Multiscale Approach to the Determination of the Photoactive Yellow Protein Signaling State Ensemble

Date
2014
Journal Title
Journal ISSN
Volume Title
Publisher
Public Library of Science
Abstract

The nature of the optical cycle of photoactive yellow protein (PYP) makes its elucidation challenging for both experiment and theory. The long transition times render conventional simulation methods ineffective, and yet the short signaling-state lifetime makes experimental data difficult to obtain and interpret. Here, through an innovative combination of computational methods, a prediction and analysis of the biological signaling state of PYP is presented. Coarse-grained modeling and locally scaled diffusion map are first used to obtain a rough bird's-eye view of the free energy landscape of photo-activated PYP. Then all-atom reconstruction, followed by an enhanced sampling scheme; diffusion map-directed-molecular dynamics are used to focus in on the signaling-state region of configuration space and obtain an ensemble of signaling state structures. To the best of our knowledge, this is the first time an all-atom reconstruction from a coarse grained model has been performed in a relatively unexplored region of molecular configuration space. We compare our signaling state prediction with previous computational and more recent experimental results, and the comparison is favorable, which validates the method presented. This approach provides additional insight to understand the PYP photo cycle, and can be applied to other systems for which more direct methods are impractical.

Description
Advisor
Degree
Type
Journal article
Keywords
Citation

Rohrdanz, Mary A., Zheng, Wenwei, Lambeth, Bradley, et al.. "Multiscale Approach to the Determination of the Photoactive Yellow Protein Signaling State Ensemble." PLoS Computational Biology, 10, no. 10 (2014) Public Library of Science: e1003797. http://dx.doi.org/10.1371/journal.pcbi.1003797.

Has part(s)
Forms part of
Rights
This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citable link to this page