Abstract
The immune system is a remarkably adaptive network, yet it often fails to function optimally due to evasion strategies of pathogens or mutated cells. Many of these evasion strategies involve alterations in protein expression and function. Protein design is an area of computational biology with potential applications in improving protein function and therapeutic protein engineering. This thesis explores methods to enhance immune function and protein design across multiple scales, from molecular engineering of antibody fragments and chimeric antigen receptors (CARs) to cellular immune responses, and computational approaches for protein structure optimization. We characterize Thymidine Kinase 1-specific single-chain antibodies, highlighting both the potential and challenges of isolating highly specific antibodies and considering nanobody libraries as alternative platforms. CAR therapies are examined in the context of antigen specificity, immune cell persistence, and tumor microenvironment limitations, while the role of atypical chemokine receptors in neuroinflammation is explored as a window into immune regulation in the central nervous system. Finally, computational approaches, including deep learning-guided protein design, are applied to luciferase to explore the balance between structural stability and function. Together, these studies combine learning from experimental immunology to computational protein design, provide insights into how structure, stability, and function intersect, and lay the groundwork for future explorations in therapeutic protein engineering.
Degree
MS
College and Department
Life Sciences; Microbiology and Molecular Biology
Rights
https://lib.byu.edu/about/copyright/
BYU ScholarsArchive Citation
Haynie, Christopher J., "Navigating Structure, Function, and Stability: Bridging Immunotherapy and Protein Engineering in the Era of Machine Learning" (2025). Theses and Dissertations. 11053.
https://scholarsarchive.byu.edu/etd/11053
Date Submitted
2025-11-20
Document Type
Thesis
Keywords
ACKRs, antibody, atypical chemokine receptors, CAR T cells, chimeric antigen receptors, cancer, computational protein design, deep learning, immunotherapy, luciferase, machine learning, nanobodies, NanoLuc, neuroinflammation, protein engineering, protein stability, scFv, TK1, thymidine kinase
Language
english