Title:
Optimization of Recombination Methods and Expanding the Utility of Penicillin G Acylase

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dc.contributor.advisor Bommarius, Andreas S.
dc.contributor.author Loo, Bernard Liat Wen en_US
dc.contributor.committeeMember Hu, Wei-Shou
dc.contributor.committeeMember Lee, Jay
dc.contributor.committeeMember Lutz, Stefan
dc.contributor.committeeMember Prausnitz, Mark
dc.contributor.department Chemical Engineering en_US
dc.date.accessioned 2008-02-07T18:13:31Z
dc.date.available 2008-02-07T18:13:31Z
dc.date.issued 2007-11-02 en_US
dc.description.abstract Protein engineering can be performed by combinatorial techniques (directed evolution) and data-driven methods using machine-learning algorithms. The main characteristic of directed evolution (DE) is the application of an effective and efficient screen or selection on a diverse mutant library. As it is important to have a diverse mutant library for the success of DE, we compared the performance of DNA-shuffling and recombination PCR on fluorescent proteins using sequence information as well as statistical methods. We found that the diversity of the libraries DNA-shuffling and recombination PCR generates were dependent on type of skew primers used and sensitive to nucleotide identity levels between genes. DNA-shuffling and recombination PCR produced libraries with different crossover tendencies, suggesting that the two protocols could be used in combination to produce better libraries. Data-driven protein engineering uses sequence, structure and function data along with analyzed empirical activity information to guide library design. Boolean Learning Support Vector Machines (BLSVM) to identify interacting residues in fluorescent proteins and the gene templates were modified to preserve interactions post recombination. By site-directed mutagenesis, recombination and expression experiments, we validated that BLSVM can be used to identify interacting residues and increase the fraction of active proteins in the library. As an extension to the above experiments, DE was applied on monomeric Red Fluorescent Proteins to improve its spectral characteristics and structure-guided protein engineering was performed on penicillin G acylase (PGA), an industrially relevant catalyst, to change its substrate specificity. en_US
dc.description.degree Ph.D. en_US
dc.identifier.uri http://hdl.handle.net/1853/19728
dc.publisher Georgia Institute of Technology en_US
dc.subject Recombination protocols en_US
dc.subject Red fluorescent proteins en_US
dc.subject Penicillin g acylase en_US
dc.subject Substrate specificity en_US
dc.subject Support vector machines en_US
dc.subject Boolean learning en_US
dc.subject.lcsh Protein engineering
dc.subject.lcsh Molecular evolution
dc.subject.lcsh Genetic engineering
dc.subject.lcsh Biotechnology
dc.title Optimization of Recombination Methods and Expanding the Utility of Penicillin G Acylase en_US
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Bommarius, Andreas S.
local.contributor.corporatename School of Chemical and Biomolecular Engineering
local.contributor.corporatename College of Engineering
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relation.isOrgUnitOfPublication 6cfa2dc6-c5bf-4f6b-99a2-57105d8f7a6f
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
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