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|Publication type:||Article in scientific journal|
|Type of review:||Peer review (publication)|
|Title:||Algorithm-aided engineering of aliphatic halogenase WelO5* for the asymmetric late-stage functionalization of soraphens|
Malca, Sumire Honda
Turner, Nicholas J.
Bornscheuer, Uwe T.
Le Chapelain, Camille
|Published in:||Nature Communications|
|Publisher / Ed. Institution:||Nature Publishing Group|
|Subject (DDC):||660.6: Biotechnology|
|Abstract:||Late-stage functionalization of natural products offers an elegant route to create novel entities in a relevant biological target space. In this context, enzymes capable of halogenating sp3 carbons with high stereo- and regiocontrol under benign conditions have attracted particular attention. Enabled by a combination of smart library design and machine learning, we engineer the iron/α-ketoglutarate dependent halogenase WelO5* for the late-stage functionalization of the complex and chemically difficult to derivatize macrolides soraphen A and C, potent anti-fungal agents. While the wild type enzyme WelO5* does not accept the macrolide substrates, our engineering strategy leads to active halogenase variants and improves upon their apparent kcat and total turnover number by more than 90-fold and 300-fold, respectively. Notably, our machine-learning guided engineering approach is capable of predicting more active variants and allows us to switch the regio-selectivity of the halogenases facilitating the targeted analysis of the derivatized macrolides’ structure-function activity in biological assays.|
|Fulltext version:||Published version|
|License (according to publishing contract):||CC BY 4.0: Attribution 4.0 International|
|Departement:||Life Sciences and Facility Management|
|Organisational Unit:||Institute of Chemistry and Biotechnology (ICBT)|
|Published as part of the ZHAW project:||PgB P-14 Engineered Halogenases|
|Appears in collections:||Publikationen Life Sciences und Facility Management|
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|2022_Buechler-etal_Algorithm-aided-engineering-aliphatic-halogenase-WelO5.pdf||2.3 MB||Adobe PDF|
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