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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Synthetic molecular evolution of hybrid cell penetrating peptides that efficiently deliver peptide and peptide nucleic acid cargoes to cells

January 2017 (has links)
acase@tulane.edu / Peptides and peptide nucleic acids (PNAs) have long been recognized as promising tools and potential therapeutics. Yet the cell membrane remains a significant barrier to their intracellular targets. Conjugation to cell penetrating peptides like pTat48-60 (tat) and pAntp43-68 (penetratin) facilitates delivery, however delivery efficiencies remain low. Improving the performance of known cell penetrating peptides by rational design is hindered by the lack of explicit design principles. Instead, here we use synthetic molecular evolution to generate and screen a cell penetrating peptide library containing 8,192 tat/penetratin hybrid peptides to identify sequences with improved ability to deliver a splice correcting PNA sequence. The parent sequences poorly deliver PNA to cells; however, at 5M peptide-PNA, the top performing PNA conjugated Delivery Peptide (PDEP) daughter sequence showed an 80-fold increase over PNA only treated cells in properly spliced luciferase mRNA and 33-fold higher standardized luminescence values than the top performing parent sequence penetratin. The PDEPs identified in this study are effective in multiple cell types, and also deliver a peptide cargo to cells. The capabilities of the PDEPs make them a valuable research tool for delivery of membrane impermeable PNA or peptide sequences. This dramatic improvement in performance following a single iteration of synthetic molecular evolution is an indication of the power of this approach to peptide sequence optimization. / 1 / William Berkeley Kauffman

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