Evidence map›Paper›PMID 26388442›Full record

ArticleCell2015

Unmasking determinants of specificity in the human kinome.

Pau Creixell, Antonio Palmeri, Chad J Miller, Hua Jane Lou, Cristina C Santini, Morten Nielsen, Benjamin E Turk, Rune Linding

Open access · hybridAbstract read
In one paragraph

Article in Cell, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
8.6field-weighted citation impact, top 2% 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

40 citing papers in PubMed, 89 citations in OpenAlex.

  1. A Constellation of Fluorescent Biosensors to Illuminate the Galaxy of Protein Kinases.Chembiochem : a European journal of chemical biology · 2026
    Review
  2. The pathogenic T42A mutation in SHP2 rewires the interaction specificity of its N-terminal regulatory domain.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
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  10. Mass Spectrometry-Based Discovery ofMass spectrometry (Tokyo, Japan) · 2020
    Article
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  15. Review
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  18. Classifying tumors by supervised network propagation.Bioinformatics (Oxford, England) · 2018
    Article
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  20. Review
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

8 authors at 4 institutions in 3 countries.

Pau CreixellDepartment of Systems Biology, Technical University of Denmark, 2800 Lyngby, Denmark. Electronic address: creixell@mit.edu.
Antonio PalmeriCentre for Molecular Bioinformatics, University of Rome Tor Vergata, 00133 Rome, Italy.
Chad J MillerDepartment of Pharmacology, Yale University School of Medicine, New Haven, CT 06520, USA.
Hua Jane LouDepartment of Pharmacology, Yale University School of Medicine, New Haven, CT 06520, USA.
Cristina C SantiniDepartment of Systems Biology, Technical University of Denmark, 2800 Lyngby, Denmark; Biotech Research & Innovation Centre (BRIC), University of Copenhagen (UCPH), 2200 Copenhagen, Denmark.
Morten NielsenDepartment of Systems Biology, Technical University of Denmark, 2800 Lyngby, Denmark.
Benjamin E TurkDepartment of Pharmacology, Yale University School of Medicine, New Haven, CT 06520, USA.
Rune LindingDepartment of Systems Biology, Technical University of Denmark, 2800 Lyngby, Denmark; Biotech Research & Innovation Centre (BRIC), University of Copenhagen (UCPH), 2200 Copenhagen, Denmark. Electronic address: linding@lindinglab.org.
Yale University · USTechnical University of Denmark · DKUniversity of Copenhagen · DKUniversity of Rome Tor Vergata · IT

Funding

INSTITUTIONAL NATIONAL RESEARCH SERVICE AWARDT32GM007324 · NIGMS · YALE UNIVERSITY · PI BENNETT, ANTON M · 1987 to 2022
$6.2M
Modeling human phosphorylation networks through kinome-wide profilingR01GM104047 · NIGMS · YALE UNIVERSITY · PI TURK, BENJAMIN E, YAFFE, MICHAEL B · 2013 to 2017
$2.4M
NIGMS NIH HHS R01 GM104047NIGMS NIH HHS T32 GM007324
6 · The paper itself

Abstract

Protein kinases control cellular responses to environmental cues by swift and accurate signal processing. Breakdowns in this high-fidelity capability are a driving force in cancer and other diseases. Thus, our limited understanding of which amino acids in the kinase domain encode substrate specificity, the so-called determinants of specificity (DoS), constitutes a major obstacle in cancer signaling. Here, we systematically discover several DoS and experimentally validate three of them, named the αC1, αC3, and APE-7 residues. We demonstrate that DoS form sparse networks of non-conserved residues spanning distant regions. Our results reveal a likely role for inter-residue allostery in specificity and an evolutionary decoupling of kinase activity and specificity, which appear loaded on independent groups of residues. Finally, we uncover similar properties driving SH2 domain specificity and demonstrate how the identification of DoS can be utilized to elucidate a greater understanding of the role of signaling networks in cancer (Creixell et al., 2015 [this issue of Cell]).

Indexed as

Computational BiologyHumansModels, MolecularNeoplasmsProtein Kinasessrc Homology DomainsSubstrate SpecificityProtein Kinases

Identifiers

PMID26388442
PMCPMC4644237
OpenAlexW1852206334

What OpenQuestion holds

Textmetadata
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.