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Phase II Reactions: Methylation Reactions

Phase II Reactions: Methylation Reactions

Methylation is a phase II biotransformation process involving the attachment of a methyl group to a substrate. Enzymes known as methyltransferases orchestrate this reaction.
The mechanism of methylation unfolds in two stages. The first stage sees a methyltransferase enzyme facilitating the transfer of a methyl group from S-adenosylmethionine (SAM) to the substrate, forming S-adenosylhomocysteine (SAH). The second stage involves further metabolism of SAH into homocysteine, which can be recycled...

Covalently Linked Protein Regulators

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Proteins can undergo many types of post-translational modifications, often in response to changes in their environment. These modifications play an important role in the function and stability of these proteins. Covalently linked molecules include functional groups, such as methyl, acetyl, and phosphate groups, and also small proteins, such as ubiquitin. There are around 200 different types of covalent regulators that have been identified.
These groups modify specific amino acids in a protein....

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Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
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Related Experiment Video

Updated: Dec 24, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Two-Level Protein Methylation Prediction using structure model-based features.

Wei Zheng^1,2, Qiqige Wuyun^3,2, Micah Cheng⁴

¹Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA.

Scientific Reports

|April 9, 2020

Summary

This summary is machine-generated.

This study introduces Met-predictor, a novel method for predicting protein methylation sites and types. It uniquely integrates protein tertiary structure information, significantly improving prediction accuracy for methyllysine and methylarginine.

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Area of Science:

Biochemistry
Bioinformatics
Computational Biology

Background:

Protein methylation is crucial for cellular processes.
Existing prediction methods often overlook tertiary structure and methylation types (e.g., mono-, di-, tri-methylation).

Purpose of the Study:

To develop a novel method, Met-predictor, for predicting protein methylation sites and types.
To incorporate protein tertiary structure information into methylation prediction for the first time.

Main Methods:

Developed Met-predictor using a support vector machine-based network.
Combined sequence-based features with novel structure model-based features (geometric information from predicted tertiary structures).

Main Results:

Met-predictor improved prediction accuracy (AUC) for lysine methylation from 0.611/0.520 to 0.655/0.566 and for arginine methylation from 0.723/0.640 to 0.734/0.643.
Achieved higher accuracy than state-of-the-art methods, with improvements of 13.1% (3.9%) and 8.5% (16.4%) for methyllysine and methylarginine, respectively.
Demonstrated excellent performance in predicting methylation types.

Conclusions:

Integrating protein tertiary structure information significantly enhances methylation site prediction.
Met-predictor offers a superior approach for predicting both methylation sites and types, advancing the field of protein post-translational modification analysis.