Evidence map›Paper›PMID 35525549›Full record

ReviewMethods in enzymology2022

Computational tools and resources for pseudokinase research.

Brady O'Boyle, Safal Shrestha, Krzysztof Kochut, Patrick A Eyers, Natarajan Kannan

Abstract readReview
In one paragraph

Review in Methods in enzymology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. 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

5 authors.

Brady O'BoyleDepartment of Biochemistry & Molecular Biology, University of Georgia, Athens, GA, United States.
Safal ShresthaInstitute of Bioinformatics, University of Georgia, Athens, GA, United States.
Krzysztof KochutDepartment of Computer Science, University of Georgia, Athens, GA, United States.
Patrick A EyersDepartment of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom.
Natarajan KannanDepartment of Biochemistry & Molecular Biology, University of Georgia, Athens, GA, United States; Institute of Bioinformatics, University of Georgia, Athens, GA, United States. Electronic address: nkannan@uga.edu.

Funding

Unlocking sequence-structure-function-disease relationships in large protein super-familiesR35GM139656 · NIGMS · UNIVERSITY OF GEORGIA · PI KANNAN, NATARAJAN · 2021 to 2025
$2.2M
A data analytics framework for mining the dark kinomeU01CA239106 · NCI · UNIVERSITY OF GEORGIA · PI KANNAN, NATARAJAN, KOCHUT, KRZYSZTOF J · 2019 to 2021
$1.3M
NCI NIH HHS U01 CA239106NIGMS NIH HHS R35 GM139656
6 · The paper itself

Abstract

Pseudokinases regulate diverse cellular processes associated with normal cellular functions and disease. They are defined bioinformatically based on the absence of one or more catalytic residues that are required for canonical protein kinase functions. The ability to define pseudokinases based on primary sequence comparison has enabled the systematic mapping and cataloging of pseudokinase orthologs across the tree of life. While these sequences contain critical information regarding pseudokinase evolution and functional specialization, extracting this information and generating testable hypotheses based on integrative mining of sequence and structural data requires specialized computational tools and resources. In this chapter, we review recent advances in the development and application of open-source tools and resources for pseudokinase research. Specifically, we describe the application of an interactive data analytics framework, KinView, for visualizing the patterns of conservation and variation in the catalytic domain motifs of pseudokinases and evolutionarily related canonical kinases using a consistent set of curated alignments organized based on the widely used kinome evolutionary hierarchy. We also demonstrate the application of an integrated Protein Kinase Ontology (ProKinO) and an interactive viewer, ProtVista, for mapping and analyzing primary sequence motifs and annotations in the context of 3D structures and AlphaFold2 models. We provide examples and protocols for generating testable hypotheses on pseudokinase functions both for bench biologists and advanced users.

Indexed as

Protein KinasesCatalytic DomainProtein KinasesComputational biologyEvolutionary constraintsFunctionProtein structurePseudoenzymesRegulationWebserver

Identifiers

PMID35525549
PMCPMC9733567

What Socratic holds

Textmetadata
LicenceTDM
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.