Ensemble-based Computational Protein Design: Novel Algorithms and Applications to Energy Landscape Approximation, Antibiotic Resistance, and Antibody Design
Date
2022
Authors
Advisors
Journal Title
Journal ISSN
Volume Title
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.
Type
Department
Description
Provenance
Subjects
Citation
Permalink
Citation
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.
Collections
Dukes student scholarship is made available to the public using a Creative Commons Attribution / Non-commercial / No derivative (CC-BY-NC-ND) license.