Algorithm-aided engineering of aliphatic halogenase WelO5* for the asymmetric late-stage functionalization of soraphens

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

doi:10.1038/s41467-022-27999-1

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.