Evidence map›Paper›PMID 36830646›Full record

ArticleBiomolecules2023

KinFams: De-Novo Classification of Protein Kinases Using CATH Functional Units.

Tolulope Adeyelu, Nicola Bordin, Vaishali P Waman, Marta Sadlej, Ian Sillitoe, Aurelio A Moya-Garcia, Christine A Orengo

Open access · goldAbstract read
In one paragraph

Article in Biomolecules, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 8% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Clustering protein functional families at large scale with hierarchical approaches.Protein science : a publication of the Protein Society · 2024
    Article
  5. TKL family kinases in human apicomplexan pathogens.Molecular and biochemical parasitology · 2024
    Review
  6. 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

7 authors at 3 institutions in 3 countries.

Tolulope AdeyeluInstitute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK.
Nicola BordinInstitute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK.ORCID 0000-0002-6568-9035
Vaishali P WamanInstitute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK.
Marta SadlejInstitute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK.ORCID 0000-0002-7572-3604
Ian SillitoeInstitute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK.
Aurelio A Moya-GarciaDepartamento de Biología Molecular y Bioquímica, Universidad de Málaga, 29071 Málaga, Spain.ORCID 0000-0002-0567-0949
Christine A OrengoInstitute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK.
Institute of Structural and Molecular Biology · GBLouisiana State University · USUniversidad de Málaga · ES

Funding

Biotechnology and Biological Sciences Research Council BB/R014892/1Wellcome TrustWellcome Trust 221327/Z/20/Z
6 · The paper itself

Abstract

Protein kinases are important targets for treating human disorders, and they are the second most targeted families after G-protein coupled receptors. Several resources provide classification of kinases into evolutionary families (based on sequence homology); however, very few systematically classify functional families (FunFams) comprising evolutionary relatives that share similar functional properties. We have developed the FunFam-MARC (Multidomain ARchitecture-based Clustering) protocol, which uses multi-domain architectures of protein kinases and specificity-determining residues for functional family classification. FunFam-MARC predicts 2210 kinase functional families (KinFams), which have increased functional coherence, in terms of EC annotations, compared to the widely used KinBase classification. Our protocol provides a comprehensive classification for kinase sequences from >10,000 organisms. We associate human KinFams with diseases and drugs and identify 28 druggable human KinFams, i.e., enriched in clinically approved drugs. Since relatives in the same druggable KinFam tend to be structurally conserved, including the drug-binding site, these KinFams may be valuable for shortlisting therapeutic targets. Information on the human KinFams and associated 3D structures from AlphaFold2 are provided via our CATH FTP website and Zenodo. This gives the domain structure representative of each KinFam together with information on any drug compounds available. For 32% of the KinFams, we provide information on highly conserved residue sites that may be associated with specificity.

Indexed as

Protein KinasesProteinsDatabases, ProteinHumansSequence Homology, Amino AcidProtein KinasesProteinsfunctional familiesKinBase classificationKinFamsprotein kinases

Identifiers

PMID36830646
PMCPMC9953599
OpenAlexW4319004578

What Socratic 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 Socratic graph.