Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-23998
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
Authors: Büchler, Johannes
Malca, Sumire Honda
Patsch, David
Voss, Moritz
Turner, Nicholas J.
Bornscheuer, Uwe T.
Allemann, Oliver
Le Chapelain, Camille
Lumbroso, Alexandre
Loiseleur, Olivier
Buller, Rebecca
et. al: No
DOI: 10.1038/s41467-022-27999-1
10.21256/zhaw-23998
Published in: Nature Communications
Volume(Issue): 13
Issue: 371
Issue Date: 18-Jan-2022
Publisher / Ed. Institution: Nature Publishing Group
ISSN: 2041-1723
Language: English
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.
URI: https://digitalcollection.zhaw.ch/handle/11475/23998
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
NCCR Catalysis
Appears in collections:Publikationen Life Sciences und Facility Management

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Büchler, J., Malca, S. H., Patsch, D., Voss, M., Turner, N. J., Bornscheuer, U. T., Allemann, O., Le Chapelain, C., Lumbroso, A., Loiseleur, O., & Buller, R. (2022). Algorithm-aided engineering of aliphatic halogenase WelO5* for the asymmetric late-stage functionalization of soraphens. Nature Communications, 13(371). https://doi.org/10.1038/s41467-022-27999-1
Büchler, J. et al. (2022) ‘Algorithm-aided engineering of aliphatic halogenase WelO5* for the asymmetric late-stage functionalization of soraphens’, Nature Communications, 13(371). Available at: https://doi.org/10.1038/s41467-022-27999-1.
J. Büchler et al., “Algorithm-aided engineering of aliphatic halogenase WelO5* for the asymmetric late-stage functionalization of soraphens,” Nature Communications, vol. 13, no. 371, Jan. 2022, doi: 10.1038/s41467-022-27999-1.
BÜCHLER, Johannes, Sumire Honda MALCA, David PATSCH, Moritz VOSS, Nicholas J. TURNER, Uwe T. BORNSCHEUER, Oliver ALLEMANN, Camille LE CHAPELAIN, Alexandre LUMBROSO, Olivier LOISELEUR und Rebecca BULLER, 2022. Algorithm-aided engineering of aliphatic halogenase WelO5* for the asymmetric late-stage functionalization of soraphens. Nature Communications. 18 Januar 2022. Bd. 13, Nr. 371. DOI 10.1038/s41467-022-27999-1
Büchler, Johannes, Sumire Honda Malca, David Patsch, Moritz Voss, Nicholas J. Turner, Uwe T. Bornscheuer, Oliver Allemann, et al. 2022. “Algorithm-Aided Engineering of Aliphatic Halogenase WelO5* for the Asymmetric Late-Stage Functionalization of Soraphens.” Nature Communications 13 (371). https://doi.org/10.1038/s41467-022-27999-1.
Büchler, Johannes, et al. “Algorithm-Aided Engineering of Aliphatic Halogenase WelO5* for the Asymmetric Late-Stage Functionalization of Soraphens.” Nature Communications, vol. 13, no. 371, Jan. 2022, https://doi.org/10.1038/s41467-022-27999-1.


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