Synthetic-bioinformatic natural product-inspired peptides

Abstract

Covering: 2016 to 2024

Natural products, particularly cyclic peptides, are a promising source of bioactive compounds. Nonribosomal peptide synthetases (NRPSs) play a key role in biosynthesizing these compounds, which include antibiotic and anticancer agents, immunosuppressants, and others. Traditional methods of discovering natural products have limitations including cryptic biosynthetic gene clusters (BGCs), low titers, and currently unculturable organisms. This has prompted the exploration of alternative approaches. Synthetic-bioinformatic natural products (syn-BNPs) are one such alternative that utilizes bioinformatics techniques to predict nonribosomal peptides (NRPs) followed by chemical synthesis of the predicted peptides. This approach has shown promise, resulting in the discovery of a variety of bioactive compounds including peptides with antibacterial, antifungal, anticancer, and proteasome-stimulating activities. Despite the success of this approach, challenges remain especially in the accurate prediction of fatty acid incorporation, tailoring enzyme modifications, and peptide release mechanisms. Further work in these areas will enable the discovery of many bioactive peptides that are currently inaccessible.