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: | , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2021-10-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-021-25831-w |
| _version_ | 1818423272140701696 |
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| author | Jonathan C. Greenhalgh Sarah A. Fahlberg Brian F. Pfleger Philip A. Romero |
| author_facet | Jonathan C. Greenhalgh Sarah A. Fahlberg Brian F. Pfleger Philip A. Romero |
| author_sort | Jonathan C. Greenhalgh |
| collection | DOAJ |
| description | 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 fatty alcohol production. |
| first_indexed | 2024-12-14T13:39:30Z |
| format | Article |
| id | doaj.art-c7cf4104a3534f20a86d3e06336ff293 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-12-14T13:39:30Z |
| publishDate | 2021-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-c7cf4104a3534f20a86d3e06336ff2932022-12-21T22:59:29ZengNature PortfolioNature Communications2041-17232021-10-0112111010.1038/s41467-021-25831-wMachine learning-guided acyl-ACP reductase engineering for improved in vivo fatty alcohol productionJonathan C. Greenhalgh0Sarah A. Fahlberg1Brian F. Pfleger2Philip A. Romero3Department of Biochemistry, University of Wisconsin-MadisonDepartment of Biochemistry, University of Wisconsin-MadisonDepartment of Chemical & Biological Engineering, University of Wisconsin-MadisonDepartment of Biochemistry, University of Wisconsin-MadisonFatty 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 fatty alcohol production.https://doi.org/10.1038/s41467-021-25831-w |
| spellingShingle | Jonathan C. Greenhalgh Sarah A. Fahlberg Brian F. Pfleger Philip A. Romero Machine learning-guided acyl-ACP reductase engineering for improved in vivo fatty alcohol production Nature Communications |
| title | Machine learning-guided acyl-ACP reductase engineering for improved in vivo fatty alcohol production |
| title_full | Machine learning-guided acyl-ACP reductase engineering for improved in vivo fatty alcohol production |
| title_fullStr | Machine learning-guided acyl-ACP reductase engineering for improved in vivo fatty alcohol production |
| title_full_unstemmed | Machine learning-guided acyl-ACP reductase engineering for improved in vivo fatty alcohol production |
| title_short | Machine learning-guided acyl-ACP reductase engineering for improved in vivo fatty alcohol production |
| title_sort | machine learning guided acyl acp reductase engineering for improved in vivo fatty alcohol production |
| url | https://doi.org/10.1038/s41467-021-25831-w |
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