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Phosphorylation

Phosphorylation

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...

Phosphorylation

Phosphorylation

Protein Kinases and Phosphatases

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...

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Ligand Binding and Linkage

Ligand Binding and Linkage

Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked. In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...

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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Related Experiment Video

Updated: Mar 22, 2026

Oligopeptide Competition Assay for Phosphorylation Site Determination

Oligopeptide Competition Assay for Phosphorylation Site Determination

Published on: May 18, 2017

Prioritizing functional phosphorylation sites based on multiple feature integration.

Qingyu Xiao^1,2, Benpeng Miao^1,2, Jie Bi^2,3

¹Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P. R. China.

Scientific Reports

|April 20, 2016

Summary

This summary is machine-generated.

This study identifies key features distinguishing functional phosphorylation sites from non-functional ones. It prioritizes over 200,000 human phosphosites, aiding research into biological roles.

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Identification of Kinase-substrate Pairs Using High Throughput Screening

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Published on: August 29, 2015

Area of Science:

Molecular Biology
Biochemistry
Bioinformatics

Background:

Protein phosphorylation is a crucial post-translational modification regulating diverse biological activities.
Advances in mass spectrometry have identified numerous phosphorylation sites, but many may lack function.
Distinguishing functional from non-functional phosphosites is vital for understanding biological roles.

Purpose of the Study:

To explore intrinsic features differentiating functional phosphorylation sites.
To develop a predictive model for identifying likely functional phosphosites.
To prioritize human phosphorylation sites for future functional studies.

Main Methods:

Comparative analysis of evolutionary conservation, kinase association, disorder scores, and secondary structures between functional and background phosphosite datasets.
Development and evaluation of four distinct classifier types based on identified features.
Systematic prioritization of human phosphorylation sites using developed models.

Main Results:

Significant differences were observed in evolutionary conservation, kinase association, disorder scores, and secondary structures between functional and background phosphosites.
Four classifier types demonstrated comparable predictive performance.
213,837 human phosphorylation sites were prioritized.

Conclusions:

Intrinsic features can effectively predict the functionality of phosphorylation sites.
The prioritized human phosphosite dataset provides a valuable resource for biological research.
The Predict Functional Phosphosites (PFP) website offers accessible data for further investigation.