| Type of Document |
Dissertation |
| Author |
Voigt, Christopher Ashby
|
| URN |
etd-08192002-161141 |
| Persistent URL |
http://resolver.caltech.edu/CaltechETD:etd-08192002-161141 |
| Title |
Computationally optimizing the directed evolution of proteins |
| Degree |
PhD |
| Option |
Aeronautics |
| Advisory Committee |
| Advisor Name |
Title |
| Douglas Rees |
Committee Chair |
| Frances Arnold |
Committee Member |
| Richard Roberts |
Committee Member |
| Stephen Mayo |
Committee Member |
| Walter Fontana |
Committee Member |
| Zhen-Gang Wang |
Committee Member |
|
| Keywords |
- enzyme
- recombination
- genetic algorithm
- schema
- library
- mutagenesis
- protein
- directed evolution
|
| Date of Defense |
2002-07-25 |
| Availability |
unrestricted |
Abstract
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.
|
| Files |
| Filename |
Size |
Approximate Download Time
(Hours:Minutes:Seconds)
|
| 28.8 Modem |
56K Modem |
ISDN (64 Kb) |
ISDN (128 Kb) |
Higher-speed Access |
| |
voigt_thesis.pdf |
45.69 Mb |
03:31:30 |
01:48:46 |
01:35:10 |
00:47:35 |
00:04:03 |
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