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Related Concept Videos

Protein-protein Interfaces02:04

Protein-protein Interfaces

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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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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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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.
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Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
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Ligand Binding Sites

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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.
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A Protocol for Computer-Based Protein Structure and Function Prediction
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Improving protein-protein interaction site prediction using graph neural network and structure profiles.

Qing Zhang1, You-Hang Hu1, Yu Zhou1

  • 1College of Information Engineering, Zhejiang University of Technology, Hangzhou, 310023, China.

Analytical Biochemistry
|June 30, 2025
PubMed
Summary

TargetPPI accurately predicts protein-protein interaction sites by integrating protein structure and sequence data using advanced neural networks. This method enhances understanding of biological processes and protein functions.

Keywords:
Deep learningEnsemble strategyProtein-protein interaction site prediction

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Protein-protein interactions (PPIs) are fundamental to cellular functions.
  • Identifying amino acid residues in PPIs is crucial for understanding protein mechanisms.

Purpose of the Study:

  • To develop an accurate predictor for protein-protein interaction sites.
  • To integrate protein structure and sequence information for improved prediction.

Main Methods:

  • Utilized a novel approach combining Convolutional Neural Networks (CNN), Bidirectional Long Short-Term Memory networks (Bi-LSTM), and Edge Aggregation through Graph Attention with Node Similarity (EGR-NS).
  • Extracted global and local features using CNN and Bi-LSTM, respectively.
  • Integrated structural features as edge embeddings in a protein structure-derived graph.

Main Results:

  • TargetPPI demonstrated superior performance compared to existing state-of-the-art methods on seven independent datasets.
  • Achieved average accuracy of 84.3%, precision of 57.6%, and Matthews Correlation Coefficient (MCC) of 0.383.
  • A mean ensemble strategy improved prediction accuracy by integrating diverse model parameters.

Conclusions:

  • TargetPPI offers a robust and accurate method for predicting protein-protein interaction sites.
  • The integration of structural and sequential data significantly enhances prediction capabilities.
  • The developed tool provides valuable insights into protein functional mechanisms and is publicly available.