Biocatalysts offer advantages over their chemical counterparts in terms of their high enantioselectivity and the opportunity to develop more environmentally friendly processes. However, the widespread adoption of biocatalytic processes is hampered by the long development times for enzymes with novel and sufficient activity and adequate stability under operating conditions. Protein engineering, while extremely useful for modifying the properties of protein catalysts in select cases, still cannot be performed rapidly enough for many applications. In order for biocatalysts to become a competitive alternative to chemical catalysts, new tools to make the tailoring of biocatalysts by protein engineering methods speedier and more efficient are necessary. The aim of this work was to develop methods to aid in the faster production of novel biocatalysts.
Protein engineering involves two steps: the generation of diversity and the screening or selection of variants with the desired properties. Both of these must be targeted to create a faster protein engineering process. In the case of the former, this work sought to clone and overexpress some template enzymes which would create smaller, more manageable libraries of mutants with a higher likelihood of function by the manipulation of a few focused amino acid residues. For the latter, this work developed and validated a Monte-Carlo simulation model of pooling to increase screening throughput and created a set of vectors to aid in high-throughput screening by eliminating unwanted mutants from the assay procedure entirely.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/7511 |
| Date | 14 November 2005 |
| Creators | Polizzi, Karen Marie |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | 1513500 bytes, application/pdf |
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