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Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Protein-protein Interfaces

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...

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Protein Complexes with Interchangeable Parts

Protein Complexes with Interchangeable Parts

Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
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Protein Complexes with Interchangeable Parts

Protein Complexes with Interchangeable Parts

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Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry

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Identifying protein complexes in PPI network using non-cooperative sequential game.

Ujjwal Maulik¹, Srinka Basu², Sumanta Ray³

¹Department of Computer Science and Engineering, Jadavpur University, Kolkata, 700108, India.

Scientific Reports

|August 23, 2017

Summary

This summary is machine-generated.

This study introduces a novel game theory model for identifying protein complexes within protein-protein interaction networks. The approach identifies dense subgraphs, revealing cellular mechanisms and protein complex structures.

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Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

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Area of Science:

Computational biology
Systems biology
Network science

Background:

Protein complexes are crucial for cellular mechanisms.
Identifying protein complexes from protein-protein interaction (PPI) networks is challenging.
Existing methods may not fully capture the complex formation dynamics.

Purpose of the Study:

To propose a novel computational model for protein complex detection.
To leverage game theory to understand protein complex formation.
To identify dense subgraphs representing protein complexes in PPI networks.

Main Methods:

Developed a noncooperative sequential game model.
Hypothesized that complex formation optimizes internal interactions, forming dense subgraphs.
Proposed an algorithm to find the Nash equilibrium of the game.

Main Results:

The Nash equilibrium corresponds to a network partition into complexes or singleton clusters.
The model effectively identifies protein complexes in both synthetic and real yeast networks.
Evaluated the structural and biological significance of the detected partitions.

Conclusions:

Game theory provides a powerful framework for protein complex detection.
The proposed model accurately identifies biologically relevant protein complexes.
This approach enhances understanding of cellular mechanisms through PPI network analysis.