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Improving protein expression, stability, and function with ProteinMPNN
Open accessPreprint — published as 10.1021/jacs.3c10941
Abstract
Natural proteins are highly optimized for function, but are often difficult to produce at a scale suitable for biotechnological applications due to poor expression in heterologous systems, limited solubility, and sensitivity to temperature. Thus, a general method that improves the physical properties of native proteins while maintaining function could have wide utility for protein-based technologies. Here we show that the deep neural network ProteinMPNN together with evolutionary and structural information provides a route to increasing protein expression, stability, and function. For both myoglobin and tobacco etch virus (TEV) protease, we generated designs with improved expression, elevated melting temperatures, and improved function. For TEV protease, we identified multiple designs with improved catalytic activity as compared to the parent sequence and previously reported TEV variants. Our approach should be broadly useful for improving the expression, stability, and function of biotechnologically important proteins.
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Highly accurate protein structure prediction with AlphaFold
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Metadata
- Authors
- Sumida, K. H., Núñez-Franco, R., Kalvet, I., Pellock, S. J., Wicky, B. I. M., Milles, L. F., Dauparas, J., Wang, J., Kipnis, Y., Jameson, N., Kang, A., De La Cruz, J., Sankaran, B., Bera, A. K., Jiménez-Osés, G., & Baker, D.
- Affiliations
- University of Washington (US)
- Howard Hughes Medical Institute (US)
- Lawrence Berkeley National Laboratory (US)
- Corresponding author
- Baker, David
- ORCID
- Venue
- Journal of the American Chemical Society
- Publisher
- openRxiv
- Published
- 2023-10-03
- Volume
- 146
- Issue
- 3
- Pages
- 2054-2061
- ISSN
- 0002-7863 (ISSN-L)
- PMC
- PMC10811672
- OpenAlex
- W4390778100
- Cited by
- 344
- References
- 1
- Citations by year
- 2026: 146 · 2025: 128 · 2024: 70
- FWCI
- 46.83
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Journal of the American Chemical Society (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- Funders
- Schmidt Futures
- National Science Foundation (HDTRA1-19-1-0003, DEAC02-05CH11231, 1629214, 1937533)
- Howard Hughes Medical Institute
- U.S. Department of Energy (-AC02-05CH11231, 05CH11231, DE AC02 05CH11231, DE-AC02-)
- Bill and Melinda Gates Foundation (OPP1156262)
- Alfred P. Sloan Foundation (g-2021-16899, DE-AC02-05CH11231)
- Washington Research Foundation
- European Molecular Biology Organization (ALTF 139-2018, ALTF 1047-2019)
- University of Washington
- Open Philanthropy Project
- Human Frontier Science Program (LT000395/2020C, LT000838/2018-C)
- Ikerbasque, Basque Foundation for Science (PID2021-125946OB-I00)
- National Institutes of Health
- Defense Advanced Research Projects Agency (HR0011-21-2-0012, DE-AC02-05CH11231)
- Defense Threat Reduction Agency (HDTRA1-19-1-0003)
- Advanced Research Projects Agency - Energy (2459-1671)
- Office of Science (DEAC02–05CH11231, AC02-05CH11231, DE-AC02)
- Agencia Estatal de Investigación (CEX2021-001136-S, PID2021‐125946OB‐I00)
- National Institute of General Medical Sciences (R35GM124773)
- National Institute of Allergy and Infectious Diseases (R0AI160052, R01AI160052)
- Division of Chemistry (1629214, DE-AC02-05CH11231, CHE 1629214)
- Division of Biological Infrastructure (DBI 1937533)
- Basic Energy Sciences (DE-AC02, DE-AC02-05CH11231., AC02–05CH11231)
- Air Force Office of Scientific Research
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Enzyme Catalysis and Immobilization
- Keywords
- ProteinMPNN, protein design, protein expression, protein stability, protein function, myoglobin, tobacco etch virus protease, deep neural network, protein solubility, thermal stability, catalytic activity, heterologous expression
- MeSH terms
- Endopeptidases, Recombinant Fusion Proteins, Temperature
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