Agentic Discovery of Non-Canonical Antimicrobial Peptides with AMPGAN v3
Antimicrobial resistance causes to over a million deaths annually. Antimicrobial peptides (AMPs) are a promising solution, but generative AMP models are not yet ready to design peptides with non-natural amino acids and/or chemical modifications, which are essential for real-world peptide drugs. We present AMPGAN v3, a multi-objective conditional GAN that expands the generative vocabulary to D-amino acids and N/C-terminus modifications such as amidation. By separating adversarial and activity-aware supervision across two specialized discriminators, AMPGAN v3 substantially improves training stability and outperforms prior generative AMP models on external classifiers. We validated five cand...
| Authors | Jay Jung, Xiaohan Zhang, Shenghan Song et al. |
|---|---|
| Primary category | q-bio.QM |
| Published | 15 June 2026 |
| Last updated at source | 15 June 2026 |
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