Artificial intelligence-driven antimicrobial peptide discovery
Paulina Szymczak Ewa Szczurek
Antimicrobial peptides (AMPs) emerge as promising agents against
antimicrobial resistance, providing an alternative to conventional antibiotics.
Artificial intelligence (AI) revolutionized AMP discovery through both
discrimination and generation approaches. The discriminators aid the
identification of promising candidates by predicting key peptide properties
such as activity and toxicity, while the generators learn the distribution over
peptides and enable sampling novel AMP candidates, either de novo, or as
analogues of a prototype peptide. Moreover, the controlled generation of AMPs
with desired properties is achieved by discriminator-guided filtering,
positive-only learning, latent space sampling, as well as conditional and
optimized generation. Here we review recent achievements in AI-driven AMP
discovery, highlighting the most exciting directions.