Artificial intelligence using a latent diffusion model enables the generation of diverse and potent antimicrobial peptides

Artificial intelligence holds great promise for the design of antimicrobial peptides (AMPs); however, current models face limitations in generating AMPs with sufficient novelty and diversity, and they are rarely applied to the generation of antifungal peptides. Here, we develop an alternative pipeline grounded in a diffusion model and molecular dynamics for the de novo design of AMPs. The peptides generated by our pipeline have lower similarity and identity than those of other reported methodologies. Among the 40 peptides synthesized for an experimental validation, 25 exhibit either antibacterial or antifungal activity. AMP-29 shows selective antifungal activity against Candida glabrata and in vivo antifungal…