Cargando…

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

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 availa...

Descripción completa

Detalles Bibliográficos
Autores principales: Koehler Leman, Julia, Lyskov, Sergey, Bonneau, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5319049/
https://www.ncbi.nlm.nih.gov/pubmed/28219343
http://dx.doi.org/10.1186/s12859-017-1541-z
_version_ 1782509305797279744
author Koehler Leman, Julia
Lyskov, Sergey
Bonneau, Richard
author_facet Koehler Leman, Julia
Lyskov, Sergey
Bonneau, Richard
author_sort Koehler Leman, Julia
collection PubMed
description 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/submit and the benchmark dataset is available at http://tinyurl.com/mp-lipid-acc-dataset. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1541-z) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-5319049
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-53190492017-02-24 Computing structure-based lipid accessibility of membrane proteins with mp_lipid_acc in RosettaMP Koehler Leman, Julia Lyskov, Sergey Bonneau, Richard BMC Bioinformatics Software 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/submit and the benchmark dataset is available at http://tinyurl.com/mp-lipid-acc-dataset. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1541-z) contains supplementary material, which is available to authorized users. BioMed Central 2017-02-20 /pmc/articles/PMC5319049/ /pubmed/28219343 http://dx.doi.org/10.1186/s12859-017-1541-z Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Koehler Leman, Julia
Lyskov, Sergey
Bonneau, Richard
Computing structure-based lipid accessibility of membrane proteins with mp_lipid_acc in RosettaMP
title Computing structure-based lipid accessibility of membrane proteins with mp_lipid_acc in RosettaMP
title_full Computing structure-based lipid accessibility of membrane proteins with mp_lipid_acc in RosettaMP
title_fullStr Computing structure-based lipid accessibility of membrane proteins with mp_lipid_acc in RosettaMP
title_full_unstemmed Computing structure-based lipid accessibility of membrane proteins with mp_lipid_acc in RosettaMP
title_short Computing structure-based lipid accessibility of membrane proteins with mp_lipid_acc in RosettaMP
title_sort computing structure-based lipid accessibility of membrane proteins with mp_lipid_acc in rosettamp
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5319049/
https://www.ncbi.nlm.nih.gov/pubmed/28219343
http://dx.doi.org/10.1186/s12859-017-1541-z
work_keys_str_mv AT koehlerlemanjulia computingstructurebasedlipidaccessibilityofmembraneproteinswithmplipidaccinrosettamp
AT lyskovsergey computingstructurebasedlipidaccessibilityofmembraneproteinswithmplipidaccinrosettamp
AT bonneaurichard computingstructurebasedlipidaccessibilityofmembraneproteinswithmplipidaccinrosettamp