AI-powered de novo architecturing of marine-mimetic antioxidant peptides in yeast synbio factories

The sustainable biosynthesis of structurally stable bioactive peptides remains a critical challenge for methanol-driven microbial cell factories. Here we present an AI-guided platform enabling de novo design of synthetic oyster-mimetic peptides (SOPs) through evolutionary-inspired protein assembly. A transformer-based language model prioritized 28 antioxidant peptides from 160 candidates, which were computationally assembled into template-free fusion architectures via natural sequence linguistics. SOPs successfully produced in Pichia pastoris under industrial scales, demonstrated a high yield of 34 g/kg dry cell weight, a reduced glutathione (GSH) content of 126.07 mg/L, and notable stability with a half-life of 15 days. Comparison with natural counterparts, SOPs exhibited 703 % higher radical scavenging capacity and superior hepatoprotection function in murine models. The embedded peptide VISDEHGIDPTK in SOPs acts as a Peroxisome proliferator-activated receptor alpha (PPARα) agonist, stabilizing ligand-receptor interactions via allosteric hydrogen bonding with Lys292 and Glu462, thereby ameliorating lipid dysregulation. SOPs demonstrated 90 % lower carbon emissions, 82 % water reduction, and 87.5 % energy savings in life cycle analysis compared to conventional marine extracted natural oyster-mimetic peptides (NOPs). This machine learning framework establishes a carbon-negative paradigm for precision bioengineering of therapeutic marine-mimetic peptides, overcoming historical limitations in marine resource dependency and structural instability. • A model is developed to screen oyster peptides with high antioxidant activity. • Oyster peptides were assembled based on a unique de novo protein architecture. • Synthetic oyster peptides emerged as a promising alternative to natural ones. • Synthetic oyster peptides emerged show superior functional characteristics. • Synthetic oyster peptides show efficacy in liver protection and lipid metabolism.