Computationally optimizing the directed evolution of proteins

directed evolution;enzyme;genetic algorithm;library;mutagenesis;protein;recombination;schema

Voigt, Christopher Ashby ; Wang, Zhen-Gang (advisor)

University:California Institute of Technology

Department:Engineering and Applied Science

关键词: directed evolution;    enzyme;    genetic algorithm;    library;    mutagenesis;    protein;    recombination;    schema;   

Others  :  https://thesis.library.caltech.edu/3169/1/voigt_thesis.pdf

美国|英语

来源: Caltech THESIS

【 摘 要 】

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.