Toxins are useful pharmacological tools for probing the structure and function of their molecular targets. Their previously demonstrated potential to act as stable, highly selective and potent ligands make them an attractive source for therapeutic development. Furthermore, their small size (<100 residues) make them ideal for structural analysis using NMR.
Here we seek to identify and establish a database of secreted cysteine-rich repeat peptides, termed “SCREPs”, forming a new structural class. Currently, there are very few studied examples, however, recent research in the O.huwena toxin (DkTx) indicates this novel class may display unique bivalent activity (Bohlen, Priel et al. 2010). DkTx has further proven itself as a powerful tool for elucidating structural information of the TRPV1 / DkTx complex, revealing an open state conformation of the channel, as well as identifying binding regions located on the external pore; this was achieved by combining cryo-EM results with NMR derived restraints (Bae, Anselmi et al. 2016).
The focus of this work is to produce and characterize a range of SCREPs, constructing methods that will enable better insights into their inherent features. Datamining techniques were used to extract sequences from the UniProtKB database; yielding an approximate ninety thousand SCREP candidates. By analyzing the sequence homology between SCREPs and known bioactive toxins, we are attempting to identify biologically relevant novel peptides, specifically those targeting ion channels. So far, recombinant production of nine selected SCREPs have indicated appropriate levels of expression for at least five peptides. High-resolution structural characterization by NMR will be presented for one of these novel SCREPS, shedding further light on this new structural class of peptides.