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...

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Veröffentlicht in:PLoS computational biology 2022-01, Vol.18 (1), p.e1009758
Hauptverfasser: Miski, Marcell, Keömley-Horváth, Bence Márk, Rákóczi Megyeriné, Dorina, Csikász-Nagy, Attila, Gáspári, Zoltán
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Rákóczi Megyeriné, Dorina
Csikász-Nagy, Attila
Gáspári, Zoltán
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.
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source MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Public Library of Science (PLoS)
subjects Algorithms
Association reactions
Availability
Binding sites
Biology and Life Sciences
Brain
Circadian rhythms
Complex formation
Computer Simulation
Constituents
Data processing
Experimental methods
Gene expression
Glutamate receptors
Glutamic acid receptors
Humans
Information processing
Kinases
Medicine and Health Sciences
Models, Neurological
N-Methyl-D-aspartic acid receptors
Nerve Tissue Proteins - chemistry
Nerve Tissue Proteins - metabolism
Neurological diseases
Observations
Permeability
Physical Sciences
Post-Synaptic Density - metabolism
Post-Synaptic Density - physiology
Postsynapse
Postsynaptic density
Postsynaptic density proteins
Protein-protein interactions
Proteins
Research and Analysis Methods
Research methodology
Self-association
Simulation
Stochasticity
Synapses - chemistry
Synapses - metabolism
α-Amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptors
title Diversity of synaptic protein complexes as a function of the abundance of their constituent proteins: A modeling approach
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