Dataset for: Curved or linear: Predicting the 3-dimensional structure of α-helical antimicrobial peptides in an amphipathic environment
datasetposted on 03.12.2019 by Glen van den Bergen, Martin Stroet, Bertrand Caron, David Poger, Alan E. Mark
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
α-Helical membrane-active antimicrobial peptides (AMPs) are known to act via a range of mechanisms including the formation of barrel-stave and toroidal pores, and the micellisation of the membrane (carpet mechanism). Different mechanisms imply the peptides adopt different 3D-structures when bound at the water-membrane interface, a highly amphipathic environment. Here an evolutionary algorithm is used to predict the 3D-structure of a range of α-helical membrane-active AMPs at the water-membrane interface by optimising amphipathicity. This amphipathic structure prediction (ASP) is capable of distinguishing between curved and linear peptides solved experimentally, potentially allowing the activity and mechanism of action of different membrane-active AMPs to be predicted. The ASP algorithm is accessible via a web interface at http://atb.uq.edu.au/asp/.