ArticleJournal of molecular biology2026
PrePPI - Structure-based Prediction of Protein-protein Interactomes and Networks.
Article in Journal of molecular biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed.
- Proteome-wide prediction of interactions between structured domains and peptide motifs reveals functionally coherent subnetworks.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Combining structural modeling and deep learning to calculate the E. coli protein interactome and functional networks.Nature communications · 2026Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
PrePPI is a structure-based pipeline that predicts protein-protein interactions (PPIs) between two structured domains and between structured domains and short linear motifs (SLiMs) on a proteome-wide scale. Since the 2023 Computational Resource Issue of JMB, the PrePPI website has been significantly expanded and redesigned. The resource now includes interactomes for human, yeast, and E. coli proteomes with 3D models for high-confidence domain-level complexes and PDB templates for most of the SLiM-mediated predicted interactions. A key new addition is derived from the clustering of the PrePPI interactomes based entirely on the structure-based likelihood of an interaction. Remarkably these clusters exhibit functional coherence and provide an unprecedented proteome-wide depiction of the subnetworks of PPIs that underlie biological phenomena. The new website - https://honigcomplab.c2b2.columbia.edu/PrePPI - provides convenient access to these clusters, to structural models for each pairwise complex, and to function annotations for individual proteins, enabling multiple modes of biological discovery.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.