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PrePPI: A structure informed proteome-wide database of protein-protein interactions
Open accessPreprint — published as 10.1016/j.jmb.2023.168052
Abstract
We present an updated version of the Predicting Protein-Protein Interactions (PrePPI) webserver which predicts PPIs on a proteome-wide scale. PrePPI combines structural and non-structural clues within a Bayesian framework to compute a likelihood ratio (LR) for essentially every possible pair of proteins in a proteome; the current database is for the human interactome. The structural modeling (SM) clue is derived from templatebased modeling and its application on a proteome-wide scale is enabled by a unique scoring function used to evaluate a putative complex. The updated version of PrePPI leverages AlphaFold structures that are parsed into individual domains. As has been demonstrated in earlier applications, PrePPI performs extremely well as measured by receiver operating characteristic curves derived from testing on E. coli and human protein-protein interaction (PPI) databases. A PrePPI database of ~1.3 million human PPIs can be queried with a webserver application that comprises multiple functionalities for examining query proteins, template complexes, 3D models for predicted complexes, and related features ( https://honiglab.c2b2.columbia.edu/PrePPI ). PrePPI is a state-of- the-art resource that offers an unprecedented structure-informed view of the human interactome. Graphic Abstract:
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Highly accurate protein structure prediction with AlphaFold
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Metadata
- Authors
- Petrey, D., Zhao, H., Trudeau, S., Murray, D., & Honig, B.
- Affiliations
- Columbia University Irving Medical Center (US)
- Corresponding author
- Honig, Barry
- Venue
- Journal of Molecular Biology
- Publisher
- openRxiv
- Published
- 2023-02-28
- Volume
- 435
- Issue
- 14
- Pages
- 168052-168052
- ISSN
- 0022-2836 (ISSN-L)
- PMC
- PMC10293085
- OpenAlex
- W4327559507
- Cited by
- 49
- References
- 1
- Citations by year
- 2026: 11 · 2025: 12 · 2024: 16 · 2023: 10
- FWCI
- 4.37
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Molecular Biology (acceptedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- PubMed Central (submittedVersion)
- Funders
- National Institutes of Health (1s10od032433-01a1)
- National Cancer Institute (U54CA209997, U54CA274506)
- National Institute of General Medical Sciences (S06GM008224, T32GM008224, T32GM145440, R35GM139585)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Keywords
- protein-protein interaction, human interactome, AlphaFold, protein domains, web server
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