Proteins that have been modified by attaching them to a surface or to a polyethylene glycol (PEG) molecule can see many uses in therapeutics and diagnostics -- these unique proteins are called protein devices. Current techniques can perform these functionalizations at a specific residue on the protein, but what remains is identifying what happens to protein structure when mutated, and where to perform the attachment. Both of these issues can be examined using molecular dynamic (MD) simulations. Currently, simulations of the unnatural amino acid (uAA) mutations necessary for protein device functionalization cannot be executed, and full-protein screens of all possible protein device models have never been attempted. Results from this dissertation first employs a new model for simulating PEGylated protein devices building off of previous studies that explore where to attach functional groups. Next, many current assumptions in the community regarding ideal attachment sites are examined. Some of these factors include primary chain location, amino acid type, solvent accessibility, and secondary structure. The focus then turns to novel tertiary structure factors that could influence how well attachment locations affect overall protein device stability. The usefulness of each factor is analyzed to show what factors provided the best predictive power for a site's performance in the screen. A general heuristic is given that could aid in future screens of other protein devices to reduce compute time and quickly identify sites for experimental examination. To explore uAA mutation effects on protein structure, parameters are developed for linear moiety R-groups present in these novel amino acids. The CHARMM and CGenFF force fields currently lack parameters for most linear-angle molecular moieties. This work proposes a method that (1) develops CHARMM parameters for four small molecules that contain terminal azido and alkynyl groups using ffTK, (2) addresses linearity issues, and (3) validates ffTK results via in silico MD simulation. Dihedral analysis examines the linear-angle-containing dihedrals and compares methods for the moiety parameterization. Next, the small molecule parameters are combined with CGenFF to generate parameters for unnatural amino acid MD simulation in a protein. Finally, validation confirms the parameters derived in this work to appropriately simulate unnatural amino acids and small molecules with azido and alkynyl groups.
| Identifer | oai:union.ndltd.org:BGMYU2/oai:scholarsarchive.byu.edu:etd-9792 |
| Date | 20 January 2021 |
| Creators | Smith, Addison Kyle |
| Publisher | BYU ScholarsArchive |
| Source Sets | Brigham Young University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | https://lib.byu.edu/about/copyright/ |
Page generated in 0.0019 seconds