Evidence map›Paper›PMID 31937869›Full record

ArticleScientific reports2020

Domain-mediated interactions for protein subfamily identification.

Heetak Lee, Inhae Kim, Seong Kyu Han, Donghyo Kim, Jungho Kong, Sanguk Kim

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Heetak LeeDepartment of Life Sciences, Pohang University of Science and Technology, Pohang, 790-784, Korea.ORCID http://orcid.org/0000-0002-7093-842X
Inhae KimDepartment of Life Sciences, Pohang University of Science and Technology, Pohang, 790-784, Korea.
Seong Kyu HanDepartment of Life Sciences, Pohang University of Science and Technology, Pohang, 790-784, Korea.
Donghyo KimDepartment of Life Sciences, Pohang University of Science and Technology, Pohang, 790-784, Korea.
Jungho KongDepartment of Life Sciences, Pohang University of Science and Technology, Pohang, 790-784, Korea.
Sanguk KimDepartment of Life Sciences, Pohang University of Science and Technology, Pohang, 790-784, Korea. sukim@postech.ac.kr.ORCID http://orcid.org/0000-0002-3449-3814

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Within a protein family, proteins with the same domain often exhibit different cellular functions, despite the shared evolutionary history and molecular function of the domain. We hypothesized that domain-mediated interactions (DMIs) may categorize a protein family into subfamilies because the diversified functions of a single domain often depend on interacting partners of domains. Here we systematically identified DMI subfamilies, in which proteins share domains with DMI partners, as well as with various functional and physical interaction networks in individual species. In humans, DMI subfamily members are associated with similar diseases, including cancers, and are frequently co-associated with the same diseases. DMI information relates to the functional and evolutionary subdivisions of human kinases. In yeast, DMI subfamilies contain proteins with similar phenotypic outcomes from specific chemical treatments. Therefore, the systematic investigation here provides insights into the diverse functions of subfamilies derived from a protein family with a link-centric approach and suggests a useful resource for annotating the functions and phenotypic outcomes of proteins.

Indexed as

Databases, ProteinEvolution, MolecularHumansMultigene FamilyNeoplasmsPhenotypeProtein DomainsProtein Interaction MapsProtein KinasesProteinsProtein KinasesProteins

Identifiers

PMID31937869
PMCPMC6959277

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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.