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Computational Protein Design

Overview of attention for book
Cover of 'Computational Protein Design'

Table of Contents

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    Book Overview
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    Chapter 1 The Framework of Computational Protein Design.
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    Chapter 2 Achievements and Challenges in Computational Protein Design.
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    Chapter 3 Production of Computationally Designed Small Soluble- and Membrane-Proteins: Cloning, Expression, and Purification.
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    Chapter 4 Deterministic Search Methods for Computational Protein Design.
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    Chapter 5 Geometric Potentials for Computational Protein Sequence Design.
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    Chapter 6 Modeling Binding Affinity of Pathological Mutations for Computational Protein Design.
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    Chapter 7 Multistate Computational Protein Design with Backbone Ensembles.
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    Chapter 8 Integration of Molecular Dynamics Based Predictions into the Optimization of De Novo Protein Designs: Limitations and Benefits.
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    Chapter 9 Applications of Normal Mode Analysis Methods in Computational Protein Design.
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    Chapter 10 Computational Protein Design Under a Given Backbone Structure with the ABACUS Statistical Energy Function.
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    Chapter 11 Computational Protein Design Through Grafting and Stabilization.
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    Chapter 12 An Evolution-Based Approach to De Novo Protein Design.
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    Chapter 13 Parallel Computational Protein Design.
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    Chapter 14 Computational Protein Design
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    Chapter 15 OSPREY Predicts Resistance Mutations Using Positive and Negative Computational Protein Design.
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    Chapter 16 Evolution-Inspired Computational Design of Symmetric Proteins.
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    Chapter 17 A Protocol for the Design of Protein and Peptide Nanostructure Self-Assemblies Exploiting Synthetic Amino Acids.
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    Chapter 18 Probing Oligomerized Conformations of Defensin in the Membrane.
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    Chapter 19 Computational Design of Ligand Binding Proteins.
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    Chapter 20 EpiSweep: Computationally Driven Reengineering of Therapeutic Proteins to Reduce Immunogenicity While Maintaining Function.
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    Chapter 21 Computational Tools for Aiding Rational Antibody Design.
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    Chapter 22 Computational Design of Membrane Curvature-Sensing Peptides.
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    Chapter 23 Computational Tools for Allosteric Drug Discovery: Site Identification and Focus Library Design.
Attention for Chapter 9: Applications of Normal Mode Analysis Methods in Computational Protein Design.
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Chapter title
Applications of Normal Mode Analysis Methods in Computational Protein Design.
Chapter number 9
Book title
Computational Protein Design
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6637-0_9
Pubmed ID
27914052
Book ISBNs
978-1-4939-6635-6, 978-1-4939-6637-0
Authors

Vincent Frappier, Matthieu Chartier, Rafael Najmanovich

Editors

Ilan Samish

Abstract

Recent advances in coarse-grained normal mode analysis methods make possible the large-scale prediction of the effect of mutations on protein stability and dynamics as well as the generation of biologically relevant conformational ensembles. Given the interplay between flexibility and enzymatic activity, the combined analysis of stability and dynamics using the Elastic Network Contact Model (ENCoM) method has ample applications in protein engineering in industrial and medical applications such as in computational antibody design. Here, we present a detailed tutorial on how to perform such calculations using ENCoM.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 14%
Student > Master 2 14%
Student > Bachelor 1 7%
Professor 1 7%
Student > Doctoral Student 1 7%
Other 3 21%
Unknown 4 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 36%
Pharmacology, Toxicology and Pharmaceutical Science 2 14%
Agricultural and Biological Sciences 2 14%
Unknown 5 36%

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