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Protein Dynamics

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Cover of 'Protein Dynamics'

Table of Contents

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    Book Overview
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    Chapter 1 Monitoring Side-Chain Dynamics of Proteins Using 2 H Relaxation
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    Chapter 2 CPMG Relaxation Dispersion
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    Chapter 3 Confocal Single-Molecule FRET for Protein Conformational Dynamics
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    Chapter 4 Protein Structural Dynamics Revealed by Site-Directed Spin Labeling and Multifrequency EPR
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    Chapter 5 Probing Backbone Dynamics with Hydrogen/Deuterium Exchange Mass Spectrometry
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    Chapter 6 Carbon–Deuterium Bonds as Non-perturbative Infrared Probes of Protein Dynamics, Electrostatics, Heterogeneity, and Folding
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    Chapter 7 Balancing Bond, Nonbond, and Gō-Like Terms in Coarse Grain Simulations of Conformational Dynamics
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    Chapter 8 A Tutorial on Building Markov State Models with MSMBuilder and Coarse-Graining Them with BACE
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    Chapter 9 Analysis of Protein Conformational Transitions Using Elastic Network Model
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    Chapter 10 Geometric Simulation of Flexible Motion in Proteins
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    Chapter 11 Principal Component Analysis: A Method for Determining the Essential Dynamics of Proteins
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    Chapter 12 A Case Study Comparing Quantitative Stability-Flexibility Relationships Across Five Metallo-β-Lactamases Highlighting Differences Within NDM-1.
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    Chapter 13 Towards Comprehensive Analysis of Protein Family Quantitative Stability–Flexibility Relationships Using Homology Models
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    Chapter 14 Using the COREX/BEST Server to Model the Native-State Ensemble
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    Chapter 15 Morphing Methods to Visualize Coarse-Grained Protein Dynamics
Attention for Chapter 12: A Case Study Comparing Quantitative Stability-Flexibility Relationships Across Five Metallo-β-Lactamases Highlighting Differences Within NDM-1.
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Chapter title
A Case Study Comparing Quantitative Stability-Flexibility Relationships Across Five Metallo-β-Lactamases Highlighting Differences Within NDM-1.
Chapter number 12
Book title
Protein Dynamics
Published in
Methods in molecular biology, January 2014
DOI 10.1007/978-1-62703-658-0_12
Pubmed ID
Book ISBNs
978-1-62703-657-3, 978-1-62703-658-0
Authors

Matthew C Brown, Deeptak Verma, Christian Russell, Donald J Jacobs, Dennis R Livesay, Matthew C. Brown, Donald J. Jacobs, Dennis R. Livesay, Brown, Matthew C., Verma, Deeptak, Russell, Christian, Jacobs, Donald J., Livesay, Dennis R.

Abstract

The Distance Constraint Model (DCM) is an ensemble-based biophysical model that integrates thermodynamic and mechanical viewpoints of protein structure. The DCM outputs a large number of structural characterizations that collectively allow for Quantified Stability-Flexibility Relationships (QSFR) to be identified and compared across protein families. Using five metallo-β-lactamases (MBLs) as a representative set, we demonstrate how QSFR properties are both conserved and varied across protein families. Similar to our characterizations on other protein families, the backbone flexibility of the five MBLs are overall visually conserved, yet there are interesting specific quantitative differences. For example, the plasmid-encoded NDM-1 enzyme, which leads to a fast spreading drug-resistant version of Klebsiella pneumoniae, has several regions of significantly increased rigidity relative to the other four. In addition, the set of intramolecular couplings within NDM-1 are also atypical. While long-range couplings frequently vary significantly across protein families, NDM-1 is distinct because it has limited correlated flexibility, which is isolated within the active site S3/S4 and S11/H6 loops. These loops are flexibly correlated in the other members, suggesting it is important to function, but the others also have significant amounts of correlated flexibility throughout the rest of their structures.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 8%
Unknown 11 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 42%
Student > Ph. D. Student 3 25%
Student > Master 2 17%
Professor > Associate Professor 1 8%
Unknown 1 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 50%
Biochemistry, Genetics and Molecular Biology 4 33%
Medicine and Dentistry 1 8%
Unknown 1 8%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 September 2013.
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#18,348,542
of 22,723,682 outputs
Outputs from Methods in molecular biology
#7,857
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Outputs of similar age
#229,267
of 305,156 outputs
Outputs of similar age from Methods in molecular biology
#293
of 594 outputs
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