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An Improved Strategy for Generating Forces in Steered Molecular Dynamics: The Mechanical Unfolding of Titin, e2lip3 and Ubiquitin

Overview of attention for article published in PLOS ONE, September 2010
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Title
An Improved Strategy for Generating Forces in Steered Molecular Dynamics: The Mechanical Unfolding of Titin, e2lip3 and Ubiquitin
Published in
PLOS ONE, September 2010
DOI 10.1371/journal.pone.0013068
Pubmed ID
Authors

Bosco K. Ho, David A. Agard

Abstract

One of the applications of Molecular Dynamics (MD) simulations is to explore the energetic barriers to mechanical unfolding of proteins such as occurs in response to the mechanical pulling of single molecules in Atomic Force Microscopy (AFM) experiments. Although Steered Molecular Dynamics simulations have provided microscopic details of the unfolding process during the pulling, the simulated forces required for unfolding are typically far in excess of the measured values. To rectify this, we have developed the Pulsed Unconstrained Fluctuating Forces (PUFF) method, which induces constant-momentum motions by applying forces directly to the instantaneous velocity of selected atoms in a protein system. The driving forces are applied in pulses, which allows the system to relax between pulses, resulting in more accurate unfolding force estimations than in previous methods. In the cases of titin, ubiquitin and e2lip3, the PUFF trajectories produce force fluctuations that agree quantitatively with AFM experiments. Another useful property of PUFF is that simulations get trapped if the target momentum is too low, simplifying the discovery and analysis of unfolding intermediates.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 7%
Italy 2 4%
Germany 2 4%
Brazil 2 4%
United Kingdom 1 2%
Unknown 36 78%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 35%
Researcher 13 28%
Student > Master 6 13%
Professor 4 9%
Professor > Associate Professor 2 4%
Other 1 2%
Unknown 4 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 35%
Physics and Astronomy 9 20%
Chemistry 6 13%
Biochemistry, Genetics and Molecular Biology 3 7%
Business, Management and Accounting 1 2%
Other 5 11%
Unknown 6 13%