June 15, 2016 (Vol. 36, No. 12)
Investigators led by scientists at The Scripps Research Institute (TSRI) say they have invented a technique for rapidly identifying various venoms that strike a specific target in the body and then optimizing such venoms for therapeutic use.
The researchers demonstrated the new method by using it to identify venoms that block a certain protein on T cells, Kv1.3, which is implicated in multiple sclerosis, rheumatoid arthritis, and other inflammatory disorders. The scientists then used their method to find an optimized, long-acting variant of a venom that blocks this protein and showed that the new molecule reduces inflammation in mice.
The study (“Autocrine-Based Selection of Drugs that Target Ion Channels from Combinatorial Venom Peptide Libraries”) appears in Angewandte Chemie.
To start, the TSRI-led team, including Richard A. Lerner, Ph.D., Lita Annenberg Hazen Professor of Immunochemistry, and first author Hongkai Zhang, Ph.D., a senior scientist in the Lerner laboratory, consulted animal toxin databases and assembled a list of 589 venoms whose protein sequences have features of interest. They then synthesized the venoms’ genes and inserted them into special viruses that deliver genes into cells.
The aim in this initial, proof-of-principle project was to find venoms that block the Kv1.3 potassium ion-channel protein. To screen their library of venoms for those that block Kv1.3, the researchers, including a team of collaborating biologists at the Institute for Advanced Immunochemical Studies at Shanghai Tech University, used a cell-based selection system of a type developed by Drs. Lerner, Zhang, and colleagues in 2012. They created a culture of special Kv1.3-containing test cells in which a strong interaction between a venom and a Kv1.3 ion channel would switch on a red fluorescence gene.
The researchers distributed the venom-gene-carrying viruses among the cells and used a fast, automated system to select the cells that showed strong fluorescence. Standard molecular biology techniques were then used to identify and quantify the venom genes these cells contained. The researchers repeated this selection process for three rounds to see which venom genes became most abundant in the cells.
In this way, the team soon identified 27 likely Kv1.3-blocking venoms. All but two turned out to be known blockers of the ion channel. Another had been reported in the literature as a suspected potassium-channel blocker, and the last, an uncharacterized scorpion venom called CllTx1, proved in subsequent traditional-method testing—using actual venom extracted from a scorpion—to be a potent Kv1.3 blocker.
The team realized that their selection system could be useful not only for screening libraries of natural venoms but also for screening artificial variants or analogs of a given venom to find those with optimal pharmaceutical properties. To demonstrate, they generated about a million analogs of a long-acting protein based on ShK, a sea anemone toxin that blocks Kv1.3, and put the analogs through three rounds of selection to find the best one.
The resulting candidate, S1-2, showed a strong effect not only for blocking Kv1.3 but also for reducing inflammation in a standard rodent model.
