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      Systematic engineering of artificial metalloenzymes for new-to-nature reactions

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          Abstract

          An E. coli platform for systematic engineering of artificial metalloenzymes that catalyze new-to-nature reactions is described.

          Abstract

          Artificial metalloenzymes (ArMs) catalyzing new-to-nature reactions could play an important role in transitioning toward a sustainable economy. While ArMs have been created for various transformations, attempts at their genetic optimization have been case specific and resulted mostly in modest improvements. To realize their full potential, methods to rapidly discover active ArM variants for ideally any reaction of interest are required. Here, we introduce a reaction-independent, automation-compatible platform, which relies on periplasmic compartmentalization in Escherichia coli to rapidly and reliably engineer ArMs based on the biotin-streptavidin technology. We systematically assess 400 ArM mutants for five bioorthogonal transformations involving different metals, reaction mechanisms, and reactants, which include novel ArMs for gold-catalyzed hydroamination and hydroarylation. Activity enhancements up to 15-fold highlight the potential of the systematic approach. Furthermore, we suggest smart screening strategies and build machine learning models that accurately predict ArM activity from sequence, which has crucial implications for future ArM development.

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          Deep learning in neural networks: An overview

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            Stochastic gradient boosting

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              Machine-learning-guided directed evolution for protein engineering

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                Author and article information

                Journal
                Sci Adv
                Sci Adv
                sciadv
                advances
                Science Advances
                American Association for the Advancement of Science
                2375-2548
                January 2021
                22 January 2021
                : 7
                : 4
                : eabe4208
                Affiliations
                [1 ]Department of Biosystems Science and Engineering, ETH Zurich, CH-4058 Basel, Switzerland.
                [2 ]National Centre of Competence in Research (NCCR) Molecular Systems Engineering, Basel, Switzerland.
                [3 ]Department of Chemistry, University of Basel, Mattenstrasse 24a, BPR 1096, CH-4002 Basel, Switzerland.
                Author notes
                [ * ]

                These authors contributed equally to this work.

                [ † ]

                Present address: Adolphe Merkle Institute Faculty of Science and Medicine, Université de Fribourg, Ch. des Verdiers, 4 1700 Fribourg, Switzerland.

                [ ]Corresponding author. Email: markus.jeschek@ 123456bsse.ethz.ch
                Author information
                https://orcid.org/0000-0001-9700-2384
                https://orcid.org/0000-0002-3814-8620
                https://orcid.org/0000-0003-4294-0247
                https://orcid.org/0000-0001-8602-5468
                https://orcid.org/0000-0003-1317-2461
                Article
                abe4208
                10.1126/sciadv.abe4208
                10964965
                33523952
                2ae61b07-606f-4584-91b6-bff9c3254f93
                Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

                History
                : 22 August 2020
                : 04 December 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000780, European Commission;
                Award ID: Madonna; grant no. 766975
                Funded by: FundRef http://dx.doi.org/10.13039/501100001711, Swiss National Science Foundation;
                Award ID: 31003A_179521
                Funded by: FundRef http://dx.doi.org/10.13039/501100001711, Swiss National Science Foundation;
                Award ID: 200020_182046
                Funded by: NCCR Molecular Systems Engineering;
                Categories
                Research Article
                Research Articles
                SciAdv r-articles
                Chemistry
                Synthetic Biology
                Synthetic Biology
                Custom metadata
                Anne Suarez

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