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Curved or linear? Predicting the 3-dimensional structure of α-helical antimicrobial peptides in an amphipathic environment.

Glen van den BergenMartin StroetBertrand CaronDavid PogerAlan E Mark
Published in: FEBS letters (2019)
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 that 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/.
Keyphrases
  • machine learning
  • gene expression
  • high resolution
  • sensitive detection
  • neural network