Discovery of a novel UV-absorbing mycosporine-like amino acid in Vertebrata lanosa using an expanded combinatorial structure database incorporating non-proteinogenic amino acids and organic solutes

Abstract

Mycosporine-like amino acids (MAAs) are among nature's most effective sunscreen compounds, capable of converting harmful ultraviolet radiation into harmless heat, and are widely distributed in marine organisms such as red macroalgae. Although decades of research have led to numerous discoveries, the rate of new MAA identifications has declined. To address this, we considerably expanded our previously developed combinatorial MAA database, increasing the number of covered structures tenfold. Following a comprehensive literature search for plausible but undescribed building blocks, the database now incorporates an extensive set of proteinogenic and non-proteinogenic amino acids, as well as other marine organic osmolytes, in combination with all (currently) known MAA scaffolds. This expanded resource was integrated into our identification platform, which combines UHPLC-VWD-HRMS2 analysis, feature-based molecular networking, and bioinformatics-driven annotation. Application of this updated workflow enabled the isolation and structural elucidation of a novel MAA, mycosporine-cysteinolic acid, from the red marine macroalga Vertebrata lanosa. Altogether, this study provides a valuable extension of the bioinformatics-based MAA screening pipeline, enhancing the annotation and discovery of novel MAAs in natural matrices.