PreprintCited by 1Bioinformatics and Genomic NetworksMachine Learning in BioinformaticsProtein Structure and Dynamics

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Narrow funnel-like interaction energy distribution is an indicator of specific protein interaction partners

Open access
Choi, Juyoung·2022·iScience

Preprint — published as 10.1016/j.isci.2023.106911 · Paper page

Abstract

Biological mechanisms consist of protein interaction networks. However, most of protein interaction prediction are based on interspecies biological evidences (knowledge-based predictions) or exhibits low accuracy for weak interactions and requires high computational power (in silico docking method). In this study, I suggest a novel method to identify protein interaction using interaction energy distribution. Protein interactions with specific partners can be predicted by searching narrow funnel-like interaction energy distribution. Kinases and E3 ubiquitin ligase are important signaling components. However, as their interactions are weak and various, those interaction predictions are limited. I described that their interaction partners can be identified by analyzing interaction energy distribution with low computational cost. The accuracy of this prediction was similar or even higher than those of yeast two-hybrid screening, the most widely applied interaction screening method. Furthermore, I showed that other specific protein interactions have narrow funnel-like interaction energy distribution. In summary, this knowledge-free protein interaction prediction method would broaden our understanding of protein interaction networks.

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Metadata

Authors
Choi, J.
Affiliations
Sogang University (KR)
Corresponding author
Choi, Juyoung
Venue
iScience
Published
2022-03-25
Volume
26
Issue
6
Pages
106911-106911
ISSN
2589-0042 (ISSN-L)
OpenAlex
W4377086792
Cited by
1
References
1
Citations by year
2026: 1
FWCI
0.09
Type
journal article
Language
en
Open access
Locations
  • iScience (publishedVersion, cc-by)
  • Research Square (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Seoul National University
  • Hallym University
  • Sogang University
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
Keywords
protein-protein interaction prediction, kinase substrate prediction, TM-score, protein-protein interaction network

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