Machine learning-guided acyl-ACP reductase engineering for improved in vivo fatty alcohol production
Fatty acyl reductases (FARs) are critical enzymes in the biosynthesis of fatty alcohols and have the ability to directly acces acyl-ACP substrates. Here, authors couple machine learning-based protein engineering framework with gene shuffling to optimize a FAR for the activity on acyl-ACP and improve...
Main Authors: | Jonathan C. Greenhalgh, Sarah A. Fahlberg, Brian F. Pfleger, Philip A. Romero |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2021-10-01
|
Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-021-25831-w |
Similar Items
-
The Plant Fatty Acyl Reductases
by: Xuanhao Zhang, et al.
Published: (2022-12-01) -
An engineered variant of MECR reductase reveals indispensability of long-chain acyl-ACPs for mitochondrial respiration
by: M. Tanvir Rahman, et al.
Published: (2023-02-01) -
EnZymClass: Substrate specificity prediction tool of plant acyl-ACP thioesterases based on ensemble learning
by: Deepro Banerjee, et al.
Published: (2022-01-01) -
Insights into Acinetobacter baumannii fatty acid synthesis 3-oxoacyl-ACP reductases
by: Emily M. Cross, et al.
Published: (2021-03-01) -
Biophysical and structural studies reveal marginal stability of a crucial hydrocarbon biosynthetic enzyme acyl ACP reductase
by: Ashima Sharma, et al.
Published: (2021-06-01)