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Updated: Feb 16, 2026

Profiling Ubiquitin and Ubiquitin-like Dependent Post-translational Modifications and Identification of Significant Alterations

Profiling Ubiquitin and Ubiquitin-like Dependent Post-translational Modifications and Identification of Significant Alterations

Published on: November 7, 2019

Identification of a ubiquitin-binding interface using Rosetta and DEER.

Maxx H Tessmer¹, David M Anderson², Adam M Pickrum¹

¹Department of Microbiology and Immunology, Medical College of Wisconsin, Milwaukee, WI 53226.

Proceedings of the National Academy of Sciences of the United States of America

|January 4, 2018

Summary

This study reveals how the Pseudomonas aeruginosa cytotoxin ExoU binds ubiquitin, a crucial cofactor for its enzymatic activity. Computational modeling and experimental data identified key binding sites, aiding in the development of potential inhibitors.

Keywords:

DEER Rosetta computational modeling continuous-wave spectroscopy ubiquitin-binding domain

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Detection of Protein Ubiquitination

Detection of Protein Ubiquitination

Published on: August 19, 2009

Area of Science:

Microbiology
Biochemistry
Structural Biology

Background:

ExoU is a Pseudomonas aeruginosa cytotoxin with phospholipase activity.
Its enzymatic activity requires ubiquitin (Ub) as a cofactor, but the interaction is poorly understood.
ExoU is large and dynamic, hindering traditional structural studies.

Purpose of the Study:

To identify the binding interface between ExoU and monoubiquitin (monoUb).
To utilize computational modeling combined with experimental data for studying protein-protein interactions.
To provide insights for developing inhibitors against P. aeruginosa infections.

Main Methods:

Combined double electron-electron resonance (DEER) spectroscopy with Rosetta computational modeling.
Utilized biochemical, biophysical, and biological assays to validate models.
Employed Rosetta to design mutations for interface analysis and affinity modulation.

Main Results:

Identified potential binding interfaces between ExoU and monoUb using computational modeling.
Validated the binding interface through experimental approaches.
Designed ExoU variants with altered and enhanced binding affinities.

Conclusions:

Computational modeling coupled with biophysical and biological assays is effective for studying large, dynamic protein interactions.
The identified ExoU-ubiquitin interaction provides a basis for therapeutic strategies.
Understanding this interaction is key to combating P. aeruginosa virulence.