Ensemble-based Computational Protein Design: Novel Algorithms and Applications to Energy Landscape Approximation, Antibiotic Resistance, and Antibody Design

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2024-09-16

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2022

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Abstract

Proteins are incredibly varied in their biological function, and are therefore attractive targets for scientists and engineers to design new and improved functions. These functions are defined by a protein structure, which can be viewed as a probability distribution over a large conformation space. Many successful protein design methods construct and evaluate models of protein structure and physics in silico to design proteins. We apply the concept of protein structure as a probability distribution to design new protein design algorithms, study mechanisms of protein binding and antibiotic resistance, and design improved broadly-neutralizing antibodies This research highlights the utility of the distribution view of protein structure, and suggests future research in this direction.

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Holt, Graham Thomas (2022). Ensemble-based Computational Protein Design: Novel Algorithms and Applications to Energy Landscape Approximation, Antibiotic Resistance, and Antibody Design. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/25747.

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