Glutton: a tool for generating structural ensembles of partly disordered proteins from chemical shifts.


Journal

Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944

Informations de publication

Date de publication:
01 04 2019
Historique:
received: 19 03 2018
revised: 15 07 2018
accepted: 03 09 2018
pubmed: 6 9 2018
medline: 13 2 2020
entrez: 6 9 2018
Statut: ppublish

Résumé

Many proteins are partially disordered in physiological conditions and only fold, fully or partially, upon binding. Their structural analysis is challenging because the accessible information, typically chemical shifts (CS) from nuclear magnetic resonance experiments, are averages over broad ensembles of conformations. We aim to develop a database for the analysis of such data in terms of conformational distributions of the protein backbone rather than of individual high-resolution structures. Glutton is the largest available database linking CS and protein 3D structures (5270 entries organized in three levels) and is searchable via a python script. It generates statistical distributions of ϕ-ψ dihedral angles based on CS or vice versa. Such ϕ-ψ distributions are used to calculate structural ensembles of partially disordered proteins from their CS. For folded proteins, such ensembles are excellent starting points for further refinement with additional experimental restraints (structure determination) or computational methods (structure prediction). Glutton is freely available at https://github.com/YeeHo/Glutton. Supplementary data are available at Bioinformatics online.

Identifiants

pubmed: 30184055
pii: 5090450
doi: 10.1093/bioinformatics/bty755
doi:

Substances chimiques

Proteins 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

1234-1236

Informations de copyright

© The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Auteurs

Yi He (Y)

Department of Bioengineering, University of California Merced, Merced, CA, USA.

Suhani Nagpal (S)

Department of Bioengineering, University of California Merced, Merced, CA, USA.

Mourad Sadqi (M)

Department of Bioengineering, University of California Merced, Merced, CA, USA.

Eva de Alba (E)

Department of Bioengineering, University of California Merced, Merced, CA, USA.

Victor Muñoz (V)

Department of Bioengineering, University of California Merced, Merced, CA, USA.
IMDEA Nanoscience, Nanobiosystems Program, Madrid, Spain.

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