ArticleScience advances2025
RBPseg: Toward a complete phage tail fiber structure atlas.
Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Precision phage therapy in the AI/ML era: a systematic review of discovery-to-clinical translation evidence.Frontiers in microbiology · 2026Pooled it
- Phage bioinformatics tools: a review of computational approaches for bacteriophage research.Briefings in bioinformatics · 2026Review
- Isolation and Genomic Characterisation of Five Novel Lytic Bacteriophages Infecting the Emerging PathogenViruses · 2026Article
- Intact architectures of myophage phi92 in extended and contracted states.PLoS pathogens · 2026Article
- Review
- Auxin (Indole-3-acetic acid) modulation of quorum sensing enhances phage susceptibility in Klebsiella pneumoniae.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026Article
- Computational prediction resolves thousands of homooligomeric phage protein structures.bioRxiv : the preprint server for biology · 2026Article
- From structure to design: experimental and AI-driven approaches in receptor-binding protein engineering for reprogramming phage host range.Archives of microbiology · 2026Review
- Article
- Identification of candidate nucleomodulins in ESKAPE bacteria -Frontiers in cellular and infection microbiology · 2026Article
- Key directions of fundamental research on bacteriophage Receptor Binding Proteins with applied potential.Frontiers in microbiology · 2026Review
- Bacteriophage-mediated biofilm control: a novel targeted strategy for the management of dental caries.Frontiers in cellular and infection microbiology · 2026Review
- Advanced Strategies in Phage Research: Innovations, Applications, and Challenges.Microorganisms · 2025Review
- Completing the BASEL phage collection to unlock hidden diversity for systematic exploration of phage-host interactions.PLoS biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bacteriophages use receptor-binding proteins (RBPs) to adhere to bacterial hosts, yet their sequence and structural diversity remain poorly understood. Tail fibers, a major class of RBPs, are elongated and flexible trimeric proteins, making their full-length structures difficult to resolve experimentally. Advances in deep learning-based protein structure prediction, such as AlphaFold2-multimer (AF2M) and ESMFold, provide opportunities for studying these challenging proteins. Here, we introduce RBPseg, a method that combines monomeric ESMFold predictions with a structural-based domain identification approach, to divide tail fiber sequences into manageable fractions for high-confidence modeling with AF2M. Using this approach, we generated complete tail fiber models, validated by single-particle cryo-electron microscopy of five fibers from three phages. A structural classification of 67 fibers identified 16 distinct classes and 89 domains, revealing patterns of modularity, convergence, divergence, and domain swapping. Our findings suggest that these structural classes represent at least 24% of the known tail fiber universe, providing key insights into their evolution and functionality.
Indexed as
Identifiers
What OpenQuestion holds
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.