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Related Concept Videos

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,...
Protein-protein Interfaces02:04

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 polypeptide...
Protein-Protein Interfaces02:04

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 polypeptide...
Ligand Binding Sites02:40

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
Bond Dissociation Energy and Activation Energy02:13

Bond Dissociation Energy and Activation Energy

Bond energy is the energy required to break a bond homolytically. These values are usually expressed in units of kcal/mol or kJ/mol and are referred to as bond dissociation energies when given for specific bonds or average bond energies when indicated for a given type of bond over many compounds. Firstly, the bond dissociation energy for a single bond is weaker than that of a double bond, which in turn is weaker than that of a triple bond. Secondly, hydrogen forms relatively strong bonds with...

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Related Experiment Video

Updated: Jul 4, 2026

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

Inferring modules of functionally interacting proteins using the Bond Energy Algorithm.

Ryosuke L A Watanabe1, Enrique Morett, Edgar E Vallejo

  • 1ITESM Campus Estado de México, Carretera Lago de Guadalupe km 3,5, Atizapán de Zaragoza, 52926, México. A00455731@itesm.mx

BMC Bioinformatics
|June 19, 2008
PubMed
Summary

The Bond Energy Algorithm (BEA) effectively predicts functional protein groups by analyzing linked relationships in phylogenetic profiles, outperforming traditional clustering methods for enhanced biological insight.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Non-homology based methods, like phylogenetic profiles, predict protein functional relationships without sequence similarity.
  • Traditional methods use pairwise similarity metrics, but proteins function in groups, requiring consideration of indirect relationships.
  • Accurate inference of protein functional modules necessitates analyzing both direct and indirect interactions.

Purpose of the Study:

  • To apply the Bond Energy Algorithm (BEA) for predicting functionally related protein groups.
  • To cluster phylogenetic profiles based on linked relationships among data elements.
  • To identify functional modules and protein associations beyond traditional pairwise comparisons.

Main Methods:

  • Utilized phylogenetic profiles from the Cluster of Orthologous Groups of Proteins (COG) database.
  • Employed the Bond Energy Algorithm (BEA) for clustering experiments.
  • Evaluated clustering results against COG functional categories and experimental data from DIP and ECOCYC databases.

Main Results:

  • BEA successfully predicted meaningful modules of functionally related proteins.
  • BEA demonstrated higher accuracy in predicting protein functional relationships compared to k-means and hierarchical clustering.
  • The algorithm effectively identified relationships by linking phylogenetic patterns through shared elements.

Conclusions:

  • Linked relationships of phylogenetic profiles analyzed by BEA are valuable for detecting functional associations.
  • BEA extends the discovery of functional modules missed by traditional clustering methods.
  • Future enhancements could incorporate gene neighborhood and protein fusion information for refined functional interaction classification.