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Narrow funnel-like interaction energy distribution is an indicator of specific protein interaction partners
Open accessPreprint — 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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Cites
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
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Metadata
- Authors
- Choi, J.
- Affiliations
- Sogang University (KR)
- Corresponding author
- Choi, Juyoung
- ORCID
- Choi, Juyoung
- Venue
- iScience
- Published
- 2022-03-25
- Volume
- 26
- Issue
- 6
- Pages
- 106911-106911
- ISSN
- 2589-0042 (ISSN-L)
- PMC
- PMC10250834
- OpenAlex
- W4377086792
- Cited by
- 1
- References
- 1
- Citations by year
- 2026: 1
- FWCI
- 0.09
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- 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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