Computational Prediction of Amino Acids Governing Protein-Membrane Interaction for the PIP3 Cell Signaling System.

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dc.contributor.author Irvine, William A en
dc.contributor.author Flanagan, Jack en
dc.contributor.author Allison, Jane en
dc.date.accessioned 2020-02-11T22:48:27Z en
dc.date.issued 2019-02 en
dc.identifier.issn 0969-2126 en
dc.identifier.uri http://hdl.handle.net/2292/49920 en
dc.description.abstract Prediction and characterization of how transiently membrane-bound signaling proteins interact with the cell membrane is important for understanding and controlling cellular signal transduction networks. Existing computational methods rely on approximate descriptions of the components of the system or their interactions, and thus are unable to identify residue- or lipid-specific contributions. Our rotational interaction energy profiling method allows rapid evaluation of an electrostatically optimal orientation of a protein for membrane association, as well as the residues or lipid species responsible for its favorability. This enables prediction of which aspects of the protein-membrane interaction to target experimentally, and thus the development of testable hypotheses, as well as providing efficient seeding of molecular dynamics simulations to further characterize the protein-membrane interaction. We illustrate our method on two proteins of the PIP3 cell signaling system, PTEN and PI3Kα. en
dc.format.medium Print-Electronic en
dc.language eng en
dc.relation.ispartofseries Structure (London, England : 1993) en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.subject Lipid Bilayers en
dc.subject Phosphatidylinositol Phosphates en
dc.subject Amino Acids en
dc.subject Membrane Proteins en
dc.subject Computational Biology en
dc.subject Signal Transduction en
dc.subject Binding Sites en
dc.subject Protein Binding en
dc.subject Models, Molecular en
dc.subject PTEN Phosphohydrolase en
dc.subject Molecular Dynamics Simulation en
dc.subject Class I Phosphatidylinositol 3-Kinases en
dc.title Computational Prediction of Amino Acids Governing Protein-Membrane Interaction for the PIP3 Cell Signaling System. en
dc.type Journal Article en
dc.identifier.doi 10.1016/j.str.2018.10.014 en
pubs.issue 2 en
pubs.begin-page 371 en
pubs.volume 27 en
dc.rights.holder Copyright: The author en
pubs.end-page 380.e3 en
pubs.publication-status Published en
dc.rights.accessrights http://purl.org/eprint/accessRights/RestrictedAccess en
pubs.subtype Research Support, Non-U.S. Gov't en
pubs.subtype Journal Article en
pubs.elements-id 761320 en
pubs.org-id Medical and Health Sciences en
pubs.org-id Medical Sciences en
pubs.org-id Pharmacology en
pubs.org-id Science en
pubs.org-id Biological Sciences en
pubs.org-id Science Research en
pubs.org-id Maurice Wilkins Centre (2010-2014) en
dc.identifier.eissn 1878-4186 en
pubs.record-created-at-source-date 2018-12-12 en
pubs.dimensions-id 30528597 en


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