Computational identification of protein complexes from network interactions: Present state, challenges, and the way forward

Omranian, Sara; Nikoloski, Zoran; Grimm, Dominik G.

doi:10.1016/j.csbj.2022.05.049

Cited by 8 publications

(5 citation statements)

References 95 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Protein-protein interaction (PPI) networks are becoming increasingly popular, since they facilitate the enhanced description and understanding of cellular systems in physiological conditions and disease [ 39 ]. They can also aid in deciphering the biological function of proteins [ 40 ] and the prediction of protein complexes [ 41 ]. Additionally, PPI networks can provide useful insights on potential interacting partners, enabling experimental biologists to prioritize research targets.…”

Section: Resultsmentioning

confidence: 99%

LIRcentral: a manually curated online database of experimentally validated functional LIR motifs

Chatzichristofi,

Sagris,

Pallaris

et al. 2023

Autophagy

View full text Add to dashboard Cite

Several selective macroautophagy receptor and adaptor proteins bind members of the Atg8 (autophagy related 8) family using short linear motifs (SLiMs), most often referred to as Atg8-family interacting motifs (AIMs) or LC3-interacting regions (LIRs). AIM/LIR motifs have been extensively studied during the last fifteen years, since they can uncover the underlying biological mechanisms and possible substrates for this key catabolic process of eukaryotic cells. Prompted by the fact that experimental information regarding LIR motifs can be found scattered across heterogeneous literature resources, we have developed LIRcentral ( https://lircentral.eu ), a freely available online repository for user-friendly access to comprehensive, high-quality information regarding LIR motifs from manually curated publications. Herein, we describe the development of LIRcentral and showcase currently available data and features, along with our plans for the expansion of this resource. Information incorporated in LIRcentral is useful for accomplishing a variety of research tasks, including: (i) guiding wet biology researchers for the characterization of novel instances of LIR motifs, (ii) giving bioinformaticians/computational biologists access to high-quality LIR motifs for building novel prediction methods for LIR motifs and LIR containing proteins (LIRCPs) and (iii) performing analyses to better understand the biological importance/features of functional LIR motifs. We welcome feedback on the LIRcentral content and functionality by all interested researchers and anticipate this work to spearhead a community effort for sustaining this resource which will further promote progress in studying LIR motifs/LIRCPs. Abbreviations : AIM, Atg8-family interacting motif; Atg8, autophagy related 8; GABARAP, GABA type A receptor-associated protein; LIR, LC3-interacting region; LIRCP, LIR-containing protein; MAP1LC3/LC3, microtubule associated protein 1 light chain 3; PMID, PubMed identifier; PPI, protein-protein interaction; SLiM, short linear motif

show abstract

Section: Resultsmentioning

confidence: 99%

LIRcentral: a manually curated online database of experimentally validated functional LIR motifs

Chatzichristofi,

Sagris,

Pallaris

et al. 2023

Autophagy

View full text Add to dashboard Cite

show abstract

“…Protein-protein interaction (PPI) networks are becoming increasingly popular, since they facilitate the enhanced description and understanding of cellular systems in physiological conditions and disease [37]. They can also aid in deciphering the biological function of proteins [38] and the prediction of protein complexes [39]. Additionally, PPI networks can provide useful insights on potential interacting partners, enabling experimental biologists to prioritize research targets.…”

Section: Resultsmentioning

confidence: 99%

“…They can also aid in deciphering the biological function of proteins [38] and the prediction of protein complexes [39]. Additionally, PPI networks can provide useful insights on potential interacting partners, enabling experimental biologists to prioritize research targets.…”

Section: Saccharomyces Cerevisiaementioning

confidence: 99%

LIRcentral: a manually curated online database of experimentally validated functional LIR-motifs

Chatzichristofi

Sagris

Pallaris

et al. 2022

Preprint

View full text Add to dashboard Cite

Several selective macroautophagy receptor and adaptor proteins bind members of the Autophagy-related protein 8 (Atg8) family using short linear motifs (SLiMs), most often referred to as Atg8-interacting motifs (AIM) or LC3-interacting motifs (LIR). AIM/LIR-motifs have been extensively studied during the last fifteen years, since they can uncover the underlying biological mechanisms and possible substrates for this key catabolic process of eukaryotic cells. Prompted by the fact that experimental information regarding LIR-motifs can be found scattered across heterogeneous literature resources, we have developed LIRcentral (https://lircentral.eu), a freely available online repository for user-friendly access to comprehensive, high-quality information regarding LIR-motifs from manually curated publications. Herein, we describe the development of LIRcentral and showcase currently available data and features, along with our plans for the expansion of this resource. Information incorporated in LIRcentral is useful for accomplishing a variety of research tasks, including: (i) guiding wet biology researchers for the characterization of novel instances of LIR-motifs, (ii) giving bioinformaticians/computational biologists access to high-quality LIR-motifs for building novel prediction methods for LIR-motifs and LIR containing proteins (LIRCPs) and (iii) performing analyses to better understand the biological importance/features of functional LIR-motifs. We welcome feedback on the LIRcentral content and functionality by all interested researchers and anticipate this work to spearhead a community effort for sustaining this resource which will further promote progress in studying LIR-motifs/LIRCPs.

show abstract

“…Bioinformatics tools, including linking protein functional information through networks and gene ontology (GO) analysis, are powerful tools for this purpose. 21 Such tools allow to redraw the signaling pathways and group together RefProts belonging to the same biological process, molecular function, or cellular localization, increasing the information about the cellular mechanism. Such information can be obtained through databases holding information on protein-protein interactions (PPIs) such as STRING, 22 BioGrid, 23 and IntAct 24 allowing them to be applied to a large-scale protein analysis such as a bottom-up approach by chromatography coupled to mass spectrometry analysis (LC-MS/MS) of RefProts.…”

Section: Introductionmentioning

confidence: 99%

Employing non-targeted interactomics approach and subcellular fractionation to increase our understanding of the ghost proteome

Rio¹,

Cardon²,

Eyckerman³

et al. 2023

iScience

View full text Add to dashboard Cite

Computational identification of protein complexes from network interactions: Present state, challenges, and the way forward

Cited by 8 publications

References 95 publications

LIRcentral: a manually curated online database of experimentally validated functional LIR motifs

LIRcentral: a manually curated online database of experimentally validated functional LIR motifs

LIRcentral: a manually curated online database of experimentally validated functional LIR-motifs

Employing non-targeted interactomics approach and subcellular fractionation to increase our understanding of the ghost proteome

Contact Info

Product

Resources

About