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dc.contributor.advisorGray, Jeffrey J.en_US
dc.contributor.authorWeitzner, Brian D.en_US
dc.date.accessioned2015-09-16T03:34:18Z
dc.date.available2015-09-16T03:34:18Z
dc.date.created2015-05en_US
dc.date.issued2015-03-11en_US
dc.date.submittedMay 2015en_US
dc.identifier.urihttp://jhir.library.jhu.edu/handle/1774.2/37835
dc.description.abstractAntibodies are important immunological molecules that can bind a diverse array of foreign molecules. The genetic mechanism that gives rise to antibodies and many antibody sequences is known, but only by studying three-dimensional structures of antibodies and antibody–antigen complexes can we reveal immunological mechanisms and provide a starting point for developing rationally designed antibodies. With the advent of high-throughput sequencing technologies, the gap between the number of sequences and structures is widening, demanding accurate antibody modeling methods. Our previously developed method, RosettaAntibody, served as a starting point for antibody structure prediction. In this dissertation, I detail my work assessing the predictive power of RosettaAntibody, and the development and testing of new methods to address its weaknesses. First, I describe an effort to assess the accuracy of RosettaAntibody on a set of unpublished crystal structures. This challenge enabled us to combine manual and automated methods for selecting models and compare RosettaAntibody to other antibody modeling methods. The most challenging aspect of structure prediction in this assessment proved to be modeling the third complementarity determining region loop on the heavy chain (CDR H3). Next I detail my work in studying CDR H3 loops to uncover why a vast majority of them contain a kink at the loop's C-terminus. Part of this work involved searching the Protein Data Bank (PDB) for structures with a similar geometry of the amino acid residues at the base of the loop, leading to a set of CDR H3-like loops from non-antibody proteins. With a clearer understanding of CDR H3 loop structures and the most detailed description of the kink to date, I developed a new loop modeling routine that utilizes this information to restrict the geometry of the loop to be kinked, resulting in an improvement in the weakest aspect of antibody structure prediction. In summary, the structure prediction methods I have developed and structural analyses I have performed provide a means to begin to address the widening sequence–structure gap. Additionally, these methods can be used to perform structural analysis in the development of rationally designed antibodies.en_US
dc.format.mimetypeapplication/pdfen_US
dc.languageen
dc.publisherJohns Hopkins University
dc.subjectRosettaen_US
dc.subjectantibodiesen_US
dc.subjectCDR H3en_US
dc.subjectstructure predictionen_US
dc.titleNext-generation antibody modelingen_US
dc.typeThesisen_US
thesis.degree.disciplineChemical & Biomolecular Engineeringen_US
thesis.degree.grantorJohns Hopkins Universityen_US
thesis.degree.grantorWhiting School of Engineeringen_US
thesis.degree.levelDoctoralen_US
thesis.degree.namePh.D.en_US
dc.type.materialtexten_US
thesis.degree.departmentChemical and Biomolecular Engineeringen_US
dc.contributor.committeeMemberDonohue, Marc D.en_US
dc.contributor.committeeMemberOstermeier, Marcen_US
dc.contributor.committeeMemberDunbrack, Roland L.en_US
dc.contributor.committeeMemberRuczinski, Ingoen_US


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