The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Automated Structure- and Sequence-Based Design of Proteins for High Bacterial Expression and Stability
Open accessAbstract
Upon heterologous overexpression, many proteins misfold or aggregate, thus resulting in low functional yields. Human acetylcholinesterase (hAChE), an enzyme mediating synaptic transmission, is a typical case of a human protein that necessitates mammalian systems to obtain functional expression. We developed a computational strategy and designed an AChE variant bearing 51 mutations that improved core packing, surface polarity, and backbone rigidity. This variant expressed at ∼2,000-fold higher levels in E. coli compared to wild-type hAChE and exhibited 20°C higher thermostability with no change in enzymatic properties or in the active-site configuration as determined by crystallography. To demonstrate broad utility, we similarly designed four other human and bacterial proteins. Testing at most three designs per protein, we obtained enhanced stability and/or higher yields of soluble and active protein in E. coli. Our algorithm requires only a 3D structure and several dozen sequences of naturally occurring homologs, and is available at http://pross.weizmann.ac.il.
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Basic local alignment search tool
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990) · Journal of Molecular Biology · doi:10.1006/jmbi.1990.9999 · Cited by 98,669
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The sirtuin SIRT6 regulates lifespan in male mice
Kanfi, Y., Naiman, S., Amir, G., Peshti, V., Zinman, G., Nahum, L., Bar-Joseph, Z., & Cohen, H. Y. (2012) · Nature · doi:10.1038/nature10815 · Cited by 1,059
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
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Advances 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
Mega-scale experimental analysis of protein folding stability in biology and design
Tsuboyama, K., Dauparas, J., Chen, J., Laine, E., Mohseni Behbahani, Y., Weinstein, J. J., Mangan, N. M., Ovchinnikov, S., & Rocklin, G. J. (2023) · Nature · doi:10.1038/s41586-023-06328-6 · Cited by 350
Jia, B., & Jeon, C. O. (2016) · Open Biology · doi:10.1098/rsob.160196 · Cited by 295
Transfer learning to leverage larger datasets for improved prediction of protein stability changes
Dieckhaus, H., Brocidiacono, M., Randolph, N. Z., & Kuhlman, B. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2314853121 · Cited by 205
Principles for computational design of binding antibodies
Baran, D., Pszolla, M. G., Lapidoth, G. D., Norn, C., Dym, O., Unger, T., Albeck, S., Tyka, M. D., & Fleishman, S. J. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1707171114 · Cited by 136
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Metadata
- Authors
- Goldenzweig, A., Goldsmith, M., Hill, S. E., Gertman, O., Laurino, P., Ashani, Y., Dym, O., Unger, T., Albeck, S., Prilusky, J., Lieberman, R. L., Aharoni, A., Silman, I., Sussman, J. L., Tawfik, D. S., & Fleishman, S. J.
- Venue
- Molecular Cell
- Publisher
- Elsevier BV
- Published
- 2016-07
- Volume
- 63
- Issue
- 2
- Pages
- 337-346
- ISSN
- 1097-2765 (ISSN-L)
- OpenAlex
- W2473135273
- Cited by
- 572
- References
- 4
- FWCI
- 13.39
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Goldenzweig, A., Goldsmith, M., Hill, S. E., Gertman, O., Laurino, P., Ashani, Y., Dym, O., Unger, T., Albeck, S., Prilusky, J., Lieberman, R. L., Aharoni, A., Silman, I., Sussman, J. L., Tawfik, D. S., & Fleishman, S. J. (2016). Automated Structure- and Sequence-Based Design of Proteins for High Bacterial Expression and Stability. Molecular Cell. https://doi.org/10.1016/j.molcel.2016.06.012
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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.
