Abstract
Raman spectroscopy has been used to measure the concentration of a
pharmaceutically relevant model amine intermediate for positive
allosteric modulators of nicotinic acetylcholine receptor in a
ω-transaminase-catalyzed conversion. A model based on a one-dimensional
convolutional neural network was developed to translate raw data
augmented Raman spectra directly into substrate concentrations, with
which the conversion from ketone to amine by ω-transaminase could be
determined over time. The model showed very good predictive
capabilities, with R2 values higher than 0.99 for the
spectra included in the modeling and 0.964 for an independent dataset.
However, the model could not extrapolate outside the concentrations
specified by the model. The presented work shows the potential of Raman
spectroscopy as a real-time monitoring tool for biocatalytic reactions.
Original language | English |
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Article number | e3444 |
Journal | Biotechnology Progress |
Volume | 40 |
Issue number | 3 |
Number of pages | 13 |
ISSN | 8756-7938 |
DOIs | |
Publication status | Published - 2024 |
Keywords
- Raman spectroscopy
- Biocatalysis
- Chemometrics
- Real‐time monitoring
- Transaminase