Screening of a novel free fatty acid receptor 1 (FFAR1) agonist peptide by phage display and machine learning based-amino acid substitution.

Free fatty acid receptor 1 (FFAR1 or GPR40) has attracted attention for the treatment of type 2 diabetes mellitus, and various small-molecule agonists have been developed. However, most FFAR1 agonists as well as endogenous ligands, such as linoleic acids, have high lipophilicity, and their high lipophilicity is related to off-target toxicity. Therefore, we need to focus on new ligand candidates with less toxicity. In this study, we screened peptides with FFAR1 agonist activity as new ligand candidates. First, we used phage display to identify peptides with high affinity to FFAR1. Next, the agonist activities of peptides determined by the phage display were evaluated by the TGF-α shedding assay. Finally, to improve the FFAR1 agonist activity of the peptide, we performed an inclusive single amino acid substitution and sequence analysis. Logistic regression (LR) analysis using 120 physiochemical properties was performed to predict peptides with high FFAR1 agonist activity. STTGTQY determined by phage display promoted glucose-stimulated insulin secretion in pancreatic MIN6 cells. Furthermore, STKGTF predicted by the LR analysis showed high insulin secretion at low concentrations compared to STTGTQY. The results of this study suggest that peptides could be new candidates as FFAR1 agonists.