4.8 Article

Identification of a ubiquitin-binding interface using Rosetta and DEER

出版社

NATL ACAD SCIENCES
DOI: 10.1073/pnas.1716861115

关键词

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

资金

  1. National Institutes of Health (NIH) [NIAID AI104922, NIGMS GM114234]
  2. NIH [P41 EB001980, S10RR022422, S10OD011937]
  3. NIGMS [R01 GM080403, R01 GM073151]
  4. NATIONAL CENTER FOR RESEARCH RESOURCES [S10RR022422] Funding Source: NIH RePORTER
  5. NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES [R01AI104922] Funding Source: NIH RePORTER
  6. NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING [P41EB001980] Funding Source: NIH RePORTER
  7. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [R01GM114234, R01GM080403, R01GM073151] Funding Source: NIH RePORTER
  8. OFFICE OF THE DIRECTOR, NATIONAL INSTITUTES OF HEALTH [S10OD011937] Funding Source: NIH RePORTER

向作者/读者索取更多资源

ExoU is a type III-secreted cytotoxin expressing A(2) phospholipase activity when injected into eukaryotic target cells by the bacterium Pseudomonas aeruginosa. The enzymatic activity of ExoU is un-detectable in vitro unless ubiquitin, a required cofactor, is added to the reaction. The role of ubiquitin in facilitating ExoU enzymatic activity is poorly understood but of significance for designing inhibitors to prevent tissue injury during infections with strains of P. aeruginosa producing this toxin. Most ubiquitin-binding proteins, including ExoU, demonstrate a low (micromolar) affinity for monoubiquitin (monoUb). Additionally, ExoU is a large and dynamic protein, limiting the applicability of traditional structural techniques such as NMR and X-ray crystallography to define this protein-protein interaction. Recent advancements in computational methods, however, have allowed high-resolution protein modeling using sparse data. In this study, we combine double electron-electron resonance (DEER) spectroscopy and Rosetta modeling to identify potential binding interfaces of ExoU and monoUb. The lowestenergy scoring model was tested using biochemical, biophysical, and biological techniques. To verify the binding interface, Rosetta was used to design a panel of mutations to modulate binding, including one variant with enhanced binding affinity. Our analyses show the utility of computational modeling when combined with sensitive biological assays and biophysical approaches that are exquisitely suited for large dynamic proteins.

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