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Ubiquitin Dynamics in Complexes Reveal Molecular Recognition Mechanisms Beyond Induced Fit and Conformational Selection

Overview of attention for article published in PLoS Computational Biology, October 2012
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Title
Ubiquitin Dynamics in Complexes Reveal Molecular Recognition Mechanisms Beyond Induced Fit and Conformational Selection
Published in
PLoS Computational Biology, October 2012
DOI 10.1371/journal.pcbi.1002704
Pubmed ID
Authors

Jan H. Peters, Bert L. de Groot

Abstract

Protein-protein interactions play an important role in all biological processes. However, the principles underlying these interactions are only beginning to be understood. Ubiquitin is a small signalling protein that is covalently attached to different proteins to mark them for degradation, regulate transport and other functions. As such, it interacts with and is recognised by a multitude of other proteins. We have conducted molecular dynamics simulations of ubiquitin in complex with 11 different binding partners on a microsecond timescale and compared them with ensembles of unbound ubiquitin to investigate the principles of their interaction and determine the influence of complex formation on the dynamic properties of this protein. Along the main mode of fluctuation of ubiquitin, binding in most cases reduces the conformational space available to ubiquitin to a subspace of that covered by unbound ubiquitin. This behaviour can be well explained using the model of conformational selection. For lower amplitude collective modes, a spectrum of zero to almost complete coverage of bound by unbound ensembles was observed. The significant differences between bound and unbound structures are exclusively situated at the binding interface. Overall, the findings correspond neither to a complete conformational selection nor induced fit scenario. Instead, we introduce a model of conformational restriction, extension and shift, which describes the full range of observed effects.

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Geographical breakdown

Country Count As %
Germany 3 3%
Italy 3 3%
India 2 2%
Israel 1 1%
United Kingdom 1 1%
Canada 1 1%
United States 1 1%
Unknown 83 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 31%
Researcher 29 31%
Professor 8 8%
Professor > Associate Professor 5 5%
Student > Master 5 5%
Other 12 13%
Unknown 7 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 31%
Chemistry 20 21%
Biochemistry, Genetics and Molecular Biology 16 17%
Physics and Astronomy 6 6%
Computer Science 4 4%
Other 10 11%
Unknown 10 11%