Computational Protein Design with Non-proteinogenic Amino Acids and Small Molecule Ligands, with Applications to Protein-protein Interaction Inhibitors, Anti-microbial Enzyme Inhibitors, and Antibody Design

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2021

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Abstract

Computational protein design is a leading-edge technology to design novel protein with novel functions, as well as study the structure and function of known protein. Conventionally, most of the existing computational protein design methods and softwares focus only on modeling proteinogenic amino acids. However, in reality most biochemical systems are far more complicated. Many kinds of protein not only consist of proteinogenic amino acids, but also contain non-natural amino acids or post-transnational modifications. For some protein, their function can only be fulfilled through the interaction with small molecule ligands or cofactors, which is also beyond the scope of proteinogenic amino acids. In order to expand the capability of computational protein design methods, in this dissertation we incorporated the the modeling of non-natural amino acids into OSPREY. OSPREY is a computational protein design software suite that based on provable algorithms and developed in our lab. Furthermore, 3 human health related designs involving non-natural amino acids or small molecule ligands are presented in this dissertation: (1) design of novel cystic fibrosis therapeutics using non-natural amino acids, (2) re-design of HIV-1 broadly neutralizing antibodies for better potency and breadth, and (3) development of novel antibiotics fighting methicillin-resistant Staphylococcus aureus and the analysis of its resistance mechanism. Through extensive computational results and experiential data, we are able to demonstrate the success of our above designs.

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Wang, Siyu (2021). Computational Protein Design with Non-proteinogenic Amino Acids and Small Molecule Ligands, with Applications to Protein-protein Interaction Inhibitors, Anti-microbial Enzyme Inhibitors, and Antibody Design. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/23730.

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