Omics-based strategies to discover novel classes of RiPP natural products

Ribosomally synthesized and post-translationally modified peptides (RiPPs) form a highly diverse class of natural products, with various biotechnologically clinically relevant activities. A recent increase in discoveries novel RiPP classes suggests that currently known RiPPs constitute just the tip iceberg. Genome mining has been driving force behind these discoveries, but remains challenging due to lack universal genetic markers for detection. In this review, we discuss how genome methodologies contribute towards discovery classes. Some methods prioritize biosynthetic gene clusters (BGCs) based on shared modifications between Other identify precursors using machine-learning classifiers. The integration such as well other types omics data more comprehensive pipelines could help tools reach their potential, keep pushing boundaries chemical diversity important molecules.