The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Biocatalysis: Enzymatic Synthesis for Industrial Applications
Open accessAbstract
Biocatalysis has found numerous applications in various fields as an alternative to chemical catalysis. The use of enzymes in organic synthesis, especially to make chiral compounds for pharmaceuticals as well for the flavors and fragrance industry, are the most prominent examples. In addition, biocatalysts are used on a large scale to make specialty and even bulk chemicals. This review intends to give illustrative examples in this field with a special focus on scalable chemical production using enzymes. It also discusses the opportunities and limitations of enzymatic syntheses using distinct examples and provides an outlook on emerging enzyme classes.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
An engineered PET depolymerase to break down and recycle plastic bottles
Tournier, V., Topham, C. M., Gilles, A., David, B., Folgoas, C., Moya-Leclair, E., Kamionka, E., Desrousseaux, M.-L., Texier, H., Gavalda, S., et al. (2020) · Nature · doi:10.1038/s41586-020-2149-4 · Cited by 2,176
Biosynthesis of Monomers for Plastics from Renewable Oils
Lu, W., Ness, J. E., Xie, W., Zhang, X., Minshull, J., & Gross, R. A. (2010) · Journal of the American Chemical Society · doi:10.1021/ja107707v · Cited by 212
Cited by
Machine Learning on a Robotic Platform for the Design of Polymer–Protein Hybrids
Tamasi, M. J., Patel, R. A., Borca, C. H., Kosuri, S., Mugnier, H., Upadhya, R., Murthy, N. S., Webb, M. A., & Gormley, A. J. (2022) · Advanced Materials · doi:10.1002/adma.202201809 · Cited by 177
Machine learning modeling of family wide enzyme-substrate specificity screens
Goldman, S., Das, R., Yang, K. K., & Coley, C. W. (2022) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1009853 · Cited by 120
Computational scoring and experimental evaluation of enzymes generated by neural networks
Johnson, S. R., Fu, X., Viknander, S., Goldin, C., Monaco, S., Zelezniak, A., & Yang, K. K. (2025) · Nature Biotechnology · doi:10.1038/s41587-024-02214-2 · Cited by 99
Opportunities and Challenges of Metal–Organic Framework Micro/Nano Reactors for Cascade Reactions
Wu, P., Zhao, Y., Zhang, X., Fan, Y., Zhang, S., Zhang, W., & Huo, F. (2023) · JACS Au · doi:10.1021/jacsau.3c00344 · Cited by 48
Protein representations: Encoding biological information for machine learning in biocatalysis
Harding-Larsen, D., Funk, J., Madsen, N. G., Gharabli, H., Acevedo-Rocha, C. G., Mazurenko, S., & Welner, D. H. (2024) · Biotechnology Advances · doi:10.1016/j.biotechadv.2024.108459 · Cited by 38
Metadata
- Authors
- Wu, S., Snajdrova, R., Moore, J. C., Baldenius, K., & Bornscheuer, U. T.
- Venue
- Angewandte Chemie International Edition
- Publisher
- Wiley
- Published
- 2020-08-17
- Volume
- 60
- Issue
- 1
- Pages
- 88-119
- ISSN
- 1433-7851 (ISSN-L)
- 1521-3773
- OpenAlex
- W3035847987
- Cited by
- 1,422
- References
- 2
- FWCI
- 47.64
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
