Development of a membrane curvature-sensing peptide based on a structure–activity correlation study

Abstract

Membrane curvature formation is important for various biological processes such as cell motility, intracellular signal transmission, and cellular uptake of foreign substances. However, it remains still a challenging topic to visualize the membrane curvature formation on the cell membranes in real-time imaging. To develop and design membrane curvature-sensors, we focused on amphipathic helical peptides of proteins belonging to the Bin/Amphiphysin/Rvs (BAR) family as the starting point. BAR proteins individually have various characteristic structures that recognize different curvatures, and the derived peptides possess the potential to function as curvature sensors with a variety of recognition abilities. Peptide-based curvature sensors can have wide applications in biological research fields due to their small size, easy modification, and large production capability in comparison to protein-based sensors. In the present study, we found that an amphipathic peptide derived from sorting nexin1 (SNX1) has a curvature-recognition ability. The mutation studies of the initial peptide revealed a close correlation between the α-helicity and lipid binding ability of the peptides. In particular, the amino acids located on the hydrophobic face played a vital role in curvature recognition. The α-helix formation of the peptides was thought to serve to accommodate lipid-packing defects on the membrane surface and to maintain their binding to lipid vesicles. The structure–activity correlation found in this study have the potential to contribute to the design of peptide-based curvature sensors that will enable the capture of various life phenomena in cells.