A sweeter future: Using protein language models for exploring sweeter brazzein homologs

Abstract

With growing concerns over the health impact of sugar, brazzein offers a viable alternative due to its sweetness, thermostability, and low risk profile. Here, we demonstrated the ability of protein language models to design new brazzein homologs with improved thermostability and potentially higher sweetness, resulting in new diverse optimized amino acid sequences that improve structural and functional features beyond what conventional methods could achieve. This innovative approach resulted in the identification of unexpected mutations, thereby generating new possibilities for protein engineering. To facilitate the characterization of the brazzein mutants, a simplified procedure was developed for expressing and analyzing related proteins. This process involved an efficient purification method using Lactococcus lactis (L. lactis), a generally recognized as safe (GRAS) bacterium, as well as taste receptor assays to evaluate sweetness. The study successfully demonstrated the potential of computational design in producing a more heat-resistant and potentially more palatable brazzein variant, V23.

Keywords: Alternative sweeteners; Brazzein; Computational design; Generative AI; Lactococcus lactis; Thermostable.