Cargando…
Geometric description of self-interaction potential in symmetric protein complexes
Proteins can self-associate with copies of themselves to form symmetric complexes called homomers. Homomers are widespread in all kingdoms of life and allow for unique geometric and functional properties, as reflected in viral capsids or allostery. Once a protein forms a homomer, however, its intern...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525250/ https://www.ncbi.nlm.nih.gov/pubmed/31101822 http://dx.doi.org/10.1038/s41597-019-0058-x |
_version_ | 1783419688395472896 |
---|---|
author | Empereur-Mot, Charly Garcia-Seisdedos, Hector Elad, Nadav Dey, Sucharita Levy, Emmanuel D. |
author_facet | Empereur-Mot, Charly Garcia-Seisdedos, Hector Elad, Nadav Dey, Sucharita Levy, Emmanuel D. |
author_sort | Empereur-Mot, Charly |
collection | PubMed |
description | Proteins can self-associate with copies of themselves to form symmetric complexes called homomers. Homomers are widespread in all kingdoms of life and allow for unique geometric and functional properties, as reflected in viral capsids or allostery. Once a protein forms a homomer, however, its internal symmetry can compound the effect of point mutations and trigger uncontrolled self-assembly into high-order structures. We identified mutation hot spots for supramolecular assembly, which are predictable by geometry. Here, we present a dataset of descriptors that characterize these hot spot positions both geometrically and chemically, as well as computer scripts allowing the calculation and visualization of these properties for homomers of choice. Since the biological relevance of homomers is not readily available from their X-ray crystallographic structure, we also provide reliability estimates obtained by methods we recently developed. These data have implications in the study of disease-causing mutations, protein evolution and can be exploited in the design of biomaterials. |
format | Online Article Text |
id | pubmed-6525250 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-65252502019-05-20 Geometric description of self-interaction potential in symmetric protein complexes Empereur-Mot, Charly Garcia-Seisdedos, Hector Elad, Nadav Dey, Sucharita Levy, Emmanuel D. Sci Data Data Descriptor Proteins can self-associate with copies of themselves to form symmetric complexes called homomers. Homomers are widespread in all kingdoms of life and allow for unique geometric and functional properties, as reflected in viral capsids or allostery. Once a protein forms a homomer, however, its internal symmetry can compound the effect of point mutations and trigger uncontrolled self-assembly into high-order structures. We identified mutation hot spots for supramolecular assembly, which are predictable by geometry. Here, we present a dataset of descriptors that characterize these hot spot positions both geometrically and chemically, as well as computer scripts allowing the calculation and visualization of these properties for homomers of choice. Since the biological relevance of homomers is not readily available from their X-ray crystallographic structure, we also provide reliability estimates obtained by methods we recently developed. These data have implications in the study of disease-causing mutations, protein evolution and can be exploited in the design of biomaterials. Nature Publishing Group UK 2019-05-17 /pmc/articles/PMC6525250/ /pubmed/31101822 http://dx.doi.org/10.1038/s41597-019-0058-x Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Empereur-Mot, Charly Garcia-Seisdedos, Hector Elad, Nadav Dey, Sucharita Levy, Emmanuel D. Geometric description of self-interaction potential in symmetric protein complexes |
title | Geometric description of self-interaction potential in symmetric protein complexes |
title_full | Geometric description of self-interaction potential in symmetric protein complexes |
title_fullStr | Geometric description of self-interaction potential in symmetric protein complexes |
title_full_unstemmed | Geometric description of self-interaction potential in symmetric protein complexes |
title_short | Geometric description of self-interaction potential in symmetric protein complexes |
title_sort | geometric description of self-interaction potential in symmetric protein complexes |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525250/ https://www.ncbi.nlm.nih.gov/pubmed/31101822 http://dx.doi.org/10.1038/s41597-019-0058-x |
work_keys_str_mv | AT empereurmotcharly geometricdescriptionofselfinteractionpotentialinsymmetricproteincomplexes AT garciaseisdedoshector geometricdescriptionofselfinteractionpotentialinsymmetricproteincomplexes AT eladnadav geometricdescriptionofselfinteractionpotentialinsymmetricproteincomplexes AT deysucharita geometricdescriptionofselfinteractionpotentialinsymmetricproteincomplexes AT levyemmanueld geometricdescriptionofselfinteractionpotentialinsymmetricproteincomplexes |