Date of Award
2024
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Biotechnology Science and Engineering
Committee Chair
Jerome Baudry
Committee Member
Luis Cruz-Vera
Committee Member
Joseph Ng
Committee Member
Baitang Ning
Committee Member
Jennifer Golden
Research Advisor
Jerome Baudry
Subject(s)
Computational biology, Protein-protein interactions.
Abstract
Non-bonded interactions are fundamental forces that govern molecular relationships between two or more molecules. These interactions contribute to the stability of complex biological structures like DNA, RNA, and proteins, and control various biological processes. Almost all of these processes are significantly influenced by protein-protein and protein-ligand intermolecular interactions. Here, the interactions of various proteins with other proteins, peptides, and/or ligands were quantified computationally to tackle human health-related problems. For estimating the intermolecular interactions, a number of computational approaches including protein structure modeling, molecular dynamics simulations, molecular docking, ensemble docking, semi-empirical methods, etc., were used. The basics of Molecular Mechanics and Quantum Mechanics were applied throughout this dissertation, either separately or combinedly, to address the issues. This study is focused on three major projects. In the first project, the role of the SETBP1 protein's interaction with the SCF-βTrCP1 E3 ubiquitin ligase in Schinzel-Giedion Syndrome (SGS) was studied. A segment of the SETBP1 protein was modeled and was used to design Proteolysis Targeting Chimeras (PROTACs) for treating SGS. Additionally, we compared the binding affinity of several SETBP1 mutants with the ubiquitin ligase to understand the effect of mutation on ubiquitination and SGS severity. The second project examined the impact of SARS-CoV-2 spike protein mutations on its binding with the human ACE2 receptor and the therapeutic antibody bebtelovimab. By computing the change in protein-protein intermolecular interaction energy, we predicted how these mutations may influence the efficacy of bebtelovimab. The final project concentrated on the cytochrome P450 enzyme. An initiative was taken to develop a computational method to identify potential toxic metabolites by combining molecular docking and semi-empirical quantum method by calculating the interaction energy between P450 and its ligands. Overall, this dissertation signifies the computational approaches in quantifying protein interactions. By integrating principles from biology, chemistry, and computational science, this research offers new insights to address health and environmental challenges.
Recommended Citation
Mansur, Maher, "Quantitative characterization of non-bonded interactions in proteins affecting human health and disease" (2024). Dissertations. 415.
https://louis.uah.edu/uah-dissertations/415