ArticleNature microbiology2024
Protein interactions in human pathogens revealed through deep learning.
Article in Nature microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 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.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
30 citing papers in PubMed.
- AlphaFold reveals how pathogenicmBio · 2026Article
- What will be the future of computational biology for macromolecules in the era of AI?PLoS computational biology · 2026Article
- A broadly conserved gram-positive lipoprotein regulates cell elongation.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Linear-time prediction of proteome-scale microbial protein interactions.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Structural insights into predicted protein-protein interactions and protein complexes in the human proteome.Scientific reports · 2026Article
- Artificial intelligence driven protein design and sustainable nanomedicine for advanced theranostics.Bioactive materials · 2026Review
- ProteomeLM: A proteome-scale language model enables accurate and rapid prediction of protein-protein interactions and gene essentiality across taxa.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- T3SS effector and regulator discovery by predicting interacting partners of T3SS chaperones in Pseudomonas aeruginosa.Protein science : a publication of the Protein Society · 2026Article
- Protein foundation models: a comprehensive survey.Science China. Life sciences · 2026Review
- Rapid Proteome-Wide Discovery of Protein-Protein Interactions With ppIRIS.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Quantifying and combating zoonotic viruses poised for emergence: Using multiplex receptor screening and decoy engineering technologies.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Backbone Thioamidation of a Ribosomal Subunit Protein in Pseudomonadota.Biochemistry · 2026Article
- Opening the black box: insights into ubiquitin-mediated control of innate antiviral immunity and AI-enhanced therapeutics.Frontiers in immunology · 2026Review
- Viral diversity of brine and precipitated halite of Tuz Lake, an inland hypersaline lake in Turkey.Archives of virology · 2025Article
- Integrating multi-omics data to reveal the host-microbiota interactome in inflammatory bowel disease.Gut microbes · 2025Review
- NMR in the Age of Modern Biomedical Research and Drug Discovery.Journal of molecular biology · 2025Review
- A Structure-Guided Kinase-Transcription Factor Interactome Atlas Reveals Docking Landscapes of the Kinome.bioRxiv : the preprint server for biology · 2025Article
- An arthropod transporter IsOATP4056 exerts inhibitory effect on its interacting membrane protein to facilitate rickettsial pathogen survival in ticks.Cell communication and signaling : CCS · 2025Article
- Predicting protein-protein interactions in the human proteome.Science (New York, N.Y.) · 2025Article
- Computational function prediction of bacteria and phage proteins.Microbiology and molecular biology reviews : MMBR · 2025Review
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Authors and funding
15 authors.
Funding
Abstract
Identification of bacterial protein-protein interactions and predicting the structures of these complexes could aid in the understanding of pathogenicity mechanisms and developing treatments for infectious diseases. Here we developed RoseTTAFold2-Lite, a rapid deep learning model that leverages residue-residue coevolution and protein structure prediction to systematically identify and structurally characterize protein-protein interactions at the proteome-wide scale. Using this pipeline, we searched through 78 million pairs of proteins across 19 human bacterial pathogens and identified 1,923 confidently predicted complexes involving essential genes and 256 involving virulence factors. Many of these complexes were not previously known; we experimentally tested 12 such predictions, and half of them were validated. The predicted interactions span core metabolic and virulence pathways ranging from post-transcriptional modification to acid neutralization to outer-membrane machinery and should contribute to our understanding of the biology of these important pathogens and the design of drugs to combat them.
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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.