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Related Concept Videos

Protein Kinases and Phosphatases02:54

Protein Kinases and Phosphatases

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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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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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Identification of Kinase-substrate Pairs Using High Throughput Screening
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KinasePA: Phosphoproteomics data annotation using hypothesis driven kinase perturbation analysis.

Pengyi Yang1,2,3, Ellis Patrick4, Sean J Humphrey2,5

  • 1School of Mathematics and Statistics, University of Sydney, Sydney, NSW, Australia.

Proteomics
|May 6, 2016
PubMed
Summary
This summary is machine-generated.

KinasePA is a new bioinformatic tool for analyzing phosphoproteomics data. It helps visualize how multiple treatments affect kinases and their substrates, revealing complex cellular signaling pathways.

Keywords:
BioinformaticsHypothesis testingKinasePerturbationPhosphoproteomicsSignalling

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Area of Science:

  • Proteomics and Bioinformatics
  • Cellular Signaling Pathways
  • Systems Biology

Background:

  • Mass spectrometry (MS)-based quantitative phosphoproteomics is crucial for understanding cellular phosphorylation.
  • Traditional experimental designs often lack the capacity to analyze multiple treatments simultaneously.
  • Analyzing combinatorial perturbations is vital for dissecting complex signaling responses.

Purpose of the Study:

  • To develop a bioinformatic tool for integrating and visualizing kinase-substrate perturbations under combinatorial treatments.
  • To enable the dissection of concordant and independent effects of multiple treatments in phosphoproteomics.
  • To provide a user-friendly platform for analyzing complex signaling pathway dynamics.

Main Methods:

  • Development of hypothesis-driven kinase perturbation analysis (KinasePA).
  • Application of KinasePA to two large-scale phosphoproteomics datasets.
  • Implementation of KinasePA within the "directPA" R package and a web interface.

Main Results:

  • KinasePA effectively annotates and visualizes perturbed kinases and substrates under combinatorial treatments.
  • Demonstrated utility in dissecting signaling pathways influenced by combined cellular stimuli and inhibitors.
  • Successfully applied to large-scale phosphoproteomics data, revealing treatment-specific effects.

Conclusions:

  • KinasePA is an effective tool for analyzing complex phosphoproteomics data with multiple treatments.
  • The tool aids in understanding kinase-substrate interactions within signaling pathways under combinatorial perturbations.
  • KinasePA is accessible via an R package and an interactive web interface for broader research application.