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Protein Networks02:26

Protein Networks

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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.
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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Protein-protein Interfaces02:04

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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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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
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Protein Organization01:24

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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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Conserved Binding Sites

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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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A Protocol for Computer-Based Protein Structure and Function Prediction
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PEPPI: Whole-proteome Protein-protein Interaction Prediction through Structure and Sequence Similarity, Functional

Eric W Bell1, Jacob H Schwartz1, Peter L Freddolino2

  • 1Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.

Journal of Molecular Biology
|June 6, 2022
PubMed
Summary
This summary is machine-generated.

We developed PEPPI, a computational pipeline that predicts protein-protein interactions using structural and sequence data. PEPPI accurately identifies interactions, outperforming existing methods and aiding in understanding viral infections.

Keywords:
SARS-CoV-2dimer threadingdirect interaction predictioninteractomeinterology

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Systems Biology

Background:

  • Identifying protein-protein interactions (PPIs) across entire proteomes is challenging for experimental methods.
  • Existing computational methods often fail to integrate both structural and sequence data effectively.

Purpose of the Study:

  • To present PEPPI, a novel computational pipeline for accurate, proteome-wide prediction of protein-protein interactions.
  • To leverage integrated structural, sequence, and functional data with machine learning for enhanced PPI prediction.

Main Methods:

  • PEPPI integrates structural similarity, sequence similarity, and functional association data.
  • A naïve Bayesian classifier model is employed for machine learning-based PPI prediction.
  • The pipeline was benchmarked against known protein interactions and non-interactions.

Main Results:

  • PEPPI achieved a 4.5% higher Area Under the Receiver Operating Characteristic curve (AUROC) compared to state-of-the-art methods.
  • Application to SARS-CoV-2 host interactions identified 403 high-confidence interactions.
  • Predictions covered 73% of a gold standard dataset, showing complementarity with experimental data.

Conclusions:

  • PEPPI offers a powerful and generally applicable tool for computational screening of protein-protein interactions.
  • The pipeline enhances the prediction accuracy by integrating diverse data types.
  • PEPPI aids in modeling complex biological systems, such as virus-host interactions.