Enhanced Sequence-Activity Mapping and Evolution of Artificial Metalloenzymes by Active Learning-Reference-Cited by-同舟云学术

Enhanced Sequence-Activity Mapping and Evolution of Artificial Metalloenzymes by Active Learning

Published:2024-05-22 Issue:7 Volume:10 Page:1357-1370
ISSN:2374-7943
Container-title:ACS Central Science
language:en
Short-container-title:ACS Cent. Sci.

Author:

Vornholt Tobias¹²^ORCID,Mutný Mojmír³,Schmidt Gregor W.¹,Schellhaas Christian¹^ORCID,Tachibana Ryo⁴^ORCID,Panke Sven¹²,Ward Thomas R.²⁴^ORCID,Krause Andreas³,Jeschek Markus¹⁵

Affiliation:

1. Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland

2. National Centre of Competence in Research (NCCR) Molecular Systems Engineering, 4056 Basel,Switzerland

3. Department of Computer Science, ETH Zurich, Andreasstrasse 5, 8092 Zurich, Switzerland

4. Department of Chemistry, University of Basel, Mattenstrasse 24a, 4058 Basel, Switzerland

5. Institute of Microbiology, University of Regensburg, Universitätsstraße 31, 93053 Regensburg, Germany

Funder

Naito Foundation

NCCR Catalysis

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acscentsci.4c00258

Reference64 articles.

1. Machine-learning-guided directed evolution for protein engineering

2. Machine Learning in Enzyme Engineering

3. Machine learning to navigate fitness landscapes for protein engineering

4. Machine-Learning-Guided Mutagenesis for Directed Evolution of Fluorescent Proteins

5. Low-N protein engineering with data-efficient deep learning

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