Review maps GAN models used for de novo peptide drug design
Authors say reported gains in predicted activity remain largely in silico, with multi-label data scarcity and property trade-offs the main barriers.
PR
By Priya Raman · Science Reporter
Aug 30 20:00 ETSource: Probiotics and antimicrobial proteins
The wire
- 01A review in Probiotics and Antimicrobial Proteins summarizes GAN architectures including CGAN, WGAN-GP and MPOGAN applied to designing antimicrobial, antiviral and anticancer peptide sequences.
- 02Machine-generated candidates are entering peptide pipelines, so readers tracking new peptide chemistry should know how thin the validation is behind reported activity gains.
- 03The authors note most results stop at in silico evaluation or early in vitro assays and propose LLM-assisted annotation and closed-loop AI-experimental platforms as next steps.
From the source
Read at pubmed.ncbi.nlm.nih.govGANs in Peptide Drug Discovery: From De Novo Design to Multi-Property Optimization and Clinical Translation
Probiotics and antimicrobial proteins · 2026 Aug 31 · Chu Y, Zhang S, Pan B et al.
Source URL https://pubmed.ncbi.nlm.nih.gov/42671526/