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 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.Author summary: Chemical and electrical synapses connect neurons in the brain. In chemical synapses the information is sent via molecules from one neuron (presynaptic one) to the other neuron (postsynaptic one). The messenger molecule called neurotransmitter is released from the presynaptic neuron’s active zone and binds to receptor molecules sitting on the postsynaptic neuron’s cell surface. This part of the postsynaptic neuron is the dendrite. Inside the dendrite there is an electron dense region full of proteins binding to each other forming large protein complexes. These complexes make sure that the receptor molecules are on the right place usually in front of the active zone. The protein dense region of the postsynaptic cell in the dendrites is called the postsynaptic density. We have performed extensive simulations on the formation of postsynaptic protein complexes using a well-defined set of proteins and a large number of publicly available input data sets on protein abundance. We used a simulator implementing the Gillespie algorithm to simulate binding and unbinding events proteins. We found that the relationship between single protein and protein complex abundances can be non-trivial, since similar complex distributions can emerge from distinct relative protein abundances and quite different protein complexes can be formed from almost similar initial protein abundances. Our results are compatible with the idea that the association-dissociation of smaller subcomplexes lead to the formation of large supercomplexes. The emergence of supercomplexes is largely facilitated by the self-association of Homer1 and Shank3 proteins. Our results are qualitatively in agreement with the formation of the experimentally observed ‘nanodomains’ in the postsynaptic density.