↓ Skip to main content

Computational Protein Design

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

Table of Contents

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

Citations

dimensions_citation
18 Dimensions

Readers on

mendeley
9 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
Modeling Binding Affinity of Pathological Mutations for Computational Protein Design.
Chapter number 6
Book title
Computational Protein Design
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6637-0_6
Pubmed ID
Book ISBNs
978-1-4939-6635-6, 978-1-4939-6637-0
Authors

Miguel Romero-Durana, Chiara Pallara, Fabian Glaser, Juan Fernández-Recio

Editors

Ilan Samish

Abstract

An important aspect of protein functionality is the formation of specific complexes with other proteins, which are involved in the majority of biological processes. The functional characterization of such interactions at molecular level is necessary, not only to understand biological and pathological phenomena but also to design improved, or even new interfaces, or to develop new therapeutic approaches. X-ray crystallography and NMR spectroscopy have increased the number of 3D protein complex structures deposited in the Protein Data Bank (PDB). However, one of the more challenging objectives in biological research is to functionally characterize protein interactions and thus identify residues that significantly contribute to the binding. Considering that the experimental characterization of protein interfaces remains expensive, time-consuming, and labor-intensive, computational approaches represent a significant breakthrough in proteomics, assisting or even replacing experimental efforts. Thanks to the technological advances in computing and data processing, these techniques now cover a vast range of protocols, from the estimation of the evolutionary conservation of amino acid positions in a protein, to the energetic contribution of each residue to the binding affinity. In this chapter, we review several existing computational protocols to model the phylogenetic, structural, and energetic properties of residues within protein-protein interfaces.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 22%
Student > Bachelor 1 11%
Student > Doctoral Student 1 11%
Student > Ph. D. Student 1 11%
Professor 1 11%
Other 0 0%
Unknown 3 33%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 1 11%
Biochemistry, Genetics and Molecular Biology 1 11%
Computer Science 1 11%
Immunology and Microbiology 1 11%
Chemistry 1 11%
Other 0 0%
Unknown 4 44%