Evidence map›Paper›PMID 22468754›Full record

ArticleJournal of proteome research2012

Characterization of domain-peptide interaction interface: prediction of SH3 domain-mediated protein-protein interaction network in yeast by generic structure-based models.

Tingjun Hou, Nan Li, Youyong Li, Wei Wang

Abstract read
In one paragraph

Article in Journal of proteome research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

58 citing papers in PubMed.

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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

4 authors.

Tingjun HouInstitute of Functional Nano & Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, China. tjhou@suda.edu.cn
Nan Li
Youyong Li
Wei Wang

Funding

Protein recognition for modular domainsR01GM085188 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI WANG, WEI · 2009 to 2012
$1.2M
NIGMS NIH HHS R01 GM085188NIGMS NIH HHS R01GM085188
6 · The paper itself

Abstract

Determination of the binding specificity of SH3 domain, a peptide recognition module (PRM), is important to understand their biological functions and reconstruct the SH3-mediated protein-protein interaction network. In the present study, the SH3-peptide interactions for both class I and II SH3 domains were characterized by the intermolecular residue-residue interaction network. We developed generic MIEC-SVM models to infer SH3 domain-peptide recognition specificity that achieved satisfactory prediction accuracy. By investigating the domain-peptide recognition mechanisms at the residue level, we found that the class-I and class-II binding peptides have different binding modes even though they occupy the same binding site of SH3. Furthermore, we predicted the potential binding partners of SH3 domains in the yeast proteome and constructed the SH3-mediated protein-protein interaction network. Comparison with the experimentally determined interactions confirmed the effectiveness of our approach. This study showed that our sophisticated computational approach not only provides a powerful platform to decipher protein recognition code at the molecular level but also allows identification of peptide-mediated protein interactions at a proteomic scale. We believe that such an approach is general to be applicable to other domain-peptide interactions.

Indexed as

Protein Interaction Mapssrc Homology DomainsAmino Acid MotifsAmino Acid SequenceBinding SitesComputer SimulationFungal ProteinsModels, MolecularMolecular Sequence DataMultiprotein ComplexesSaccharomyces cerevisiaeSensitivity and SpecificitySequence AlignmentSequence Homology, Amino AcidSubstrate SpecificitySupport Vector MachineFungal ProteinsMultiprotein Complexes

Identifiers

PMID22468754
PMCPMC3345086

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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 OpenQuestion graph.