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When two are better than one: Modeling the mechanisms of antibody mixtures
It is difficult to predict how antibodies will behave when mixed together, even after each has been independently characterized. Here, we present a statistical mechanical model for the activity of antibody mixtures that accounts for whether pairs of antibodies bind to distinct or overlapping epitope...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7224563/ https://www.ncbi.nlm.nih.gov/pubmed/32365091 http://dx.doi.org/10.1371/journal.pcbi.1007830 |
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author | Einav, Tal Bloom, Jesse D. |
author_facet | Einav, Tal Bloom, Jesse D. |
author_sort | Einav, Tal |
collection | PubMed |
description | It is difficult to predict how antibodies will behave when mixed together, even after each has been independently characterized. Here, we present a statistical mechanical model for the activity of antibody mixtures that accounts for whether pairs of antibodies bind to distinct or overlapping epitopes. This model requires measuring n individual antibodies and their [Image: see text] pairwise interactions to predict the 2(n) potential combinations. We apply this model to epidermal growth factor receptor (EGFR) antibodies and find that the activity of antibody mixtures can be predicted without positing synergy at the molecular level. In addition, we demonstrate how the model can be used in reverse, where straightforward experiments measuring the activity of antibody mixtures can be used to infer the molecular interactions between antibodies. Lastly, we generalize this model to analyze engineered multidomain antibodies, where components of different antibodies are tethered together to form novel amalgams, and characterize how well it predicts recently designed influenza antibodies. |
format | Online Article Text |
id | pubmed-7224563 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-72245632020-06-01 When two are better than one: Modeling the mechanisms of antibody mixtures Einav, Tal Bloom, Jesse D. PLoS Comput Biol Research Article It is difficult to predict how antibodies will behave when mixed together, even after each has been independently characterized. Here, we present a statistical mechanical model for the activity of antibody mixtures that accounts for whether pairs of antibodies bind to distinct or overlapping epitopes. This model requires measuring n individual antibodies and their [Image: see text] pairwise interactions to predict the 2(n) potential combinations. We apply this model to epidermal growth factor receptor (EGFR) antibodies and find that the activity of antibody mixtures can be predicted without positing synergy at the molecular level. In addition, we demonstrate how the model can be used in reverse, where straightforward experiments measuring the activity of antibody mixtures can be used to infer the molecular interactions between antibodies. Lastly, we generalize this model to analyze engineered multidomain antibodies, where components of different antibodies are tethered together to form novel amalgams, and characterize how well it predicts recently designed influenza antibodies. Public Library of Science 2020-05-04 /pmc/articles/PMC7224563/ /pubmed/32365091 http://dx.doi.org/10.1371/journal.pcbi.1007830 Text en © 2020 Einav, Bloom http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Einav, Tal Bloom, Jesse D. When two are better than one: Modeling the mechanisms of antibody mixtures |
title | When two are better than one: Modeling the mechanisms of antibody mixtures |
title_full | When two are better than one: Modeling the mechanisms of antibody mixtures |
title_fullStr | When two are better than one: Modeling the mechanisms of antibody mixtures |
title_full_unstemmed | When two are better than one: Modeling the mechanisms of antibody mixtures |
title_short | When two are better than one: Modeling the mechanisms of antibody mixtures |
title_sort | when two are better than one: modeling the mechanisms of antibody mixtures |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7224563/ https://www.ncbi.nlm.nih.gov/pubmed/32365091 http://dx.doi.org/10.1371/journal.pcbi.1007830 |
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