Paving the way for new antimicrobial peptides through molecular de-extinction

Abstract

Molecular de extinction has emerged as a novel strategy for studying biological molecules throughout evolutionary history. Among the myriad possibilities offered by ancient genomes and proteomes, antimicrobial peptides (AMPs) stand out as particularly promising alternatives to traditional antibiotics. Various strategies, including software tools and advanced deep learning models, have been used to mine these host de fense peptides. For example, computational analysis of disulfide bond patterns has led to the identification of six previously uncharacterized p-defensins in extinct and critically endangered species. Additionally, artificial intelligence and machine learning have been utilized to uncover ancient antibiotics, revealing numerous candidates, including mammu thusin, and elephasin, which display inhibitory effects toward pathogens in vitro and in vivo. These innovations promise to discover novel antibiot ics and deepen our insight into evolutionary processes.