Uncovering domain motif interactions using high-throughput protein-protein interaction detection methods.

Idrees, S; Paudel, KR; Sadaf, T; Hansbro, PM

Uncovering domain motif interactions using high-throughput protein-protein interaction detection methods.

Idrees, S

Paudel, KR Sadaf, T Hansbro, PM

Permalink

Publisher:: Wiley
Publication Type:: Journal Article
Citation:: FEBS Lett, 2024
Issue Date:: 2024-03-05

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Published versionAdobe PDF (738.08 kB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Idrees, S https://orcid.org/0000-0001-8512-7593
dc.contributor.author	Paudel, KR
dc.contributor.author	Sadaf, T
dc.contributor.author	Hansbro, PM
dc.date.accessioned	2024-03-11T22:32:53Z
dc.date.available	2024-02-18
dc.date.available	2024-03-11T22:32:53Z
dc.date.issued	2024-03-05
dc.identifier.citation	FEBS Lett, 2024
dc.identifier.issn	0014-5793
dc.identifier.issn	1873-3468
dc.identifier.uri	http://hdl.handle.net/10453/176497
dc.description.abstract	Protein-protein interactions (PPIs) are often mediated by short linear motifs (SLiMs) in one protein and domain in another, known as domain-motif interactions (DMIs). During the past decade, SLiMs have been studied to find their role in cellular functions such as post-translational modifications, regulatory processes, protein scaffolding, cell cycle progression, cell adhesion, cell signalling and substrate selection for proteasomal degradation. This review provides a comprehensive overview of the current PPI detection techniques and resources, focusing on their relevance to capturing interactions mediated by SLiMs. We also address the challenges associated with capturing DMIs. Moreover, a case study analysing the BioGrid database as a source of DMI prediction revealed significant known DMI enrichment in different PPI detection methods. Overall, it can be said that current high-throughput PPI detection methods can be a reliable source for predicting DMIs.
dc.language	eng
dc.publisher	Wiley
dc.relation.ispartof	FEBS Lett
dc.relation.isbasedon	10.1002/1873-3468.14841
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0304 Medicinal and Biomolecular Chemistry, 0601 Biochemistry and Cell Biology, 0603 Evolutionary Biology
dc.subject.classification	Biochemistry & Molecular Biology
dc.subject.classification	3101 Biochemistry and cell biology
dc.title	Uncovering domain motif interactions using high-throughput protein-protein interaction detection methods.
dc.type	Journal Article
utslib.location.activity	England
utslib.for	0304 Medicinal and Biomolecular Chemistry
utslib.for	0601 Biochemistry and Cell Biology
utslib.for	0603 Evolutionary Biology
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Science
pubs.organisational-group	University of Technology Sydney/Strength - CFI - Centre for Inflammation
utslib.copyright.status	open_access	*
dc.date.updated	2024-03-11T22:32:52Z
pubs.publication-status	Published online

Abstract:

Protein-protein interactions (PPIs) are often mediated by short linear motifs (SLiMs) in one protein and domain in another, known as domain-motif interactions (DMIs). During the past decade, SLiMs have been studied to find their role in cellular functions such as post-translational modifications, regulatory processes, protein scaffolding, cell cycle progression, cell adhesion, cell signalling and substrate selection for proteasomal degradation. This review provides a comprehensive overview of the current PPI detection techniques and resources, focusing on their relevance to capturing interactions mediated by SLiMs. We also address the challenges associated with capturing DMIs. Moreover, a case study analysing the BioGrid database as a source of DMI prediction revealed significant known DMI enrichment in different PPI detection methods. Overall, it can be said that current high-throughput PPI detection methods can be a reliable source for predicting DMIs.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/176497