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.
|Advisor:||Ortoleva, Peter J.|
|Commitee:||Yu, Yan, Tait, Steven L., Raghavachari, Krishnan|
|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|
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