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Diversity of synaptic protein complexes as a function of the abundance of their constituent proteins: A modeling approach
The postsynaptic density (PSD) is a dense protein network playing a key role in information processing during learning and memory, and is also indicated in a number of neurological disorders. Efforts to characterize its detailed molecular organization are encumbered by the large variability of the a...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8797218/ https://www.ncbi.nlm.nih.gov/pubmed/35041658 http://dx.doi.org/10.1371/journal.pcbi.1009758 |
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author | Miski, Marcell Keömley-Horváth, Bence Márk Rákóczi Megyeriné, Dorina Csikász-Nagy, Attila Gáspári, Zoltán |
author_facet | Miski, Marcell Keömley-Horváth, Bence Márk Rákóczi Megyeriné, Dorina Csikász-Nagy, Attila Gáspári, Zoltán |
author_sort | Miski, Marcell |
collection | PubMed |
description | The postsynaptic density (PSD) is a dense protein network playing a key role in information processing during learning and memory, and is also indicated in a number of neurological disorders. Efforts to characterize its detailed molecular organization are encumbered by the large variability of the abundance of its constituent proteins both spatially, in different brain areas, and temporally, during development, circadian rhythm, and also in response to various stimuli. In this study we ran large-scale stochastic simulations of protein binding events to predict the presence and distribution of PSD complexes. We simulated the interactions of seven major PSD proteins (NMDAR, AMPAR, PSD-95, SynGAP, GKAP, Shank3, Homer1) based on previously published, experimentally determined protein abundance data from 22 different brain areas and 42 patients (altogether 524 different simulations). Our results demonstrate that the relative ratio of the emerging protein complexes can be sensitive to even subtle changes in protein abundances and thus explicit simulations are invaluable to understand the relationships between protein availability and complex formation. Our observations are compatible with a scenario where larger supercomplexes are formed from available smaller binary and ternary associations of PSD proteins. Specifically, Homer1 and Shank3 self-association reactions substantially promote the emergence of very large protein complexes. The described simulations represent a first approximation to assess PSD complex abundance, and as such, use significant simplifications. Therefore, their direct biological relevance might be limited but we believe that the major qualitative findings can contribute to the understanding of the molecular features of the postsynapse. |
format | Online Article Text |
id | pubmed-8797218 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-87972182022-01-29 Diversity of synaptic protein complexes as a function of the abundance of their constituent proteins: A modeling approach Miski, Marcell Keömley-Horváth, Bence Márk Rákóczi Megyeriné, Dorina Csikász-Nagy, Attila Gáspári, Zoltán PLoS Comput Biol Research Article The postsynaptic density (PSD) is a dense protein network playing a key role in information processing during learning and memory, and is also indicated in a number of neurological disorders. Efforts to characterize its detailed molecular organization are encumbered by the large variability of the abundance of its constituent proteins both spatially, in different brain areas, and temporally, during development, circadian rhythm, and also in response to various stimuli. In this study we ran large-scale stochastic simulations of protein binding events to predict the presence and distribution of PSD complexes. We simulated the interactions of seven major PSD proteins (NMDAR, AMPAR, PSD-95, SynGAP, GKAP, Shank3, Homer1) based on previously published, experimentally determined protein abundance data from 22 different brain areas and 42 patients (altogether 524 different simulations). Our results demonstrate that the relative ratio of the emerging protein complexes can be sensitive to even subtle changes in protein abundances and thus explicit simulations are invaluable to understand the relationships between protein availability and complex formation. Our observations are compatible with a scenario where larger supercomplexes are formed from available smaller binary and ternary associations of PSD proteins. Specifically, Homer1 and Shank3 self-association reactions substantially promote the emergence of very large protein complexes. The described simulations represent a first approximation to assess PSD complex abundance, and as such, use significant simplifications. Therefore, their direct biological relevance might be limited but we believe that the major qualitative findings can contribute to the understanding of the molecular features of the postsynapse. Public Library of Science 2022-01-18 /pmc/articles/PMC8797218/ /pubmed/35041658 http://dx.doi.org/10.1371/journal.pcbi.1009758 Text en © 2022 Miski et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Miski, Marcell Keömley-Horváth, Bence Márk Rákóczi Megyeriné, Dorina Csikász-Nagy, Attila Gáspári, Zoltán Diversity of synaptic protein complexes as a function of the abundance of their constituent proteins: A modeling approach |
title | Diversity of synaptic protein complexes as a function of the abundance of their constituent proteins: A modeling approach |
title_full | Diversity of synaptic protein complexes as a function of the abundance of their constituent proteins: A modeling approach |
title_fullStr | Diversity of synaptic protein complexes as a function of the abundance of their constituent proteins: A modeling approach |
title_full_unstemmed | Diversity of synaptic protein complexes as a function of the abundance of their constituent proteins: A modeling approach |
title_short | Diversity of synaptic protein complexes as a function of the abundance of their constituent proteins: A modeling approach |
title_sort | diversity of synaptic protein complexes as a function of the abundance of their constituent proteins: a modeling approach |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8797218/ https://www.ncbi.nlm.nih.gov/pubmed/35041658 http://dx.doi.org/10.1371/journal.pcbi.1009758 |
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