Evidence map›Paper›PMID 39534081›Full record

ArticleFrontiers in genetics2024

Number of human protein interactions correlates with structural, but not regulatory conservation of the respective genes.

Rijalda Mekic, Marianna A Zolotovskaia, Maksim Sorokin, Tharaa Mohammad, Nina Shaban, Ivan Musatov, Victor Tkachev, Alexander Modestov, Alexander Simonov, Denis Kuzmin and 1 more

Abstract read
In one paragraph

Article in Frontiers in genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

11 authors.

Rijalda MekicLaboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.
Marianna A ZolotovskaiaLaboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.
Maksim SorokinLaboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.
Tharaa MohammadLaboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.
Nina ShabanLaboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.
Ivan MusatovLaboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.
Victor TkachevOncobox Ltd., Moscow, Russia.
Alexander ModestovLaboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.
Alexander SimonovLaboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.
Denis KuzminLaboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.
Anton BuzdinLaboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The differential ratio of nonsynonymous to synonymous nucleotide substitutions (dN/dS) is a common measure of the rate of structural evolution in proteincoding genes. In addition, we recently suggested that the proportion of transposable elements in gene promoters that host functional genomic sites serves as a marker of the rate of regulatory evolution of genes. Such functional genomic regions may include transcription factor binding sites and modified histone binding loci. Methods: Here, we constructed a model of the human interactome based on 600,136 documented molecular interactions and investigated the overall relationship between the number of interactions of each protein and the rate of structural and regulatory evolution of the corresponding genes. Results: By evaluating a total of 4,505 human genes and 1,936 molecular pathways we found a general correlation between structural and regulatory evolution rate metrics (Spearman 0.08-0.16 and 0.25-0.37 for gene and pathway levels, respectively, Discussion: Our result suggests stronger structural rather than regulatory conservation of genes whose protein products have multiple interaction partners.

Indexed as

human gene regulationhuman interactome modelmolecular evolutionmolecular pathwaysoncoboxpd databaseregulatory evolution rateretrospectstructural evolution rate

Identifiers

PMID39534081
PMCPMC11554504

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.