A research team has created a new algorithmic method for generating mirror-image peptides making an important advancement in peptide therapeutics. Using existing protein databases, the team identified two peptides that are current drug therapies in their naturally occurring (L)-form and synthesized their mirror-image (D)-form. The team demonstrated that the enantiomer peptides have the same therapeutic efficacy as their naturally occurring counterpart and have a much longer half-life. The study findings were published in Proceedings of the Natural Academy of Sciences.
Simply converting (L)-peptides to (D)-peptides alters the peptide and results in loss of function. The team used a computational approach to create mirror images of all 111,867 molecules in the Protein Data Bank (PDB) creating a D-PDB database. Using an algorithm to search for therapeutically active structures, the team identified two (D)-peptides whose counterparts are widely used peptide drugs. GLP-1 is a treatment for diabetes and PTH is an osteoporosis drug therapy.
(D)-peptides for both targets were synthesized and the researchers used an HEK293 stable cell line expression model to demonstrate that both mirror-image peptides had the same efficacy and were worked longer than their naturally occurring counterparts. It is known that (D)-peptides are resistant to protein degradation resulting in longer bioavailability. In addition, the team is investigating the potential for these drugs to be taken in pill form, instead of intravenously or by injection, which would simplify daily administration.
"Mirror image peptides are not recognized and degraded by enzymes in the stomach or bloodstream and therefore have a long-lasting effect," says Philip Kim, a professor of computer science and molecular genetics in the University of Toronto's Donnelly Centre for Cellular and Biomolecular Research. The other advantage, he said, is that mirror-image peptides also get overlooked by the immune system, which often mistakes natural peptides for foreign invaders and thus limits drug efficacy.
Image: The new method overcomes obstacles in designing D versions of complex helical peptides. Image courtesy of Michael Garton, University of Toronto