Dissertation/Thesis Abstract

The Experimental Analysis of Mutlitple Computationally-Driven Methods for the Deletion of Broadly Distributed T cell Epitopes in a Functional Biotherapeutic Candidate
by Salvat, Regina, Ph.D., Dartmouth College, 2015, 221; 3685082
Abstract (Summary)

Novel biotherapeutics have reshaped drug discovery and promise a continued revolution in disease therapy, yet therapeutic proteins present unique design challenges. One distinguishing risk factor is the prospect of eliciting an adaptive immune response upon administration to human patients. An anti-drug immune response can compromise therapeutic efficacy and even threaten patient safety. Grafting-based deimmunization strategies have been successfully developed for therapeutic antibodies, but are not, however, broadly applicable to other protein classes, such as therapeutic enzymes. A broadly applicable protein deimmunization technologies is required for non-immunoglobulin therapeutic candidates. To help meet this challenge, optimization algorithms that seamlessly integrate computational prediction of T cell epitopes and bioinformatics-based assessment of the structural and functional consequences of epitope-deleting mutations have recently been developed. These methods address the fact that biotherapeutic deimmunization represents a dual-objective protein design space with tradeoffs between immunogenicity and stability or activity.

This thesis describes the experimental validation of four iterations of these algorithms using the Enterobacter cloacae P99 β-lactamase (P99βL), a component of Antibody Directed Enzyme Prodrug Therapies, as a model protein. The first algorithm tested, Integer Programming for Immunogenic Proteins (IP 2), seamlessly integrates computational prediction of T cell epitopes with both 1- and 2-body sequence potentials that assess protein tolerance to epitope-deleting mutations. IP2 successfully employed moderate mutational loads to delete distributed T cell epitopes, while maintaining enzyme functionality. Second, a more advanced extension of IP2, Protein Engineering Pareto Frontier (PEPFR), was explored experimentally to assess and validate the inherent tradeoffs linking the target enzyme's sequence, function, and immunogenic potential. Third, EpiSweep, a structure-based algorithm was applied to P99βL, and the experimental outcomes were compared to PEPFR designs having the same mutational load and predicted immunogenicity, and yielded new insights into the relative advantages of each deimmunization methodology. Finally, a sequence-based approach to deimmunized library design was applied to P99βL at varying mutational loads, and library functionality was tested. Together, these experimental analyses have provided a rich data set by which to assess the accuracy, efficiency, and overall utility of cutting-edge biotherapeutic deimmunization technologies. The methods may ultimately prove useful in accelerating the biotherapeutic design and development process

Indexing (document details)
Advisor: Griswold, Karl E.
Commitee: Ackerman, Margaret E., Bailey-Kellogg, Chris, Moise, Lenny
School: Dartmouth College
Department: Engineering
School Location: United States -- New Hampshire
Source: DAI-B 76/07(E), Dissertation Abstracts International
Source Type: DISSERTATION
Subjects: Chemical engineering, Immunology, Computer science
Keywords: Biotechnology, Deimmunization, Protein engineering
Publication Number: 3685082
ISBN: 9781321606751
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