0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessMolecular hydrogen (H 2 ) is considered an eco-friendly future energy-carrier and an alternative to fossil fuel 1 and thus, major efforts are directed towards identifying efficient and economical hydrogen catalysts. 2,3 Efficient hydrogen catalysis is used by many microorganisms, some of them producing H 2 from organic materials and others consuming it. 4-6 To metabolize H 2 , these microorganisms use enzymes called hydrogenases. 7,8 For the future development of efficient catalysts a detailed analysis of the catalytic mechanisms of such hydrogenases is required and existing analytical techniques could not provide a full understanding. 9 Consequently, new analytical technologies are of utmost importance to unravel natures’ blueprints for highly efficient hydrogen catalysts. Here, we introduce signal-enhanced or hyperpolarized, nuclear magnetic resonance (NMR) to study hydrogenases under turnover conditions. So far undiscovered hydrogen species of the catalytic cycle of [Fe]-hydrogenases, are revealed and thus, extend the knowledge regarding this class of enzymes. These findings pave new pathways for the exploration of novel hydrogen metabolisms in vivo . We furthermore envision that the results contribute to the rational design of future catalysts to solve energy challenges of our society.
Lukas Kaltschnee, Andrey N. Pravdivtsev, Manuel Gehl, Gangfeng Huang, Georgi L. Stoychev, Christoph Riplinger, Maximilian Keitel, Frank Neese, Jan‐Bernd Hövener, Alexander A. Auer, Christian Griesinger, Seigo Shima, Stefan Glöggler (2023). Sensitivity-enhanced magnetic resonance reveals hydrogen intermediates during active [Fe]-hydrogenase catalysis. bioRxiv (Cold Spring Harbor Laboratory), DOI: 10.1101/2023.05.10.540199.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Preprint
Year
2023
Authors
13
Datasets
0
Total Files
0
Language
English
Journal
bioRxiv (Cold Spring Harbor Laboratory)
DOI
10.1101/2023.05.10.540199
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access