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

Authors

Vojtkova, M., Baltusis, M., Martiny, H.-M., Baral, A., Pyrounakis, N., Beleon, A., Freitag, R., Pico-Tomas, A., Kaas, R. S., Petersen, T. N., Munk, P.

Abstract

Antimicrobial resistance databases are central to genomic surveillance, but resistance determinants remain distributed across resources with different scopes, structures, and annotations. 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 598 structurally conserved clusters coherent despite sequence divergence. Their structure-guided alignments were used to build Hidden Markov Models (HMMs) for remote homology search. In wastewater metagenomes from seven European cities, PanRes 3D-based HMMs expanded detection beyond high-confidence BLAST, with 35.2% 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. PanRes is available through an interactive web platform (https://panres.rambio.dk/), a structure-informed resource for exploring the whole resistome.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 23 Jun 2026.

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