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Related Concept Videos

Protein Kinases and Phosphatases02:54

Protein Kinases and Phosphatases

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...
Protein Kinases and Phosphatases02:54

Protein Kinases and Phosphatases

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...
Amplifying Signals via Enzymatic Cascade01:22

Amplifying Signals via Enzymatic Cascade

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 the...

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Related Experiment Video

Updated: Jun 25, 2026

Identification of Kinase-substrate Pairs Using High Throughput Screening
11:13

Identification of Kinase-substrate Pairs Using High Throughput Screening

Published on: August 29, 2015

Reconstructing regulatory kinase pathways from phosphopeptide data: a bioinformatics approach.

Lawrence G Puente1, Robin E C Lee, Lynn A Megeney

  • 1Ottawa Health Research Institute, The Ottawa Hospital, Ottawa, ON, Canada.

Methods in Molecular Biology (Clifton, N.J.)
|February 26, 2009
PubMed
Summary

Protein phosphorylation signaling is complex. New in silico models integrate protein interaction data to build comprehensive kinase networks, revealing insights beyond simple pathway analysis.

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A Mass Spectrometry-Based Approach to Identify Phosphoprotein Phosphatases and their Interactors
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A Mass Spectrometry-Based Approach to Identify Phosphoprotein Phosphatases and their Interactors

Published on: April 29, 2022

Related Experiment Videos

Last Updated: Jun 25, 2026

Identification of Kinase-substrate Pairs Using High Throughput Screening
11:13

Identification of Kinase-substrate Pairs Using High Throughput Screening

Published on: August 29, 2015

A Mass Spectrometry-Based Approach to Identify Phosphoprotein Phosphatases and their Interactors
10:17

A Mass Spectrometry-Based Approach to Identify Phosphoprotein Phosphatases and their Interactors

Published on: April 29, 2022

Area of Science:

  • Molecular Biology
  • Systems Biology
  • Bioinformatics

Background:

  • Protein phosphorylation is a fundamental cellular mechanism regulating diverse biological processes.
  • Traditional linear pathway models often fail to capture the intricate nature of in vivo kinase signaling networks.
  • Advancements in protein interaction databases provide a rich source of data for network reconstruction.

Purpose of the Study:

  • To develop sophisticated in silico models of intracellular protein phosphorylation signaling.
  • To leverage protein-protein and kinase-substrate interaction data for network construction.
  • To explore complex kinase signaling pathways that are not apparent through conventional methods.

Main Methods:

  • Integration of protein phosphorylation data with existing protein-protein interaction databases.
  • Utilization of kinase-substrate interaction databases for network building.
  • Application of graph theory for the analysis of constructed kinase interaction networks.

Main Results:

  • Construction of in silico models representing complex intracellular protein phosphorylation signaling.
  • Visualization and analysis of kinase interaction networks using graph theory.
  • Identification of novel hypotheses regarding signaling pathway mechanisms.

Conclusions:

  • In silico modeling, integrating diverse interaction data, offers a powerful approach to understanding complex signaling networks.
  • Graph theory analysis of kinase interaction networks facilitates the discovery of non-obvious biological insights.
  • This systems biology approach enhances our comprehension of cellular signaling beyond simplistic linear models.