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Intrinsically Disordered Proteins Studied by NMR Spectroscopy

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Cover of 'Intrinsically Disordered Proteins Studied by NMR Spectroscopy'

Table of Contents

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    Book Overview
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    Chapter 1 Back to the Future: Nuclear Magnetic Resonance and Bioinformatics Studies on Intrinsically Disordered Proteins.
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    Chapter 2 Structure and Dynamics of Intrinsically Disordered Proteins.
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    Chapter 3 NMR Methods for the Study of Instrinsically Disordered Proteins Structure, Dynamics, and Interactions: General Overview and Practical Guidelines
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    Chapter 4 Ensemble Calculation for Intrinsically Disordered Proteins Using NMR Parameters
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    Chapter 5 NMR Spectroscopic Studies of the Conformational Ensembles of Intrinsically Disordered Proteins.
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    Chapter 6 Recombinant Intrinsically Disordered Proteins for NMR: Tips and Tricks.
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    Chapter 7 Biophysical Methods to Investigate Intrinsically Disordered Proteins: Avoiding an "Elephant and Blind Men" Situation.
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    Chapter 8 Application of SAXS for the Structural Characterization of IDPs
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    Chapter 9 Bioinformatics Approaches for Predicting Disordered Protein Motifs
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    Chapter 10 Towards Understanding Protein Disorder In-Cell
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    Chapter 11 The Protein Ensemble Database
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    Chapter 12 Order and Disorder in the Replicative Complex of Paramyxoviruses.
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    Chapter 13 Druggability of Intrinsically Disordered Proteins.
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    Chapter 14 Beta Amyloid Hallmarks: From Intrinsically Disordered Proteins to Alzheimer's Disease.
Attention for Chapter 11: The Protein Ensemble Database
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Chapter title
The Protein Ensemble Database
Chapter number 11
Book title
Intrinsically Disordered Proteins Studied by NMR Spectroscopy
Published in
Advances in experimental medicine and biology, January 2015
DOI 10.1007/978-3-319-20164-1_11
Pubmed ID
Book ISBNs
978-3-31-920163-4, 978-3-31-920164-1
Authors

Mihaly Varadi, Peter Tompa, Varadi, Mihaly, Tompa, Peter

Abstract

The scientific community's major conceptual notion of structural biology has recently shifted in emphasis from the classical structure-function paradigm due to the emergence of intrinsically disordered proteins (IDPs). As opposed to their folded cousins, these proteins are defined by the lack of a stable 3D fold and a high degree of inherent structural heterogeneity that is closely tied to their function. Due to their flexible nature, solution techniques such as small-angle X-ray scattering (SAXS), nuclear magnetic resonance (NMR) spectroscopy and fluorescence resonance energy transfer (FRET) are particularly well-suited for characterizing their biophysical properties. Computationally derived structural ensembles based on such experimental measurements provide models of the conformational sampling displayed by these proteins, and they may offer valuable insights into the functional consequences of inherent flexibility. The Protein Ensemble Database (http://pedb.vib.be) is the first openly accessible, manually curated online resource storing the ensemble models, protocols used during the calculation procedure, and underlying primary experimental data derived from SAXS and/or NMR measurements. By making this previously inaccessible data freely available to researchers, this novel resource is expected to promote the development of more advanced modelling methodologies, facilitate the design of standardized calculation protocols, and consequently lead to a better understanding of how function arises from the disordered state.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 4%
Unknown 25 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 35%
Student > Ph. D. Student 4 15%
Student > Master 4 15%
Other 2 8%
Student > Bachelor 1 4%
Other 3 12%
Unknown 3 12%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 27%
Agricultural and Biological Sciences 6 23%
Chemistry 5 19%
Physics and Astronomy 3 12%
Computer Science 2 8%
Other 0 0%
Unknown 3 12%