PanRes: A database of latent and acquired antimicrobial resistance allowing 3D-based protein homology search

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ID: 332457
2026
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Abstract
Abstract Motivation Antimicrobial resistance databases are central to genomic surveillance, but resistance determinants remain distributed across resources with different scopes, structures, and annotations. Results We developed PanRes, a curated resistance database of 11 717 genes integrating acquired and latent determinants of antibiotic, biocide, and metal resistance within a unified ontology. We predicted representative protein structures and clustered them by structural similarity, grouping proteins into 505 high-confidence structurally conserved clusters coherent despite sequence divergence. Their structure-guided alignments were used to build Hidden Markov Models (HMMs) for remote homology search. In seven wastewater metagenomes from five European cities, PanRes 3D-based HMMs expanded detection beyond what was possible with BLAST, with 35.3% of retained hits identified only by the HMMs and generally showing greater divergence from known proteins. For beta-lactamases, several proteins retained beta-lactamase-like folds and catalytic geometry despite weak sequence similarity. Availability and implementation PanRes is available through an interactive web platform (https://panres.rambio.dk/), a structure-informed resource for exploring the whole resistome. The database, HMM profiles, and ontology are available at Zenodo (10.5281/zenodo.22876216). Supplementary information Supplementary data are available at Bioinformatics online.
Reference Key
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Authors Martina Vojtková, Martynas Baltušis, Hannah-Marie Martiny, Amulya Baral, Nikiforos Pyrounakis, Attila Beleon, Rebecca Freitag, Anna Pico-Tomàs, Rolf Sommer Kaas, Thomas N Petersen, Patrick Munk
Journal BMC Bioinformatics
Year 2026
DOI
10.1093/bioinformatics/btag776
URL
https://doi.org/10.1093/bioinformatics/btag776
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