ProtAlign-ARG: antibiotic resistance gene characterization integrating protein language models and alignment-based scoring.

ABSTRACT: The evolution and spread of antibiotic resistance pose a global health challenge. Whole genome and metagenomic sequencing offer a promising approach to monitoring the spread, but typical alignment-based approaches for antibiotic resistance gene (ARG) detection are inherently limited in the ability to detect new variants. Large protein language models could present a powerful alternative but are limited by databases available for training. Here we introduce ProtAlign-ARG, a novel hybrid model combining a pre-trained protein language model and an alignment scoring-based model to expand the capacity for ARG detection from DNA sequencing data. ProtAlign-ARG learns from vast unannotated protein sequences, utilizing raw protein language model embeddings to improve the accuracy of ARG classificat

SUBMITTER: Ahmed S 

PROVIDER: S-EPMC12361412 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature