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Molecular Mechanism of Allosteric Communication in Hsp70 Revealed by Molecular Dynamics Simulations

Overview of attention for article published in PLoS Computational Biology, December 2012
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Title
Molecular Mechanism of Allosteric Communication in Hsp70 Revealed by Molecular Dynamics Simulations
Published in
PLoS Computational Biology, December 2012
DOI 10.1371/journal.pcbi.1002844
Pubmed ID
Authors

Federica Chiappori, Ivan Merelli, Giorgio Colombo, Luciano Milanesi, Giulia Morra

Abstract

Investigating ligand-regulated allosteric coupling between protein domains is fundamental to understand cell-life regulation. The Hsp70 family of chaperones represents an example of proteins in which ATP binding and hydrolysis at the Nucleotide Binding Domain (NBD) modulate substrate recognition at the Substrate Binding Domain (SBD). Herein, a comparative analysis of an allosteric (Hsp70-DnaK) and a non-allosteric structural homolog (Hsp110-Sse1) of the Hsp70 family is carried out through molecular dynamics simulations, starting from different conformations and ligand-states. Analysis of ligand-dependent modulation of internal fluctuations and local deformation patterns highlights the structural and dynamical changes occurring at residue level upon ATP-ADP exchange, which are connected to the conformational transition between closed and open structures. By identifying the dynamically responsive protein regions and specific cross-domain hydrogen-bonding patterns that differentiate Hsp70 from Hsp110 as a function of the nucleotide, we propose a molecular mechanism for the allosteric signal propagation of the ATP-encoded conformational signal.

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The data shown below were compiled from readership statistics for 129 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 3 2%
Korea, Republic of 1 <1%
Germany 1 <1%
United States 1 <1%
Poland 1 <1%
Unknown 122 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 36 28%
Researcher 29 22%
Student > Master 17 13%
Student > Bachelor 11 9%
Professor > Associate Professor 7 5%
Other 20 16%
Unknown 9 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 44 34%
Biochemistry, Genetics and Molecular Biology 31 24%
Chemistry 19 15%
Physics and Astronomy 5 4%
Medicine and Dentistry 5 4%
Other 12 9%
Unknown 13 10%