Work

Archaeasins as a promising resource for developing next-generation antibiotics uncovered via deep learning

Year: 2025

Type: article

Abstract: Fighting against antibiotic resistance has an unexpected ally, archaea. Despite the extensive exploration of antimicrobial peptides in bacteria and eukaryotes, the archaeal domain has been overlooked. A recent study employed deep learning to screen archaeasins. The synthesized versions showed a 93 % success rate against pathogens by depolarizing the cytoplasmic membrane, not the outer membrane. This highlights the promise and deep learning power of archaea for antibiotic discovery and the culture of uncultured archaea.

Source: Engineering Microbiology

DOI: 10.1016/j.engmic.2025.100241

Authors: Huan Du, Yang Liu

Institution: Shenzhen University

Language: English

Topic: Antimicrobial Peptides and Activities

Subfield: Microbiology

Field: Immunology and Microbiology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $1,960

Funders: Natural Science Foundation of Shenzhen City, National Natural Science Foundation of China