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Related Concept Videos

Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...
Conservation of Protein Domains02:26

Conservation of Protein Domains

Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...
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 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,...
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...

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Related Experiment Video

Updated: Jul 19, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Bayesian data mining of protein domains gives an efficient predictive algorithm and new insight.

Rajani R Joshi1, Vivekanand V Samant

  • 1Department of Mathematics, Indian Institute of Technology Bombay, Powai, Mumbai, 400 076, India. rrj@math.iitb.ac.in

Journal of Molecular Modeling
|October 10, 2006
PubMed
Summary

This study introduces a new computational method for classifying protein domains using Bayesian Data Mining. The approach accurately predicts single, two continuous, or two discontinuous domains from primary sequences and secondary structures.

More Related Videos

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

Related Experiment Videos

Last Updated: Jul 19, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

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

Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Machine Learning in Proteomics

Background:

  • Identifying structural domains in proteins is crucial for predicting tertiary folds and functional sites.
  • Accurate domain identification aids in the design of biologically active molecules.

Purpose of the Study:

  • To present a novel computational method for classifying protein domains.
  • To predict whether a protein consists of single, two continuous, or two discontinuous domains.

Main Methods:

  • Utilizes Bayesian Data Mining for protein domain classification.
  • Requires only primary sequence and computer-predicted secondary structure as input.
  • Incorporates correlation patterns between 3D motifs and local helical folds.

Main Results:

  • Achieved prediction accuracies of 83.3% for single, 60% for two continuous, and 65.7% for two discontinuous domains.
  • Demonstrated superior performance compared to existing methods like DGS and DomSSEA.
  • Revealed conserved patterns of secondary folds and tertiary motifs with statistical confidence.

Conclusions:

  • The developed method is computationally simple, fast, and accurate for protein domain classification.
  • Offers new insights into conserved structural patterns within protein domains.
  • Enhances the accuracy of predicting domain boundary points for protein structural and functional modeling.