Evidence map›Paper›PMID 37668974›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Using Linear Motif Database Resources to Identify SH2 Domain Binders.

Hugo Sámano-Sánchez, Toby J Gibson, Lucía B Chemes

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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. 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

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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

3 authors.

Hugo Sámano-SánchezStructural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.ORCID 0000-0003-4744-4787
Toby J GibsonStructural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.ORCID 0000-0003-0657-5166
Lucía B ChemesStructural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany. lchemes@iib.unsam.edu.ar.ORCID 0000-0003-0192-9906

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The SH2-binding phosphotyrosine class of short linear motifs (SLiMs) are key conditional regulatory elements, particularly in signaling protein complexes beneath the cell's plasma membrane. In addition to transmitting cellular signaling information, they can also play roles in cellular hijack by invasive pathogens. Researchers can take advantage of bioinformatics tools and resources to predict the motifs at conserved phosphotyrosine residues in regions of intrinsically disordered protein. A candidate SH2-binding motif can be established and assigned to one or more of the SH2 domain subgroups. It is, however, not so straightforward to predict which SH2 domains are capable of binding the given candidate. This is largely due to the cooperative nature of the binding amino acids which enables poorer binding residues to be tolerated when the other residues are optimal. High-throughput peptide arrays are powerful tools used to derive SH2 domain-binding specificity, but they are unable to capture these cooperative effects and also suffer from other shortcomings. Tissue and cell type expression can help to restrict the list of available interactors: for example, some well-studied SH2 domain proteins are only present in the immune cell lineages. In this article, we provide a table of motif patterns and four bioinformatics strategies that introduce a range of tools that can be used in motif hunting in cellular and pathogen proteins. Experimental followup is essential to determine which SH2 domain/motif-containing proteins are the actual functional partners.

Indexed as

Amino Acidssrc Homology DomainsCell LineageCell MembranePhosphotyrosineAmino AcidsPhosphotyrosineBinding specificityCell signalingPathogen hijackPhosphotyrosineRegular expressionSH2 domainShort linear motif (SLiM)

Identifiers

PMID37668974

What Socratic holds

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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 Socratic graph.