De novo antioxidant peptide design via machine learning and DFT studies.

Antioxidant peptides (AOPs) are highly valued in food and pharmaceutical industries due to their significant role in human function. This study introduces a novel approach to identifying robust AOPs using a deep generative model based on sequence representation. Through filtration with a deep-learning classification model and subsequent clustering via the Butina cluster algorithm, twelve peptides (GP1-GP12) with potential antioxidant capacity were predicted. Density functional theory (DFT) calculations guided the selection of six peptides for synthesis and biological experiments. Molecular orbital representations revealed that the HOMO for these peptides is primarily localized on the indole segment, underscoring its pivotal role in antioxidant activity. All six synthesized peptides exhibited antioxidant activity in the DPPH assay, while the hydroxyl radical test showed suboptimal results. A hemolysis assay confirmed the non-hemolytic nature of the generated peptides. Additionally, an in silico investigation explored the potential inhibitory interaction between the peptides and the Keap1 protein. Analysis revealed that ligands GP3, GP4, and GP12 induced significant structural changes in proteins, affecting their stability and flexibility. These findings highlight the capability of machine learning approaches in generating novel antioxidant peptides.

Peptiligase, an enzyme for efficient chemo-enzymatic synthesis of aviptadil.

Increasing attention to peptides as prospective therapeutics has created a renaissance in searching for new alternatives to the current peptide synthetic approaches as well as their modification. In this context, it is necessary to develop different approaches for peptide ligation. Using enzymes as a novel strategy and powerful tool for the peptide and protein ligation has recently received a lot of attention. We here designed a fully convergent chemo-enzymatic peptide synthesis (CEPS) process for the synthesis of aviptadil a 28-mer therapeutic peptide with potential therapeutic effects in various medical contexts specially in the treatment of acute respiratory distress syndrome (ARDS) by coupling two peptide segments with four different peptiligase variants in aqueous environments. Our study reveals that peptiligase variants are capable of ligation reaction in 15 min. The overall time of ligation is shorter than those peptides with similar lengths and hinderance to aviptadil which reported for conventional synthesis by full solid-phase peptide synthesis. Yields ranged from 54 % to 76 %.