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Related Concept Videos

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...
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...
Signal Sequences and Sorting Receptors01:41

Signal Sequences and Sorting Receptors

Signal sequences are short amino acid sequences that guide newly synthesized proteins to their proper location within the cell. Classical signal sequences are fifteen to sixty amino acids long and present at the N-terminus of a polypeptide chain. Each signal sequence has a conserved segment of basic residues towards their N terminus, a hydrophobic core, and a C-terminus rich in polar residues. The C-terminus also contains a signal cleavage site and features a -3 -1 sequence motif. The -3-1...

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Related Experiment Video

Updated: Jun 9, 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

Simple sequence-based kernels do not predict protein-protein interactions.

Jiantao Yu1, Maozu Guo, Chris J Needham

  • 1School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.

Bioinformatics (Oxford, England)
|August 31, 2010
PubMed
Summary
This summary is machine-generated.

Protein-protein interaction (PPI) prediction accuracies are often overestimated. Simple sequence-based features are insufficient, but protein domain features show some predictive value when using balanced datasets.

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Systems Biology

Background:

  • Protein-protein interactions (PPIs) are crucial for cellular functions.
  • Sequence-based features are commonly used for PPI prediction.
  • Previous studies report high accuracy for sequence-based PPI prediction.

Purpose of the Study:

  • To evaluate the realism of high accuracies reported for sequence-based PPI prediction methods.
  • To investigate the impact of dataset composition on prediction accuracy.
  • To develop a more robust method for predicting PPIs.

Main Methods:

  • Analysis of existing PPI prediction methods and their reported accuracies.
  • Assessment of the influence of training and testing dataset structures.
  • Development of a positive set-specific method ('BRS-nonint') to create balanced negative datasets.
  • Evaluation of sequence-based and protein domain-based features.

Main Results:

  • Reported accuracies for sequence-based PPI prediction are significantly overestimated.
  • Prediction accuracy is highly dependent on the structure of training and testing datasets.
  • Bias towards dominant samples (hub proteins) inflates accuracy estimates.
  • A balanced negative set creation method was proposed.
  • Simple sequence-based features lack sufficient predictive power for PPIs.
  • Protein domain-based features demonstrate some predictive value.

Conclusions:

  • High accuracy claims for sequence-based PPI prediction are questionable.
  • Careful dataset balancing is essential for reliable PPI prediction.
  • Protein domain information is more informative than simple sequence features for PPI prediction.