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Proteomics

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...

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Related Experiment Video

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Preparation of Synaptic Plasma Membrane and Postsynaptic Density Proteins Using a Discontinuous Sucrose Gradient

Preparation of Synaptic Plasma Membrane and Postsynaptic Density Proteins Using a Discontinuous Sucrose Gradient

Published on: September 3, 2014

Towards a quantitative model of the post-synaptic proteome.

Oksana Sorokina¹, Anatoly Sorokin, J Douglas Armstrong

¹School of Informatics, University of Edinburgh, Edinburgh, UK. oksana.sorokina@ed.ac.uk

Molecular Biosystems

|August 30, 2011

Summary

This study models protein interactions in the postsynaptic density (PSD) to understand how protein complexes form and influence brain function. The research provides a quantitative view of molecular interactions crucial for cognitive processes.

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Last Updated: May 29, 2026

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Published on: September 3, 2014

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Published on: September 17, 2011

Area of Science:

Neuroscience
Molecular Biology
Computational Biology

Background:

The postsynaptic density (PSD) is crucial for excitatory glutamatergic synapses, containing numerous proteins essential for signaling and cognitive functions.
Protein clustering and domain interactions within the PSD are vital for synaptic signal processing.
Existing protein-protein interaction maps lack quantitative details on stoichiometry and binding properties.

Purpose of the Study:

To develop a quantitative model of protein interactions within the PSD.
To analyze the formation and distribution of protein complexes based on domain structure, affinity, and availability.
To provide a more realistic molecular-level understanding of the postsynaptic proteome.

Main Methods:

Utilized a rule-based modeling approach employing stochastic calculus of domain binding.
Formalized the combinatorial signaling pathways within the PSD.
Performed numerical analysis of protein complex distribution, size, and composition.

Main Results:

Identified critical conditions for protein aggregation into large complexes within the PSD.
Characterized the distribution of protein complex sizes and compositions.
Integrated quantitative data on stoichiometry and binding properties into network analysis.

Conclusions:

The developed model offers a more realistic, quantitative perspective on the postsynaptic proteome.
This approach enhances understanding of how molecular dynamics in the PSD relate to cognitive processes.
The study bridges the gap between qualitative interaction maps and quantitative molecular behavior.