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Crosslinking constraints and computational models as complementary tools in modeling the extracellular domain of the glycine receptor

Liu, Z and Szarecka, A and Yonkunas, M and Speranskiy, K and Kurnikova, M and Cascio, M (2014) Crosslinking constraints and computational models as complementary tools in modeling the extracellular domain of the glycine receptor. PLoS ONE, 9 (7).

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Abstract

The glycine receptor (GlyR), a member of the pentameric ligand-gated ion channel superfamily, is the major inhibitory neurotransmitter-gated receptor in the spinal cord and brainstem. In these receptors, the extracellular domain binds agonists, antagonists and various other modulatory ligands that act allosterically to modulate receptor function. The structures of homologous receptors and binding proteins provide templates for modeling of the ligand-binding domain of GlyR, but limitations in sequence homology and structure resolution impact on modeling studies. The determination of distance constraints via chemical crosslinking studies coupled with mass spectrometry can provide additional structural information to aid in model refinement, however it is critical to be able to distinguish between intra- and inter-subunit constraints. In this report we model the structure of GlyBP, a structural and functional homolog of the extracellular domain of human homomeric α1 GlyR. We then show that intra- and intersubunit Lys-Lys crosslinks in trypsinized samples of purified monomeric and oligomeric protein bands from SDS-polyacrylamide gels may be identified and differentiated by MALDI-TOF MS studies of limited resolution. Thus, broadly available MS platforms are capable of providing distance constraints that may be utilized in characterizing large complexes that may be less amenable to NMR and crystallographic studies. Systematic studies of state-dependent chemical crosslinking and mass spectrometric identification of crosslinked sites has the potential to complement computational modeling efforts by providing constraints that can validate and refine allosteric models. © 2014 Liu et al.


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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Liu, Z
Szarecka, A
Yonkunas, M
Speranskiy, K
Kurnikova, M
Cascio, Mcascio@pitt.eduCASCIO
Contributors:
ContributionContributors NameEmailPitt UsernameORCID
EditorBenos, Panayiotis V.benos@pitt.eduBENOSUNSPECIFIED
Centers: Other Centers, Institutes, or Units > Center for Neuroscience
Date: 15 July 2014
Date Type: Publication
Journal or Publication Title: PLoS ONE
Volume: 9
Number: 7
DOI or Unique Handle: 10.1371/journal.pone.0102571
Schools and Programs: Swanson School of Engineering > Materials Science and Engineering
Refereed: Yes
Date Deposited: 26 Sep 2014 17:39
Last Modified: 28 Jan 2018 00:55
URI: http://d-scholarship.pitt.edu/id/eprint/23001

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