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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 comprise protein interaction networks. However, most protein interaction predictions are based on interspecies biological evidence. These knowledge-based predictions are biased and have limited predictive ranges. Moreover, protein interaction prediction using in silico docking exhibits low accuracy for weak interactions and requires high computational power. This study suggests 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, because their interactions vary and are weak, the interaction predictions are highly limited. However, this study shows that their interaction can be identified by analyzing interaction energy distribution with high accuracy and low computational cost. Furthermore, other specific protein interactions have significantly narrower funnel-like interaction energy distribution than those of noninteracting protein pairs.
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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
- 2022-03-03
- 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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