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Cell-penetrating peptide (CPP) based transfection systems (PBTS) are a promising class of drug delivery vectors. CPPs are short mainly cationic peptides capable of delivering cell non-permeant cargo to the interior of the cell. Some CPPs have the ability to form non-covalent complexes with oligonucleotides for gene therapy applications. In this study, we use quantitative structure-activity relationships (QSAR) , a statistical method based on regression data analysis. Here, an fragment QSAR (FQSAR) model is developed to predict new peptides based on standard alpha helical conformers and Assisted Model Building with Energy Refinement molecular mechanics simulations of previous peptides. These new peptides were examined for plasmid transfection efficiency and compared with their predicted biological activity. The best predicted peptides were capable of achieving plasmid transfection with significant improvement compared to the previous generation of peptides. Our results demonstrate that FQSAR model refinement is an efficient method for optimizing PBTS for improved biological activity. [ABSTRACT FROM AUTHOR]

Delivery of pharmaceutical agents across a blood-brain barrier (BBB) is a challenge for brain cancer therapy. In this study, an in vitro BBB model was utilized to study the delivery of oligonucleotides across brain endothelial cells targeting to glioma cells in a Transwell™ setup. A series of novel peptides were synthesized by covalent conjugation of cell-penetrating peptides with targeting peptides for delivery of gene-based therapeutics. These peptides were screened for passage across the Transwell™ and we found the most efficient peptide PepFect32 from originating PepFect 14 coupled with the targeting peptide angiopep-2. PepFect32/pDNA nanocomplexes exhibited high transcytosis across the BBB in vitro model and the highest transfection efficiency to glioma cells. In conclusion, PepFect32 revealed the most efficient peptide-based vector for pDNA delivery across in vitro BBB model. [ABSTRACT FROM AUTHOR]