Voigt, Christopher Ashby (2003) Computationally optimizing the directed evolution of proteins. Dissertation (Ph.D.), California Institute of Technology. http://resolver.caltech.edu/CaltechETD:etd-08192002-161141
Directed evolution has proven a successful strategy for protein engineering. To accelerate the discovery process, we have developed several computational methods to optimize the mutant libraries by targeting specific residues for mutagenesis, and subunits for recombination. In achieving this goal, a statistical model was first used to study the dynamics of directed evolution as a search algorithm. These simulations improved our understanding of the relationship between parameters describing the search space (e.g., interactions between amino acids) and experimental search parameters (e.g., mutation rate and library size). Based on these simulations, a more detailed model was used to calculate the structural tolerance of each residue to amino acid substitutions. Further, a computational model was developed to optimize recombination experiments, based on the three-dimensional structure. Together, these computational techniques represent a major step towards information-driven combinatorial protein design.
|Item Type:||Thesis (Dissertation (Ph.D.))|
|Subject Keywords:||directed evolution; enzyme; genetic algorithm; library; mutagenesis; protein; recombination; schema|
|Degree Grantor:||California Institute of Technology|
|Division:||Engineering and Applied Science|
|Thesis Availability:||Public (worldwide access)|
|Defense Date:||25 July 2002|
|Default Usage Policy:||No commercial reproduction, distribution, display or performance rights in this work are provided.|
|Deposited By:||Imported from ETD-db|
|Deposited On:||04 Sep 2002|
|Last Modified:||12 Dec 2014 18:02|
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