English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Serial Femtosecond Crystallography at the X-ray Free Electron Laser (XFEL)sources enabled the imaging of the catalytic intermediates of the oxygenevolution reaction of Photosystem II. However, due to the incoherent transitionof the S-states, the resolved structures are a convolution from differentcatalytic states. Here, we train Decision Tree Classifier and K-mean clusteringmodels on Mn compounds obtained from the Cambridge Crystallographic Database topredict the S-state of the X-ray, XFEL, and CryoEm structures by predicting theMn's oxidation states in the oxygen evolving complex (OEC). The model agreesmostly with the XFEL structures in the dark S1 state. However, significantdiscrepancies are observed for the excited XFEL states (S2, S3, and S0) and thedark states of the X-ray and CryoEm structures. Furthermore, there is amismatch between the predicted S-states within the two monomers of the samedimer, mainly in the excited states. The model suggests that improving theresolution is crucial to precisely resolve the geometry of the illuminatedS-states to overcome the noncoherent S-state transition. In addition,significant radiation damage is observed in X-ray and CryoEM structures,particularly at the dangler Mn center (Mn4). Our model represents a valuabletool for investigating the electronic structure of the catalytic metal clusterof PSII to understand the water splitting mechanism.

Predicting the Oxidation States of Mn ions in the Oxygen Evolving Complex of Photosystem II Using Supervised and Unsupervised Machine Learning