Evidence map›Paper›PMID 41378882›Full record

ArticleBriefings in bioinformatics2025

Impact of intrinsically disordered regions and functional disorder hotspots in the human kinome.

Sonet Daniel Thomas, Aparna Rajan, Althaf Mahin, Mukthar Ahmed, S Pavithra, U Vignesh, Naveen Joy, Levin John, Lijin Varghese, Alimath Sambreena and 7 more

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 2025. 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

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

2 citing papers in PubMed.

  1. Article
  2. 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

17 authors.

Sonet Daniel ThomasCentre for Integrative Omics Data Science (CIODS), Centre for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Deralakatte, Manglore 575018, Karnataka, India.
Aparna RajanCentre for Integrative Omics Data Science (CIODS), Centre for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Deralakatte, Manglore 575018, Karnataka, India.
Althaf MahinCentre for Integrative Omics Data Science (CIODS), Centre for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Deralakatte, Manglore 575018, Karnataka, India.
Mukthar AhmedDepartment of Zoology, College of Science, King Saud University, P. O. Box 2455, Riyadh Province, Riyadh 11451, Kingdom of Saudi Arabia.
S PavithraSchool of Computer Science and Engineering, Vellore Institute of Technology, Chennai 600127, Tamil Nadu, India.
U VigneshSchool of Computer Science and Engineering, Vellore Institute of Technology, Chennai 600127, Tamil Nadu, India.
Naveen JoyCentre for Integrative Omics Data Science (CIODS), Centre for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Deralakatte, Manglore 575018, Karnataka, India.
Levin JohnCentre for Integrative Omics Data Science (CIODS), Centre for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Deralakatte, Manglore 575018, Karnataka, India.
Lijin VargheseCentre for Integrative Omics Data Science (CIODS), Centre for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Deralakatte, Manglore 575018, Karnataka, India.
Alimath SambreenaCentre for Integrative Omics Data Science (CIODS), Centre for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Deralakatte, Manglore 575018, Karnataka, India.
Jalaluddin Akbar Kandel CodiCentre for Integrative Omics Data Science (CIODS), Centre for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Deralakatte, Manglore 575018, Karnataka, India.
Thottethodi Subrahmanya Keshava PrasadCentre for Integrative Omics Data Science (CIODS), Centre for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Deralakatte, Manglore 575018, Karnataka, India.
Manavalan VijayakumarCentre for Integrative Omics Data Science (CIODS), Centre for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Deralakatte, Manglore 575018, Karnataka, India.
S GeethaSchool of Computer Science and Engineering, Vellore Institute of Technology, Chennai 600127, Tamil Nadu, India.
R ParvathiSchool of Computer Science and Engineering, Vellore Institute of Technology, Chennai 600127, Tamil Nadu, India.
R GanesanSchool of Computer Science and Engineering, Vellore Institute of Technology, Chennai 600127, Tamil Nadu, India.
Rajesh RajuCentre for Integrative Omics Data Science (CIODS), Centre for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Deralakatte, Manglore 575018, Karnataka, India.ORCID 0000-0003-2319-121X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A ubiquitous and reversible phosphorylation is important for molecular signaling cascades, regulated by the transient interaction of protein kinases. The coupled folding and phosphorylation determining substrate specificity re-calibrates the interactive environment of intrinsically disordered regions (IDRs). There are over 50 computational methods for predicting IDRs in the proteome, yet achieving an accurate depiction remains an ongoing challenge. In this study, we present a standardized and kinase-centric approach for IDR prediction within the human kinome, employing a long short-term memory deep learning framework that achieves a high predictive performance (AUC = 0.97). The web server is now publicly accessible at: https://ciods.in/kindisorder. Our workflow begins with proteome-wide IDR prediction and proceeds with the categorization of short and long IDR segments, followed by an in-depth analysis of their distribution relative to the kinase domain regulatory core. We evaluated the conservation of these IDRs across all 137 human kinase families, computing a trend-setting conservation index to identify both conserved and variable disorder patterns. Through this framework, we uncovered 1039 functional disorder region hotspots that correlate with dynamic conformational shifts, phosphorylation sites, functional motif enrichment, and mutation impact embedded within IDRs. To further validate their regulatory significance, we conducted biophysical profiling of conserved and variable IDRs. Finally, we developed a structural integrity framework to link these IDRs to their influence on intrinsic signaling cascades and substrate specificity. This study offers a comprehensive functional characterization of IDRs in the human kinome, providing a valuable resource for exploring kinase regulation and opportunities in drug repurposing.

Indexed as

Intrinsically Disordered ProteinsProtein KinasesProteomeComputational BiologyDeep LearningHumansPhosphorylationIntrinsically Disordered ProteinsProtein KinasesProteomefunctional disorder hotspotshuman kinomeIDR conformation maplong short-term memory

Identifiers

PMID41378882
PMCPMC12696717

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

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.