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Deep learning study of tyrosine reveals that roaming can lead to photodamage
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Westermayr, Julia, Gastegger, Michael, Vörös, Dóra, Panzenboeck, Lisa, Joerg, Florian, González, Leticia and Marquetand, Philipp (2022) Deep learning study of tyrosine reveals that roaming can lead to photodamage. Nature Chemistry, 14 . pp. 914-919. doi:10.1038/s41557-022-00950-z ISSN 1755-4330.
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WRAP-deep-learning-study-tyrosine reveals-roaming-can-lead-photodamage-Westermayr-2022.pdf - Accepted Version - Requires a PDF viewer. Download (3789Kb) | Preview |
Official URL: http://dx.doi.org/10.1038/s41557-022-00950-z
Abstract
Amino acids are among the building blocks of life, forming peptides and proteins, and have been carefully ‘selected’ to prevent harmful reactions caused by light. To prevent photodamage, molecules relax from electronic excited states to the ground state faster than the harmful reactions can occur; however, such photochemistry is not fully understood, in part because theoretical simulations of such systems are extremely expensive—with only smaller chromophores accessible. Here, we study the excited-state dynamics of tyrosine using a method based on deep neural networks that leverages the physics underlying quantum chemical data and combines different levels of theory. We reveal unconventional and dynamically controlled ‘roaming’ dynamics in excited tyrosine that are beyond chemical intuition and compete with other ultrafast deactivation mechanisms. Our findings suggest that the roaming atoms are radicals that can lead to photodamage, offering a new perspective on the photostability and photodamage of biological systems.
Item Type: | Journal Article | ||||||||||||
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Subjects: | Q Science > QD Chemistry | ||||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Chemistry | ||||||||||||
Library of Congress Subject Headings (LCSH): | Tyrosine , Tyrosine -- Computer simulation, Photodegradation, Amino acids , Photochemistry | ||||||||||||
Journal or Publication Title: | Nature Chemistry | ||||||||||||
Publisher: | Nature Publishing Group | ||||||||||||
ISSN: | 1755-4330 | ||||||||||||
Official Date: | August 2022 | ||||||||||||
Dates: |
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Volume: | 14 | ||||||||||||
Page Range: | pp. 914-919 | ||||||||||||
DOI: | 10.1038/s41557-022-00950-z | ||||||||||||
Status: | Peer Reviewed | ||||||||||||
Publication Status: | Published | ||||||||||||
Reuse Statement (publisher, data, author rights): | This version of the article has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1038/s41557-022-00950-z. Use of this Accepted Version is subject to the publisher’s Accepted Manuscript terms of use https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms | ||||||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||||||
Date of first compliant deposit: | 3 January 2023 | ||||||||||||
Date of first compliant Open Access: | 3 January 2023 | ||||||||||||
RIOXX Funder/Project Grant: |
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