Bioinformatic prediction and experimental validation of RiPP recognition elements

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a family of natural products for which discovery efforts have rapidly grown over the past decade. There are currently 38 known RiPP classes encoded by prokaryotes. Half of the prokaryotic RiPP classes include a protein domain called the RiPP Recognition Element (RRE) for successful installation of post-translational modifications on a RiPP precursor peptide. In most cases, the RRE domain binds to the N-terminal “leader” region of the precursor peptide, facilitating enzymatic modification of the C-terminal “core” region. The prevalence of the RRE domain renders it a theoretically useful bioinformatic handle for class-independent RiPP discovery; however, first-in-class RiPPs have yet to be isolated and experimentally characterized using an RRE-centric strategy. Moreover, with most known RRE domains engaging their cognate precursor peptide(s) with high specificity and nanomolar affinity, evaluation of the residue-specific interactions that govern RRE:substrate complexation is a necessary first step to leveraging the RRE domain for various bioengineering applications. This chapter details protocols for developing custom bioinformatic models to predict and annotate RRE domains in a class-specific manner. Next, we outline methods for experimental validation of precursor peptide binding using fluorescence polarization binding assays and in vitro enzyme activity assays. We anticipate the methods herein will guide and enhance future critical analyses of the RRE domain, eventually enabling its future use as a customizable tool for molecular biology.