Published July 1, 2026
| Version v1
Dataset
Open
Dataset for Iterative and data-driven ortholog mining enables reliable discovery of stereoselective ketoreductases
Authors/Creators
-
Stockinger, Peter
(Data manager)1, 2
-
Niklaus, Michael
(Researcher)2
- Yar, Kevin (Data collector)2
- Imstepf, Nicolas (Data collector)2, 1, 3
- Pastierikova, Ivana (Data collector)2
- Küng, Jasmin2
- Hanlon, Steven Paul (Researcher)4
- Iding, Hans (Researcher)4
- Honda Malca, Sumire (Project manager)2
-
Buller, Rebecca
(Supervisor)2, 1
-
1.
University of Bern
-
2.
ZHAW Zurich University of Applied Sciences
-
3.
Delft University of Technology
- 4. Roche
Description
The Zenodo repository contains the complete experimental datasets underlying all main-text and Supporting Information figures and tables of the manuscript, including raw and processed GC-FID and chiral HPLC-UV peak data (retention times, peak areas), external calibration curves, calculated conversions (with means and standard deviations), and nanoDSF-derived melting temperatures for ketoreductase (KRED) ortholog variants. Data cover two iterative rounds of ortholog mining - an initial broad sampling of 48 evolutionarily distant variants and a refined sampling of 60 phylogenetically closer orthologs - alongside substrate-scope studies on five pharmaceutically relevant prochiral ketones (1a–5a).
Files
README.txt
Files
(1.4 MB)
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Additional details
Funding
- Swiss National Science Foundation
- NCCR Catalysis (phase II) 225147
Software
- Repository URL
- https://github.com/Buller-Lab/Ssal-KRED_orthologs
- Programming language
- Python