Revolutionising the design and analysis of protein engineering experiments using fractional factorial design Article Swipe
Steven P. D. Harborne
,
Duncan Wotherspoon
,
Jessica Michie
,
Alasdair McComb
,
Tommi Kotila
,
Steven G. Gilmour
,
Adrian Goldman
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1101/298273
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1101/298273
Protein engineering is one of the foundations of biotechnology, used to increase protein stability, re-assign the catalytic properties of enzymes or increase the interaction affinity between antibody and target. To date, strategies for protein engineering have focussed on systematic, random or computational methods for introducing new mutations. Here, we introduce the statistical approach of fractional factorial design as a convenient and powerful tool for the design and analysis of protein mutations, allowing sampling of a large mutational space whilst minimising the tests to be done. Our test case is the integral membrane protein, Acridine resistance subunit B (AcrB), part of the AcrAB-TolC multi-protein complex, a multi-drug efflux pump of Gram-negative bacteria. E. coli AcrB is naturally histidine-rich, meaning that it is a common contaminant in the purification of recombinantly expressed, histidine-tagged membrane proteins. Coupled with the ability of AcrB to crystallise from picogram quantities causing false positives in 2-D and 3-D crystallisation screening, AcrB contamination represents a significant hindrance to the determination of new membrane protein structures. Here, we demonstrate the use of fractional factorial design for protein engineering, identifying the most important residues involved in the interaction between AcrB and nickel resin. We demonstrate that a combination of spatially close, but sequentially distant histidine residues are important for nickel binding, which were different from those predicted a priori . Fractional factorial methodology has the ability to decrease the time and material costs associated with protein engineering whilst expanding the depth of mutational space explored; a revolutionary concept. Significance statement Protein engineering is important for the production of enzymes for bio-manufacturing, stabilised protein for research and production of therapeutic antibodies against human diseases. Here, we introduce a statistical method that can reduce the time and cost required to perform protein engineering. We validate our approach experimentally using the multi-drug efflux pump AcrB, a target for understanding drug-resistance in pathogenic bacteria, but also a persistent contaminant in the purification of membrane proteins from E. coli . This provides a general method for increasing the efficiency of protein engineering.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/298273
- https://www.biorxiv.org/content/biorxiv/early/2018/04/16/298273.full.pdf
- OA Status
- green
- Cited By
- 3
- References
- 28
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2796637348
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2796637348Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/298273Digital Object Identifier
- Title
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Revolutionising the design and analysis of protein engineering experiments using fractional factorial designWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-04-16Full publication date if available
- Authors
-
Steven P. D. Harborne, Duncan Wotherspoon, Jessica Michie, Alasdair McComb, Tommi Kotila, Steven G. Gilmour, Adrian GoldmanList of authors in order
- Landing page
-
https://doi.org/10.1101/298273Publisher landing page
- PDF URL
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https://www.biorxiv.org/content/biorxiv/early/2018/04/16/298273.full.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.biorxiv.org/content/biorxiv/early/2018/04/16/298273.full.pdfDirect OA link when available
- Concepts
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Fractional factorial design, Protein engineering, Histidine, Computational biology, False positive paradox, Factorial experiment, Biochemistry, Protein design, Chemistry, Biotechnology, Biology, Mathematics, Enzyme, Protein structure, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
- Citations by year (recent)
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2021: 2, 2020: 1Per-year citation counts (last 5 years)
- References (count)
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28Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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