Evidence map›Paper›PMID 27006112›Full record

ArticleScientific reports2016

Impact of structure space continuity on protein fold classification.

Jinrui Xu, Jianzhi Zhang

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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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

2 citing papers in PubMed.

  1. Review
  2. The Urfold: Structural similarity just above the superfold level?Protein science : a publication of the Protein Society · 2019
    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

2 authors.

Jinrui XuDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Jianzhi ZhangDepartment of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA.

Funding

Pleiotropy: patterns, mechanisms, and evolutionary consequencesR01GM103232 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZHANG, JIANZHI · 2013 to 2020
$1.8M
NIGMS NIH HHS R01 GM103232NIGMS NIH HHS R01GM103232
6 · The paper itself

Abstract

Protein structure classification hierarchically clusters domain structures based on structure and/or sequence similarities and plays important roles in the study of protein structure-function relationship and protein evolution. Among many classifications, SCOP and CATH are widely viewed as the gold standards. Fold classification is of special interest because this is the lowest level of classification that does not depend on protein sequence similarity. The current fold classifications such as those in SCOP and CATH are controversial because they implicitly assume that folds are discrete islands in the structure space, whereas increasing evidence suggests significant similarities among folds and supports a continuous fold space. Although this problem is widely recognized, its impact on fold classification has not been quantitatively evaluated. Here we develop a likelihood method to classify a domain into the existing folds of CATH or SCOP using both query-fold structure similarities and within-fold structure heterogeneities. The new classification differs from the original classification for 3.4-12% of domains, depending on factors such as the structure similarity score and original classification scheme used. Because these factors differ for different biological purposes, our results indicate that the importance of considering structure space continuity in fold classification depends on the specific question asked.

Indexed as

Protein FoldingAlgorithmsLikelihood FunctionsModels, MolecularProtein ConformationProteinsProteins

Identifiers

PMID27006112
PMCPMC4804218

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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.