Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Einav, Tal, Bloom, Jesse D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
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
_version_ 1783533926998867968
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
work_keys_str_mv AT einavtal whentwoarebetterthanonemodelingthemechanismsofantibodymixtures
AT bloomjessed whentwoarebetterthanonemodelingthemechanismsofantibodymixtures