2025
Of Revolutions and Roadblocks: The Emerging Role of Machine Learning in Biocatalysis
ACS Central Science. 2025. DOI : 10.1021/acscentsci.5c00949.Computer-assisted multilevel optimization of malonyl-CoA availability in Pseudomonas putida
Metabolic Engineering. 2025. Vol. 90, p. 165 – 177. DOI : 10.1016/j.ymben.2025.03.008.Data-driven protease engineering by DNA-recording and epistasis-aware machine learning
Nature Communications. 2025. Vol. 16, num. 1. DOI : 10.1038/s41467-025-60622-7.Permeabilisation of the Outer Membrane of Escherichia coli for Enhanced Transport of Complex Molecules
Microbial Biotechnology. 2025. Vol. 18, num. 3. DOI : 10.1111/1751-7915.70122. 2024
Enhanced Sequence-Activity Mapping and Evolution of Artificial Metalloenzymes by Active Learning
ACS Central Science. 2024. Vol. 10, num. 7, p. 1357 – 1370. DOI : 10.1021/acscentsci.4c00258.From sequence to function and back – High-throughput sequence-function mapping in synthetic biology
Current Opinion in Systems Biology. 2024. Vol. 37. DOI : 10.1016/j.coisb.2023.100499.2023
An Artificial Metalloenzyme for Atroposelective Metathesis**
Chemcatchem. 2023. Vol. 15, num. 23. DOI : 10.1002/cctc.202301113.Ultradeep characterisation of translational sequence determinants refutes rare-codon hypothesis and unveils quadruplet base pairing of initiator tRNA and transcript
Nucleic Acids Research. 2023. Vol. 5, num. 51, p. 2377 – 2396. DOI : 10.1093/nar/gkad040.2021
Systematic engineering of artificial metalloenzymes for new-to-nature reactions
Science Advances. 2021. Vol. 7, num. 4. DOI : 10.1126/sciadv.abe4208.2020
Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping
Nature Communications. 2020. Vol. 11, num. 1. DOI : 10.1038/s41467-020-17222-4.The Quest for Xenobiotic Enzymes: From New Enzymes for Chemistry to a Novel Chemistry of Life
ChemBioChem. 2020. Vol. 21, num. 16, p. 2241 – 2249. DOI : 10.1002/cbic.202000121.2019
Chemo-enzymatic cascades to produce cycloalkenes from bio-based resources
Nature Communications. 2019. Vol. 10, num. 1. DOI : 10.1038/s41467-019-13071-y.2018
E. coli surface display of streptavidin for directed evolution of an allylic deallylase
Chemical Science. 2018. Vol. 9, num. 24, p. 5383 – 5388. DOI : 10.1039/C8SC00484F.Artificial Metalloenzymes on the Verge of New-to-Nature Metabolism
Trends in Biotechnology. 2018. Vol. 36, num. 1, p. 60 – 72. DOI : 10.1016/j.tibtech.2017.10.003.2017
Combinatorial pathway optimization for streamlined metabolic engineering
Current Opinion in Biotechnology. 2017. Vol. 47, p. 142 – 151. DOI : 10.1016/j.copbio.2017.06.014.Biotin-independent strains of Escherichia coli for enhanced streptavidin production
Metabolic Engineering. 2017. Vol. 40, p. 33 – 40. DOI : 10.1016/j.ymben.2016.12.013.2016
Directed evolution of artificial metalloenzymes for in vivo metathesis
Nature. 2016. Vol. 537, p. 661 – 665. DOI : 10.1038/nature19114.Rationally reduced libraries for combinatorial pathway optimization minimizing experimental effort
Nature Communications. 2016. Vol. 7, num. 1. DOI : 10.1038/ncomms11163.Periplasmic Screening for Artificial Metalloenzymes
Methods in Enzymology; Elsevier, 2016. p. 539 – 556.
