Development and Applications of Computational Enzyme Engineering Tools

Open Access
Grisewood, Matthew Jeffery
Graduate Program:
Chemical Engineering
Doctor of Philosophy
Document Type:
Date of Defense:
January 16, 2018
Committee Members:
  • Costas D Maranas, Dissertation Advisor/Co-Advisor
  • Costas D Maranas, Committee Chair/Co-Chair
  • Michael John Janik, Committee Member
  • Howard M Salis, Committee Member
  • James Gregory Ferry, Outside Member
  • Iterative Protein Redesign and Optimization
  • IPRO
  • Computational
  • Enzyme
  • Redesign
  • Methyl-coenzyme M reductase
  • acyl-ACP thioesterase
  • Mcr
  • 'TesA
  • OptZyme
  • Optimization
  • beta-glucuronidase
  • Protein engineering
  • Specificity
  • Activity
Proteins are biological polymers that have diverse functions, including antibodies that protect the body from viruses, transport proteins that regulate intracellular ion concentrations, and enzymes that catalyze chemical reactions. Despite their natural prevalence, many instances still remain where an environmentally available protein does not exist, or is not known, for a given application. In these instances, it is possible to use protein engineering techniques to address a specific application. While purely experimental approaches are readily available to engineer proteins, these methods are often laborious or infeasible for more complicated systems. Computational protein engineering procedures can screen larger numbers of protein variants and direct the designed variants to promising regions of the sequence space. The Iterative Protein Redesign and Optimization procedure (IPRO) is a computational protein engineering tool that incorporates random backbone perturbations with deterministic amino acid selection procedures, followed by several steps to refine the protein-ligand structure, to improve or reduce binding for a given target, or multiple targets. First, relationships were derived between computationally-accessible interaction energies and enzyme catalytic properties, namely KM, kcat, and kcat/KM. Through the use of these relationships, which were validated using existing literature, a new computational procedure named OptZyme was developed to redesign enzymes using the IPRO framework. Several methods for diverse applications, ranging from de novo antibody design to binding site translocation, incorporated the IPRO framework and were assembled into a single platform so that these programs can be more easily accessed and used by users. OptZyme was used within this updated platform to improve substrate specificity (i.e., KM) for medium-chain fatty acyl-ACPs. By tailoring the chain length of the substrate, the chemical properties of the produced free fatty acids are changed. Mutations that form a continuous hydrophobic surface with the ω-1 atom of an acyl-ACP were shown to be selective for that chain length. Finally, the ability to anaerobically oxidize methane to create liquid fuels is presumed to be kinetically-limited, but as of yet, the step that controls the net oxidation rate has not been firmly established. Multiple scenarios were devised that considered plausible limiting steps for the anaerobic oxidation of methane. Two of the case studies focused on improving catalysis by using OptZyme, while another used a simple IPRO formulation to alter cofactor specificity. Based on a detailed literature review, the rate of product unbinding from the active site of methyl-coenzyme M reductase was suggested to limit methane oxidation kinetics. For the final case study, a novel amino acid selection step was developed to consider multiple design criteria at once. It was used to improve the rate of product release for methyl-coenzyme M reductase and suggested large, multi-conformational, hydrophobic side chains. By improving the rate of methane oxidation, the economics of methane-to-liquid fuel bioconversion becomes more propitious.