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Peer-reviewedCC BY 4.0Bioinformatics

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

  • Martina Vojtková1
  • Martynas Baltušis1
  • Hannah-Marie Martiny1
  • Amulya Baral2
  • Nikiforos Pyrounakis1
  • Attila Beleon1
  • Rebecca Freitag1
  • Anna Pico-Tomàs3
  • Rolf Sommer Kaas1
  • Thomas N Petersen1
  • Patrick Munk1
  1. 1Research Group for Genomic Epidemiology, Technical University of Denmark , 2800 Kongens Lyngby,
  2. 2Department of Production Animal Clinical Sciences, Faculty of Veterinary Medicine, Norwegian University of Life Sciences, 1433 Ås,
  3. 3Catalan Institute for Water Research (ICRA) , 17003 Girona, Catalonia
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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).

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Cite

BibTeXRIS
BibTeX
@article{vojtkova2026panres,
  title = {{PanRes: a database of latent and acquired antimicrobial resistance allowing 3D-based protein homology search}},
  author = {Martina Vojtková and Martynas Baltušis and Hannah-Marie Martiny and Amulya Baral and Nikiforos Pyrounakis and Attila Beleon and Rebecca Freitag and Anna Pico-Tomàs and Rolf Sommer Kaas and Thomas N Petersen and Patrick Munk},
  journal = {Bioinformatics},
  year = {2026},
  month = oct,
  doi = {10.1093/bioinformatics/btag776},
  url = {https://academic.oup.com/bioinformatics/article/doi/10.1093/bioinformatics/btag776/8917311},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - PanRes: a database of latent and acquired antimicrobial resistance allowing 3D-based protein homology search
AU  - Martina Vojtková
AU  - Martynas Baltušis
AU  - Hannah-Marie Martiny
AU  - Amulya Baral
AU  - Nikiforos Pyrounakis
AU  - Attila Beleon
AU  - Rebecca Freitag
AU  - Anna Pico-Tomàs
AU  - Rolf Sommer Kaas
AU  - Thomas N Petersen
AU  - Patrick Munk
PY  - 2026
DA  - 2026/10/15
JO  - Bioinformatics
DO  - 10.1093/bioinformatics/btag776
UR  - https://academic.oup.com/bioinformatics/article/doi/10.1093/bioinformatics/btag776/8917311
AB  - 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).
SN  - 1367-4803
SN  - 1367-4811
ER  -