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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.
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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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Mitogen-activated protein kinase, or MAPK pathway, activates three sequential kinases to regulate cellular responses such as proliferation, differentiation, survival, and apoptosis. The canonical MAPK pathway starts with a mitogen or growth factor binding to an RTK. The activated RTKs stimulate Ras, which recruits Raf or MAP3 Kinase (MAPKKK), the first kinase of the MAPK signaling cascade. Raf further phosphorylates and activates MEK or MAP2 Kinases (MAPKK), which in turn phosphorylates MAP...
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When a ligand binds to a cell-surface receptor, the receptor's intracellular domain changes shape, which may either activate its enzyme function or allow its binding to other molecules. The initial signal is amplified by most signal transduction pathways. This means that a single ligand molecule can activate multiple molecules of a downstream target. Proteins that relay a signal are most commonly phosphorylated at one or more sites, activating or inactivating the protein. Kinases catalyze...
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Updated: Sep 17, 2025

Kinase Inhibitor Screening In Self-assembled Human Protein Microarrays
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Inference of differential kinase interaction networks with KINference.

Nicolai Meyerhöfer1,2, Nevan J Krogan2,3,4,5, Benjamin J Polacco2,4,5

  • 1Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander University Erlangen-Nürnberg (FAU), 91052 Erlangen, Germany.

Bioinformatics (Oxford, England)
|June 27, 2025
PubMed
Summary

KINference infers differential kinase-substrate links from phosphoproteomics data. This data-driven approach identifies condition-specific kinase activity, advancing network biology and disease research.

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Area of Science:

  • Computational Biology
  • Systems Biology
  • Network Biology

Background:

  • Differential kinase interaction networks (DKINs) represent condition-specific kinase-substrate links.
  • Existing methods struggle to predict DKINs, often relying on limited prior biochemical knowledge.
  • There is a need for data-driven DKIN inference methods, especially when prior knowledge is scarce.

Purpose of the Study:

  • To develop a novel computational method for inferring differential kinase-substrate links (DKINs).
  • To provide a data-driven approach for DKIN inference applicable even with limited prior knowledge.
  • To identify condition-specific kinase activity and subnetworks from phosphoproteomics data.

Main Methods:

  • KINference integrates baseline kinase networks with node and edge filters.
  • Node filters utilize functional relevance and differential phosphorylation scores.
  • Edge filters employ prize-collecting Steiner trees and kinase-target phosphorylation correlations.

Main Results:

  • KINference successfully identifies differentially active subnetworks from phosphoproteomics data.
  • The method shows significant overlap with known kinase-substrate interactions in validation datasets.
  • A case study on SARS-CoV-2 infection data suggests a novel host-pathway link to viral replication.

Conclusions:

  • KINference provides a robust, data-driven method for DKIN inference.
  • The tool facilitates hypothesis generation for biological discovery, as demonstrated in viral infection studies.
  • KINference advances the field of network biology by enabling condition-specific network analysis.