Structural Consequences of Disease-Related Mutations for Protein-Protein Interactions
Mutation of a single amino acid in a protein often has consequences on the interaction with other proteins, which may affect other interaction networks and pathways and ultimately lead to pathological phenotypes. A detailed structural analysis of these altered protein–protein complexes is essential to interpret the impact of a given mutation at the molecular level, which may facilitate intervention with therapeutic purposes. Given current limitations in the structural coverage of the human interactome, computational docking is emerging as a complementary source of information. Structural analysis can help to locate a given mutation at a protein–protein interface, but further characterisation of its impact on binding affinity is needed for a full interpretation. The integration of computational docking methods and energy‐based descriptors is facilitating the characterisation of an increasing number of disease‐related mutations, thus improving our understanding of the consequences of such mutations at the phenotypic level.
Main Authors: | , |
---|---|
Format: | capítulo de libro biblioteca |
Published: |
John Wiley & Sons
2020-05-16
|
Subjects: | Protein–protein interactions, Single amino acid variants, Structural bioinformatics, Computational docking, Interface prediction, Binding affinity change, |
Online Access: | http://hdl.handle.net/10261/235838 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
dig-icvv-es-10261-235838 |
---|---|
record_format |
koha |
spelling |
dig-icvv-es-10261-2358382021-03-26T02:10:15Z Structural Consequences of Disease-Related Mutations for Protein-Protein Interactions Rosell, Mireia Fernández-Recio, Juan Protein–protein interactions Single amino acid variants Structural bioinformatics Computational docking Interface prediction Binding affinity change Mutation of a single amino acid in a protein often has consequences on the interaction with other proteins, which may affect other interaction networks and pathways and ultimately lead to pathological phenotypes. A detailed structural analysis of these altered protein–protein complexes is essential to interpret the impact of a given mutation at the molecular level, which may facilitate intervention with therapeutic purposes. Given current limitations in the structural coverage of the human interactome, computational docking is emerging as a complementary source of information. Structural analysis can help to locate a given mutation at a protein–protein interface, but further characterisation of its impact on binding affinity is needed for a full interpretation. The integration of computational docking methods and energy‐based descriptors is facilitating the characterisation of an increasing number of disease‐related mutations, thus improving our understanding of the consequences of such mutations at the phenotypic level. 2021-03-25T12:10:10Z 2021-03-25T12:10:10Z 2020-05-16 2021-03-25T12:10:11Z capítulo de libro http://purl.org/coar/resource_type/c_3248 doi: 10.1002/047001590X isbn: 9780470015902 Encyclopedia of Life Sciences (eLS): 1-9 (2020) http://hdl.handle.net/10261/235838 10.1002/047001590X http://dx.doi.org/10.1002/047001590X Sí none John Wiley & Sons |
institution |
ICVV ES |
collection |
DSpace |
country |
España |
countrycode |
ES |
component |
Bibliográfico |
access |
En linea |
databasecode |
dig-icvv-es |
tag |
biblioteca |
region |
Europa del Sur |
libraryname |
Biblioteca del ICVV España |
topic |
Protein–protein interactions Single amino acid variants Structural bioinformatics Computational docking Interface prediction Binding affinity change Protein–protein interactions Single amino acid variants Structural bioinformatics Computational docking Interface prediction Binding affinity change |
spellingShingle |
Protein–protein interactions Single amino acid variants Structural bioinformatics Computational docking Interface prediction Binding affinity change Protein–protein interactions Single amino acid variants Structural bioinformatics Computational docking Interface prediction Binding affinity change Rosell, Mireia Fernández-Recio, Juan Structural Consequences of Disease-Related Mutations for Protein-Protein Interactions |
description |
Mutation of a single amino acid in a protein often has consequences on the interaction with other proteins, which may affect other interaction networks and pathways and ultimately lead to pathological phenotypes. A detailed structural analysis of these altered protein–protein complexes is essential to interpret the impact of a given mutation at the molecular level, which may facilitate intervention with therapeutic purposes. Given current limitations in the structural coverage of the human interactome, computational docking is emerging as a complementary source of information. Structural analysis can help to locate a given mutation at a protein–protein interface, but further characterisation of its impact on binding affinity is needed for a full interpretation. The integration of computational docking methods and energy‐based descriptors is facilitating the characterisation of an increasing number of disease‐related mutations, thus improving our understanding of the consequences of such mutations at the phenotypic level. |
format |
capítulo de libro |
topic_facet |
Protein–protein interactions Single amino acid variants Structural bioinformatics Computational docking Interface prediction Binding affinity change |
author |
Rosell, Mireia Fernández-Recio, Juan |
author_facet |
Rosell, Mireia Fernández-Recio, Juan |
author_sort |
Rosell, Mireia |
title |
Structural Consequences of Disease-Related Mutations for Protein-Protein Interactions |
title_short |
Structural Consequences of Disease-Related Mutations for Protein-Protein Interactions |
title_full |
Structural Consequences of Disease-Related Mutations for Protein-Protein Interactions |
title_fullStr |
Structural Consequences of Disease-Related Mutations for Protein-Protein Interactions |
title_full_unstemmed |
Structural Consequences of Disease-Related Mutations for Protein-Protein Interactions |
title_sort |
structural consequences of disease-related mutations for protein-protein interactions |
publisher |
John Wiley & Sons |
publishDate |
2020-05-16 |
url |
http://hdl.handle.net/10261/235838 |
work_keys_str_mv |
AT rosellmireia structuralconsequencesofdiseaserelatedmutationsforproteinproteininteractions AT fernandezreciojuan structuralconsequencesofdiseaserelatedmutationsforproteinproteininteractions |
_version_ |
1777671012241899520 |