

Shuichi HiroseComputational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST),2-42, Aomi, Koto-ku, Tokyo, 135-0064, Japan. hirose-shuichi@aist.go.jp
Kiyonobu Yokota
Yutaka Kuroda
Hiroshi Wako
Shigeru Endo
Satoru Kanai
Tamotsu Noguchi
National Institute of Advanced Industrial Science and Technology · JPWaseda University · JPKitasato University · JPTokyo University of Agriculture and Technology · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStructural flexibility is an important characteristic of proteins because it is often associated with their function. The movement of a polypeptide segment in a protein can be broken down into two types of motions: internal and external ones. The former is deformation of the segment itself, but the latter involves only rotational and translational motions as a rigid body. Normal Model Analysis (NMA) can derive these two motions, but its application remains limited because it necessitates the gathering of complete structural information.

resultsIn this work, we present a novel method for predicting two kinds of protein motions in ordered structures. The prediction uses only information from the amino acid sequence. We prepared a dataset of the internal and external motions of segments in many proteins by application of NMA. Subsequently, we analyzed the relation between thermal motion assessed from X-ray crystallographic B-factor and internal/external motions calculated by NMA. Results show that attributes of amino acids related to the internal motion have different features from those related to the B-factors, although those related to the external motion are correlated strongly with the B-factors. Next, we developed a method to predict internal and external motions from amino acid sequences based on the Random Forest algorithm. The proposed method uses information associated with adjacent amino acid residues and secondary structures predicted from the amino acid sequence. The proposed method exhibited moderate correlation between predicted internal and external motions with those calculated by NMA. It has the highest prediction accuracy compared to a naïve model and three published predictors.

conclusionsFinally, we applied the proposed method predicting the internal motion to a set of 20 proteins that undergo large conformational change upon protein-protein interaction. Results show significant overlaps between the predicted high internal motion regions and the observed conformational change regions.

Indexed as

Computational BiologyMovementAlgorithmsAmino Acid SequenceHumansModels, MolecularProtein BindingProteinsProtein Structure, SecondaryTemperatureProteins

Identifiers

PMID20626880
PMCPMC3245509
OpenAlexW1979985164

What OpenQuestion holds

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LicenceCC BY
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.