Computing structure-based lipid accessibility of membrane proteins with mp_lipid_acc in RosettaMP

Julia Koehler Leman, Sergey Lyskov, Richard Bonneau

Research output: Contribution to journalArticle

Abstract

Background: Membrane proteins are underrepresented in structural databases, which has led to a lack of computational tools and the corresponding inappropriate use of tools designed for soluble proteins. For membrane proteins, lipid accessibility is an essential property. Although programs are available for sequence-based prediction of lipid accessibility and structure-based identification of solvent-accessible surface area, the latter does not distinguish between water accessible and lipid accessible residues in membrane proteins. Results: Here we present mp_lipid_acc, the first method to identify lipid accessible residues from the protein structure, implemented in the RosettaMP framework and available as a webserver. Our method uses protein structures transformed in membrane coordinates, for instance from PDBTM or OPM databases, and a defined membrane thickness to classify lipid accessibility of residues. mp_lipid_acc is applicable to both α-helical and β-barrel membrane proteins of diverse architectures with or without water-filled pores and uses a concave hull algorithm for surface-residue classification. We further provide a manually curated benchmark dataset that can be used for further method development. Conclusions: We present a novel tool to classify lipid accessibility from the protein structure, which is applicable to proteins of diverse architectures and achieves prediction accuracies of 90% on a manually curated database. mp_lipid_acc is part of the Rosetta software suite, available at www.rosettacommons.org. The webserver is available at http://rosie.graylab.jhu.edu/mp_lipid_acc/submitand the benchmark dataset is available at http://tinyurl.com/mp-lipid-acc-dataset.

Original languageEnglish (US)
Article number115
JournalBMC bioinformatics
Volume18
Issue number1
DOIs
StatePublished - Feb 20 2017

Keywords

  • Accessible surface area
  • Lipid accessibility
  • Membrane proteins
  • Rosetta software
  • Structure prediction

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics

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