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Mapping the Pareto Optimal Design Space for a Functionally Deimmunized Biotherapeutic Candidate
The immunogenicity of biotherapeutics can bottleneck development pipelines and poses a barrier to widespread clinical application. As a result, there is a growing need for improved deimmunization technologies. We have recently described algorithms that simultaneously optimize proteins for both reduc...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4288714/ https://www.ncbi.nlm.nih.gov/pubmed/25568954 http://dx.doi.org/10.1371/journal.pcbi.1003988 |
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author | Salvat, Regina S. Parker, Andrew S. Choi, Yoonjoo Bailey-Kellogg, Chris Griswold, Karl E. |
author_facet | Salvat, Regina S. Parker, Andrew S. Choi, Yoonjoo Bailey-Kellogg, Chris Griswold, Karl E. |
author_sort | Salvat, Regina S. |
collection | PubMed |
description | The immunogenicity of biotherapeutics can bottleneck development pipelines and poses a barrier to widespread clinical application. As a result, there is a growing need for improved deimmunization technologies. We have recently described algorithms that simultaneously optimize proteins for both reduced T cell epitope content and high-level function. In silico analysis of this dual objective design space reveals that there is no single global optimum with respect to protein deimmunization. Instead, mutagenic epitope deletion yields a spectrum of designs that exhibit tradeoffs between immunogenic potential and molecular function. The leading edge of this design space is the Pareto frontier, i.e. the undominated variants for which no other single design exhibits better performance in both criteria. Here, the Pareto frontier of a therapeutic enzyme has been designed, constructed, and evaluated experimentally. Various measures of protein performance were found to map a functional sequence space that correlated well with computational predictions. These results represent the first systematic and rigorous assessment of the functional penalty that must be paid for pursuing progressively more deimmunized biotherapeutic candidates. Given this capacity to rapidly assess and design for tradeoffs between protein immunogenicity and functionality, these algorithms may prove useful in augmenting, accelerating, and de-risking experimental deimmunization efforts. |
format | Online Article Text |
id | pubmed-4288714 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-42887142015-01-12 Mapping the Pareto Optimal Design Space for a Functionally Deimmunized Biotherapeutic Candidate Salvat, Regina S. Parker, Andrew S. Choi, Yoonjoo Bailey-Kellogg, Chris Griswold, Karl E. PLoS Comput Biol Research Article The immunogenicity of biotherapeutics can bottleneck development pipelines and poses a barrier to widespread clinical application. As a result, there is a growing need for improved deimmunization technologies. We have recently described algorithms that simultaneously optimize proteins for both reduced T cell epitope content and high-level function. In silico analysis of this dual objective design space reveals that there is no single global optimum with respect to protein deimmunization. Instead, mutagenic epitope deletion yields a spectrum of designs that exhibit tradeoffs between immunogenic potential and molecular function. The leading edge of this design space is the Pareto frontier, i.e. the undominated variants for which no other single design exhibits better performance in both criteria. Here, the Pareto frontier of a therapeutic enzyme has been designed, constructed, and evaluated experimentally. Various measures of protein performance were found to map a functional sequence space that correlated well with computational predictions. These results represent the first systematic and rigorous assessment of the functional penalty that must be paid for pursuing progressively more deimmunized biotherapeutic candidates. Given this capacity to rapidly assess and design for tradeoffs between protein immunogenicity and functionality, these algorithms may prove useful in augmenting, accelerating, and de-risking experimental deimmunization efforts. Public Library of Science 2015-01-08 /pmc/articles/PMC4288714/ /pubmed/25568954 http://dx.doi.org/10.1371/journal.pcbi.1003988 Text en © 2015 Salvat et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Salvat, Regina S. Parker, Andrew S. Choi, Yoonjoo Bailey-Kellogg, Chris Griswold, Karl E. Mapping the Pareto Optimal Design Space for a Functionally Deimmunized Biotherapeutic Candidate |
title | Mapping the Pareto Optimal Design Space for a Functionally Deimmunized Biotherapeutic Candidate |
title_full | Mapping the Pareto Optimal Design Space for a Functionally Deimmunized Biotherapeutic Candidate |
title_fullStr | Mapping the Pareto Optimal Design Space for a Functionally Deimmunized Biotherapeutic Candidate |
title_full_unstemmed | Mapping the Pareto Optimal Design Space for a Functionally Deimmunized Biotherapeutic Candidate |
title_short | Mapping the Pareto Optimal Design Space for a Functionally Deimmunized Biotherapeutic Candidate |
title_sort | mapping the pareto optimal design space for a functionally deimmunized biotherapeutic candidate |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4288714/ https://www.ncbi.nlm.nih.gov/pubmed/25568954 http://dx.doi.org/10.1371/journal.pcbi.1003988 |
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