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Computational Protein Design

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

Table of Contents

  1. Altmetric Badge
    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 18: Probing Oligomerized Conformations of Defensin in the Membrane.
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Chapter title
Probing Oligomerized Conformations of Defensin in the Membrane.
Chapter number 18
Book title
Computational Protein Design
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6637-0_18
Pubmed ID
27914061
Book ISBNs
978-1-4939-6635-6, 978-1-4939-6637-0
Authors

Wenxun Gan, Dina Schneidman, Ning Zhang, Buyong Ma, Ruth Nussinov

Editors

Ilan Samish

Abstract

Computational prediction and design of membrane protein-protein interactions facilitate biomedical engineering and biotechnological applications. Due to their antimicrobial activity, human defensins play an important role in the innate immune system. Human defensins are attractive pharmaceutical targets due to their small size, broad activity spectrum, reduced immunogenicity, and resistance to proteolysis. Protein engineering based modification of defensins can improve their pharmaceutical properties. Here we present an approach to computationally probe defensins' oligomerization states in the membrane. First, we develop a novel docking and rescoring algorithm. Then, on the basis of the 3D structure of Sapecin, an insect defensin, and a model of its antimicrobial ion-channel, we optimize the parameters of our empirical scoring function. Finally, we apply our docking program and scoring function to the hBD-2 (human β-defensin-2) molecule and obtain structures of four possible oligomers. These results can be used in higher level simulations.

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Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 30%
Lecturer > Senior Lecturer 1 10%
Student > Bachelor 1 10%
Other 1 10%
Student > Master 1 10%
Other 1 10%
Unknown 2 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 30%
Immunology and Microbiology 1 10%
Medicine and Dentistry 1 10%
Unknown 5 50%

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 13 January 2018.
All research outputs
#15,398,970
of 22,908,162 outputs
Outputs from Methods in molecular biology
#5,357
of 13,132 outputs
Outputs of similar age
#256,356
of 420,477 outputs
Outputs of similar age from Methods in molecular biology
#465
of 1,074 outputs
Altmetric has tracked 22,908,162 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,132 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
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We're also able to compare this research output to 1,074 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.

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