4.5 Article

The enhanced membrane interaction and perturbation of a cell penetrating peptide in the presence of anionic lipids: Toward an understanding of its selectivity for cancer cells

期刊

BIOCHIMICA ET BIOPHYSICA ACTA-BIOMEMBRANES
卷 1828, 期 6, 页码 1457-1470

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ELSEVIER
DOI: 10.1016/j.bbamem.2013.02.008

关键词

Cell penetrating peptide; Peptide/lipid interaction; Lipid model system; Anticancer activity

资金

  1. French Ministere de l'Enseignement Superieur et de la Recherche

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Cell penetrating peptides (CPPs) are usually short, highly cationic peptides that are capable of crossing the cell membrane and transport cargos of varied size and nature in cells by energy- and receptor-independent mechanisms. An additional potential is the newly discovered anti-tumor activity of certain CPPs, including RW16 (RRWRRWWRRWWRRWRR) which is derived from penetratin and is investigated here. The use of CPPs in therapeutics, diagnosis and potential application as anti-tumor agents increases the necessity of understanding their mode of action, a subject yet not totally understood. With this in mind, the membrane interaction and perturbation mechanisms of RW16 with both zwitterionic and anionic lipid model systems (used as representative models of healthy vs tumor cells) were investigated using a large panoply of biophysical techniques. It was shown that RW16 autoassociates and that its oligomerization state highly influences its' membrane interaction. Overall a stronger association and perturbation of anionic membranes was observed, especially in the presence of oligomeric peptide, when compared to zwitterionic ones. This might explain, at least in part, the anti-tumor activity and so the selective interaction with cancer cells whose membranes have been shown to be especially anionic. Hydrophobic contacts between the peptide and lipids were also shown to play an important role in the interaction. That probably results from the tryptophan insertion into the fatty acid lipid area following a peptide flip after the first electrostatic recognition. A model is presented that reflects the ensemble of results. (C) 2013 Elsevier B.V. All rights reserved.

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