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