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Simulation and Theory of Antibody Binding to Crowded Antigen-Covered Surfaces

In this paper we introduce a fully flexible coarse-grained model of immunoglobulin G (IgG) antibodies parametrized directly on cryo-EM data and simulate the binding dynamics of many IgGs to antigens adsorbed on a surface at increasing densities. Moreover, we work out a theoretical model that allows...

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Autores principales: De Michele, Cristiano, De Los Rios, Paolo, Foffi, Giuseppe, Piazza, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4788199/
https://www.ncbi.nlm.nih.gov/pubmed/26967624
http://dx.doi.org/10.1371/journal.pcbi.1004752
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author De Michele, Cristiano
De Los Rios, Paolo
Foffi, Giuseppe
Piazza, Francesco
author_facet De Michele, Cristiano
De Los Rios, Paolo
Foffi, Giuseppe
Piazza, Francesco
author_sort De Michele, Cristiano
collection PubMed
description In this paper we introduce a fully flexible coarse-grained model of immunoglobulin G (IgG) antibodies parametrized directly on cryo-EM data and simulate the binding dynamics of many IgGs to antigens adsorbed on a surface at increasing densities. Moreover, we work out a theoretical model that allows to explain all the features observed in the simulations. Our combined computational and theoretical framework is in excellent agreement with surface-plasmon resonance data and allows us to establish a number of important results. (i) Internal flexibility is key to maximize bivalent binding, flexible IgGs being able to explore the surface with their second arm in search for an available hapten. This is made clear by the strongly reduced ability to bind with both arms displayed by artificial IgGs designed to rigidly keep a prescribed shape. (ii) The large size of IgGs is instrumental to keep neighboring molecules at a certain distance (surface repulsion), which essentially makes antigens within reach of the second Fab always unoccupied on average. (iii) One needs to account independently for the thermodynamic and geometric factors that regulate the binding equilibrium. The key geometrical parameters, besides excluded-volume repulsion, describe the screening of free haptens by neighboring bound antibodies. We prove that the thermodynamic parameters govern the low-antigen-concentration regime, while the surface screening and repulsion only affect the binding at high hapten densities. Importantly, we prove that screening effects are concealed in relative measures, such as the fraction of bivalently bound antibodies. Overall, our model provides a valuable, accurate theoretical paradigm beyond existing frameworks to interpret experimental profiles of antibodies binding to multi-valent surfaces of different sorts in many contexts.
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spelling pubmed-47881992016-03-23 Simulation and Theory of Antibody Binding to Crowded Antigen-Covered Surfaces De Michele, Cristiano De Los Rios, Paolo Foffi, Giuseppe Piazza, Francesco PLoS Comput Biol Research Article In this paper we introduce a fully flexible coarse-grained model of immunoglobulin G (IgG) antibodies parametrized directly on cryo-EM data and simulate the binding dynamics of many IgGs to antigens adsorbed on a surface at increasing densities. Moreover, we work out a theoretical model that allows to explain all the features observed in the simulations. Our combined computational and theoretical framework is in excellent agreement with surface-plasmon resonance data and allows us to establish a number of important results. (i) Internal flexibility is key to maximize bivalent binding, flexible IgGs being able to explore the surface with their second arm in search for an available hapten. This is made clear by the strongly reduced ability to bind with both arms displayed by artificial IgGs designed to rigidly keep a prescribed shape. (ii) The large size of IgGs is instrumental to keep neighboring molecules at a certain distance (surface repulsion), which essentially makes antigens within reach of the second Fab always unoccupied on average. (iii) One needs to account independently for the thermodynamic and geometric factors that regulate the binding equilibrium. The key geometrical parameters, besides excluded-volume repulsion, describe the screening of free haptens by neighboring bound antibodies. We prove that the thermodynamic parameters govern the low-antigen-concentration regime, while the surface screening and repulsion only affect the binding at high hapten densities. Importantly, we prove that screening effects are concealed in relative measures, such as the fraction of bivalently bound antibodies. Overall, our model provides a valuable, accurate theoretical paradigm beyond existing frameworks to interpret experimental profiles of antibodies binding to multi-valent surfaces of different sorts in many contexts. Public Library of Science 2016-03-11 /pmc/articles/PMC4788199/ /pubmed/26967624 http://dx.doi.org/10.1371/journal.pcbi.1004752 Text en © 2016 De Michele 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 (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
De Michele, Cristiano
De Los Rios, Paolo
Foffi, Giuseppe
Piazza, Francesco
Simulation and Theory of Antibody Binding to Crowded Antigen-Covered Surfaces
title Simulation and Theory of Antibody Binding to Crowded Antigen-Covered Surfaces
title_full Simulation and Theory of Antibody Binding to Crowded Antigen-Covered Surfaces
title_fullStr Simulation and Theory of Antibody Binding to Crowded Antigen-Covered Surfaces
title_full_unstemmed Simulation and Theory of Antibody Binding to Crowded Antigen-Covered Surfaces
title_short Simulation and Theory of Antibody Binding to Crowded Antigen-Covered Surfaces
title_sort simulation and theory of antibody binding to crowded antigen-covered surfaces
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4788199/
https://www.ncbi.nlm.nih.gov/pubmed/26967624
http://dx.doi.org/10.1371/journal.pcbi.1004752
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