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Covalently Linked Protein Regulators

Covalently Linked Protein Regulators

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.

Improving Translational Accuracy

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...

Improving Translational Accuracy

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...

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Related Experiment Video

Updated: Jun 12, 2026

Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization

Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization

Published on: February 27, 2020

Predicting post-translational lysine acetylation using support vector machines.

Florian Gnad¹, Shubin Ren, Chunaram Choudhary

¹Department of Proteomics and Signal Transduction, Max-Planck-Institute of Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany.

Bioinformatics (Oxford, England)

|May 28, 2010

Summary

This summary is machine-generated.

Researchers developed a support vector machine (SVM) to predict lysine acetylation sites. This computational tool accurately identifies potential protein acetylation sites, aiding in understanding cell signaling.

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Last Updated: Jun 12, 2026

Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization

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Published on: February 27, 2020

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Detection of Protein S-Acylation using Acyl-Resin Assisted Capture

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Published on: April 10, 2020

Area of Science:

Biochemistry
Proteomics
Computational Biology

Background:

Lysine acetylation is a critical post-translational modification regulating cell signaling pathways.
Identifying acetylation sites is crucial for understanding protein function and regulation.
Previous studies have identified numerous acetylation sites, but a comprehensive dataset was lacking.

Purpose of the Study:

To create the most comprehensive human acetylome dataset to date.
To develop a computational tool for accurate in silico prediction of lysine acetylation sites.
To facilitate further research into the functional roles of protein acetylation.

Main Methods:

Utilized high-resolution mass spectrometry to identify lysine acetylation sites.
Compiled a dataset of 3600 acetylation sites on 1750 human proteins.
Trained a support vector machine (SVM) model using this comprehensive dataset.

Main Results:

Generated the most extensive human acetylome dataset available.
Developed a SVM-based predictor for acetylated lysine residues.
Achieved 78% precision at 78% recall for acetylation site prediction.

Conclusions:

The comprehensive acetylome dataset enables robust training of predictive models.
The developed SVM predictor offers high accuracy in identifying potential acetylation sites.
This tool can significantly advance research in cell signaling and protein regulation.