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Related Concept Videos

Protein Complexes with Interchangeable Parts01:57

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.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order to...
Protein Complexes with Interchangeable Parts01:57

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.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order to...
Protein Complex Assembly02:41

Protein Complex Assembly

Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...
Protein Complex Assembly02:41

Protein Complex Assembly

Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...
Protein Networks02:26

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.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Protein Networks02:26

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.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

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A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Refining Markov Clustering for protein complex prediction by incorporating core-attachment structure.

Sriganesh Srihari1, Kang Ning, Hon Wai Leong

  • 1School of Computing, National University of Singapore, Singapore 117590, Singapore. srigsri@comp.nus.edu.sg

Genome Informatics. International Conference on Genome Informatics
|February 25, 2010
PubMed
Summary

This study refines protein complex detection by improving the Markov Clustering (MCL) algorithm using a core-attachment model. The new MCL-CA method significantly enhances accuracy and coverage of predicted protein complexes.

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Area of Science:

  • Computational biology
  • Systems biology
  • Proteomics

Background:

  • Protein complexes drive essential cellular functions.
  • Detecting protein complexes requires analyzing protein-protein interaction (PPI) networks.
  • The Markov Clustering (MCL) algorithm is a scalable PPI clustering method but generates noisy results.

Purpose of the Study:

  • To improve the accuracy and coverage of protein complex detection.
  • To refine MCL-generated clusters by incorporating protein organization insights.
  • To introduce a novel computational method for protein complex analysis.

Main Methods:

  • Developed MCL-CA, a method that refines MCL clusters using a core-attachment protein organization model.
  • Evaluated MCL-CA on two distinct biological datasets.
  • Compared MCL-CA's performance against MCL, CORE, and COACH algorithms.

Main Results:

  • MCL-CA significantly improves the accuracy of predicted protein complexes compared to MCL.
  • MCL-CA increases the number of identified known complexes.
  • Predicted complexes from MCL-CA demonstrate adherence to the core-attachment structure.

Conclusions:

  • The core-attachment model effectively refines PPI network clusters for better protein complex identification.
  • MCL-CA offers a superior approach to protein complex detection over standard MCL.
  • The findings support the biological relevance of the core-attachment protein organization model.