The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Computational Enzyme Design
Abstract
Recent developments in computational chemistry and biology have come together in the “inside‐out” approach to enzyme engineering. Proteins have been designed to catalyze reactions not previously accelerated in nature. Some of these proteins fold and act as catalysts, but the success rate is still low. The achievements and limitations of the current technology are highlighted and contrasted to other protein engineering techniques. On its own, computational “inside‐out” design can lead to the production of catalytically active and selective proteins, but their kinetic performances fall short of natural enzymes. When combined with directed evolution, molecular dynamics simulations, and crowd‐sourced structure‐prediction approaches, however, computational designs can be significantly improved in terms of binding, turnover, and thermal stability.
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Cites
Predicting protein structures with a multiplayer online game
Cooper, S., Khatib, F., Treuille, A., Barbero, J., Lee, J., Beenen, M., Leaver-Fay, A., Baker, D., Popović, Z., & players, F. (2010) · Nature · doi:10.1038/nature09304 · Cited by 1,368
Self-citationStructure of HIV-1 gp120 V1/V2 domain with broadly neutralizing antibody PG9
McLellan, J. S., Pancera, M., Carrico, C., Gorman, J., Julien, J.-P., Khayat, R., Louder, R., Pejchal, R., Sastry, M., Dai, K., et al. (2011) · Nature · doi:10.1038/nature10696 · Cited by 830
Computational Design of Proteins Targeting the Conserved Stem Region of Influenza Hemagglutinin
Fleishman, S. J., Whitehead, T. A., Ekiert, D. C., Dreyfus, C., Corn, J. E., Strauch, E.-M., Wilson, I. A., & Baker, D. (2011) · Science · doi:10.1126/science.1202617 · Cited by 585
Self-citationRadzicka, A., & Wolfenden, R. (1996) · Journal of the American Chemical Society · doi:10.1021/ja954077c · Cited by 484
Cited by
The coming of age of de novo protein design
Huang, P.-S., Boyken, S. E., & Baker, D. (2016) · Nature · doi:10.1038/nature19946 · Cited by 1,478
Self-citationAdvances in protein structure prediction and design
Kuhlman, B., & Bradley, P. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-019-0163-x · Cited by 806
Protein Conformational Populations and Functionally Relevant Substates
Ramanathan, A., Savol, A., Burger, V., Chennubhotla, C. S., & Agarwal, P. K. (2014) · Accounts of Chemical Research · doi:10.1021/ar400084s · Cited by 110
Protein design via deep learning
Ding, W., Nakai, K., & Gong, H. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac102 · Cited by 66
Turzo, S. B. A., Seffernick, J. T., Rolland, A. D., Donor, M. T., Heinze, S., Prell, J. S., Wysocki, V. H., & Lindert, S. (2022) · Nature Communications · doi:10.1038/s41467-022-32075-9 · Cited by 47
Metadata
- Authors
- Kiss, G., Çelebi‐Ölçüm, N., Moretti, R., Baker, D., & Houk, K. N.
- Venue
- Angewandte Chemie International Edition
- Publisher
- Wiley
- Published
- 2013-03-25
- Volume
- 52
- Issue
- 22
- Pages
- 5700-5725
- ISSN
- 1433-7851 (ISSN-L)
- 1521-3773
- OpenAlex
- W2162943526
- Cited by
- 492
- References
- 4
- FWCI
- 21.11
- Type
- journal article
- Language
- en
- Open access
- closed
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