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Related Concept Videos

Protein Kinases and Phosphatases02:54

Protein Kinases and Phosphatases

15.8K
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...
15.8K
Protein Kinases and Phosphatases02:54

Protein Kinases and Phosphatases

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Phosphorylation01:02

Phosphorylation

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The addition or removal of phosphate groups from proteins is the most common chemical modification that regulates cellular processes. These modifications can affect the structure, activity, stability, and localization of proteins within cells as well as their interactions with other proteins.
During phosphorylation, protein kinases transfer the terminal phosphate group of ATP to specific amino acid side chains of substrate proteins. Serine, threonine, and tyrosine are the most commonly...
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Phosphorylation01:02

Phosphorylation

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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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Transducer Mechanism: Enzyme-Linked Receptors01:27

Transducer Mechanism: Enzyme-Linked Receptors

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Enzyme-linked receptors are cell-surface receptors acting as an enzyme or associating with an enzyme intracellularly. They make excellent drug targets. Drugs can bind to the extracellular ligand-binding domain or directly affect their enzymatic domain and alter their activity.
Major types that are helpful drug targets include:
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Identification of Kinase-substrate Pairs Using High Throughput Screening
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Computational methods and opportunities for phosphorylation network medicine.

Yian Ann Chen1, Steven A Eschrich1

  • 1Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, 12902 Magnolia Drive Tampa, FL 33612, USA.

Translational Cancer Research
|December 23, 2014
PubMed
Summary
This summary is machine-generated.

Protein phosphorylation is crucial for cell signaling and cancer treatment. Advances in phosphoproteomics and kinase inhibitors offer new therapeutic strategies by targeting complex cellular networks.

Keywords:
Phosphorylationcomputational biologydrug repurposingkinasenetwork inference

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Area of Science:

  • Biochemistry
  • Cell Biology
  • Bioinformatics

Background:

  • Protein phosphorylation is a key post-translational modification regulating cell signaling.
  • Cancer research increasingly targets complex signaling networks due to their complexity and redundancy.
  • Protein kinases are major drug targets in cancer therapy, with inhibitors widely used clinically.

Purpose of the Study:

  • To review the current state of phosphoproteomics for identifying and quantifying protein phosphorylation.
  • To discuss platform characteristics, database resources, and computational tools in phosphoproteomics.
  • To highlight the connection between phosphoproteomics advancements and cancer therapeutics.

Main Methods:

  • Review of high-throughput proteomics platforms, particularly mass-spectrometry (MS)-based methods.
  • Analysis of existing public databases and computational tools for phosphoproteomics data.
  • Examination of methods for inferring phosphorylation networks.

Main Results:

  • Phosphoproteomics, driven by MS and high-throughput platforms, provides high-dimensional data essential for cancer research.
  • Numerous database resources and computational tools are available to support phosphoproteomics analysis.
  • Inference of phosphorylation networks is advancing, linking molecular insights to therapeutic strategies.

Conclusions:

  • Phosphoproteomics advancements are critical for understanding cell signaling and developing targeted cancer therapies.
  • The integration of phosphoproteomics data, computational tools, and network inference offers significant opportunities for therapeutic development.
  • Future research in bioinformatics and biostatistics is essential to address limitations and leverage emerging technologies in phosphoproteomics.