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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 Kinases and Phosphatases02:54

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Proteins undergo chemical modifications that trigger changes in the charge, structure, and conformation of the proteins. Phosphorylation, acetylation, glycosylation, nitrosylation, ubiquitination, lipidation, methylation, and proteolysis are various protein modifications that regulate protein activity. Such modifications are usually enzyme-driven.
Protein kinases
Many proteins in the cell are regulated by phosphorylation, the addition of a phosphate group. A family of enzymes called kinases...
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Phosphoinositides and PIPs01:42

Phosphoinositides and PIPs

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Phosphoinositides are a group of phospholipids containing a glycerol backbone with two fatty acid chains and a phosphate attached to a myoinositol sugar ring. The inositol head group extends into the cytoplasm, where it is modified by adding phosphate groups to form phosphatidylinositol phosphates or PIPs.
Different phosphoinositides are synthesized and recruited on the cytosolic face of the plasma membrane. The localization of specific phosphoinositides concentrated in separate membrane...
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Amplifying Signals via Enzymatic Cascade01:22

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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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Assembly of Signaling Complexes01:30

Assembly of Signaling Complexes

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Multiprotein signaling complexes are formed in a dynamic process involving protein-protein interactions at the cytoplasmic domain of transmembrane receptors or enzymatic and non-enzymatic proteins associated with the receptor. These complexes ensure the activation and propagation of intracellular signals that regulate cell functions.
Interaction domains in cell signaling
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Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

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Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
Convergence and divergence, and cross-talk between signaling pathways
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Updated: Aug 14, 2025

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Phosphoproteomics data-driven signalling network inference: Does it work?

Lourdes O Sriraja1, Adriano Werhli1,2, Evangelia Petsalaki1

  • 1European Molecular Biology Laboratory - European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK.

Computational and Structural Biotechnology Journal
|January 9, 2023
PubMed
Summary
This summary is machine-generated.

Predicting kinase-substrate associations from phosphoproteome data is challenging due to incomplete annotations. A sequence similarity filter significantly improved predictions, highlighting the need for better evaluation methods.

Keywords:
AUCContext specific networksCorrelationEvaluation of performanceFunChiSqGaussian graphical modelKinasesKinase–substrate relationshipsMutual informationNetwork biologyNetwork inferencePredictionSequence similarity

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Area of Science:

  • Systems Biology
  • Proteomics
  • Bioinformatics

Background:

  • Global phosphoproteome profiling offers extensive phosphosite data, enabling kinase-substrate association predictions.
  • However, most substrates lack identified regulatory kinases due to biased and incomplete database annotations.

Purpose of the Study:

  • To compare the performance of six pairwise measures for predicting kinase-substrate associations using mass spectrometry-based phosphoproteome data.
  • To evaluate the effectiveness of a sequence similarity filter in improving these predictions.

Main Methods:

  • Utilized publicly available, time-resolved, and perturbation mass spectrometry-based phosphoproteome data.
  • Compared six pairwise measures for kinase-substrate association prediction.
  • Validated performance against literature-based networks and predicted kinase-substrate interaction sets, and applied a sequence similarity filter.

Main Results:

  • Pairwise measures showed poor performance in predicting kinase-substrate associations using current reference sets.
  • Performance remained poor when analyzing substrate-substrate associations regulated by the same kinase.
  • Incorporating a sequence similarity filter significantly boosted the performance of substrate-substrate association predictions.

Conclusions:

  • Filtering methods, like sequence similarity, are crucial for reducing noise and enhancing signal in network inference for kinase-substrate associations.
  • Current gold-standard reference sets are inadequate for evaluation due to limitations and context-agnostic nature.
  • Development of context-specific and higher-coverage evaluation methods is necessary for accurate kinase-substrate association prediction.