Dissertation/Thesis Abstract

Physics-Based Vaccine Design: From Self-Assembly Facilitating Peptide Prediction to Broad-Spectrum, Neutralizing, & Symmetry-Based Epitope Discovery
by Biner, Daniel William, Ph.D., Indiana University, 2020, 144; 28023870
Abstract (Summary)

Computational epitope discovery has traditionally been complicated by multiple scales of epitope organization and a lack of structurally characterized epitopes. To provide a theoretical account of clinically relevant epitope physics, all-atom Molecular Dynamics simulations were run on the Zika virus structure. Four epitope discovery algorithms were developed against six preexisting algorithms and thirty-eight flavivirus-antibody structures. For the first time, virus protein flexibility was shown to outperform solvent accessible surface area at epitope discovery! A new epitope discovery benchmarking method was introduced, highlighting bias in previous epitope analyses. New methods for 1) quantifying virus-like particle flexibility and 2) predicting vaccine self-assembly facilitating peptides were also presented.

Indexing (document details)
Advisor: Ortoleva, Peter J.
Commitee: Yu, Yan, Tait, Steven L., Raghavachari, Krishnan
School: Indiana University
Department: Chemistry
School Location: United States -- Indiana
Source: DAI-B 82/2(E), Dissertation Abstracts International
Subjects: Immunology, Pharmaceutical sciences
Keywords: Conserved B-Cell epitope, Flavivirus, Precision-recall, Protein flexibility, Zika virus
Publication Number: 28023870
ISBN: 9798664729764
Copyright © 2021 ProQuest LLC. All rights reserved. Terms and Conditions Privacy Policy Cookie Policy