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

PLoS Computational Biology, ISSN: 1553-7358, Vol: 12, Issue: 3, Page: e1004752
2016
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Article 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.

Bibliographic Details

http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84962109465&origin=inward; http://dx.doi.org/10.1371/journal.pcbi.1004752; http://www.ncbi.nlm.nih.gov/pubmed/26967624; https://dx.plos.org/10.1371/journal.pcbi.1004752.g001; http://dx.doi.org/10.1371/journal.pcbi.1004752.g001; https://dx.plos.org/10.1371/journal.pcbi.1004752; https://dx.plos.org/10.1371/journal.pcbi.1004752.g003; http://dx.doi.org/10.1371/journal.pcbi.1004752.g003; https://dx.plos.org/10.1371/journal.pcbi.1004752.g006; http://dx.doi.org/10.1371/journal.pcbi.1004752.g006; https://dx.plos.org/10.1371/journal.pcbi.1004752.g002; http://dx.doi.org/10.1371/journal.pcbi.1004752.g002; https://dx.plos.org/10.1371/journal.pcbi.1004752.g005; http://dx.doi.org/10.1371/journal.pcbi.1004752.g005; https://dx.plos.org/10.1371/journal.pcbi.1004752.g007; http://dx.doi.org/10.1371/journal.pcbi.1004752.g007; https://dx.plos.org/10.1371/journal.pcbi.1004752.g004; http://dx.doi.org/10.1371/journal.pcbi.1004752.g004; https://dx.plos.org/10.1371/journal.pcbi.1004752.t001; http://dx.doi.org/10.1371/journal.pcbi.1004752.t001; https://dx.doi.org/10.1371/journal.pcbi.1004752.t001; https://journals.plos.org/ploscompbiol/article/figure?id=10.1371/journal.pcbi.1004752.t001; https://dx.doi.org/10.1371/journal.pcbi.1004752.g007; https://journals.plos.org/ploscompbiol/article/figure?id=10.1371/journal.pcbi.1004752.g007; https://dx.doi.org/10.1371/journal.pcbi.1004752.g003; https://journals.plos.org/ploscompbiol/article/figure?id=10.1371/journal.pcbi.1004752.g003; https://dx.doi.org/10.1371/journal.pcbi.1004752.g004; https://journals.plos.org/ploscompbiol/article/figure?id=10.1371/journal.pcbi.1004752.g004; https://dx.doi.org/10.1371/journal.pcbi.1004752; https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004752; https://dx.doi.org/10.1371/journal.pcbi.1004752.g006; https://journals.plos.org/ploscompbiol/article/figure?id=10.1371/journal.pcbi.1004752.g006; https://dx.doi.org/10.1371/journal.pcbi.1004752.g001; https://journals.plos.org/ploscompbiol/article/figure?id=10.1371/journal.pcbi.1004752.g001; https://dx.doi.org/10.1371/journal.pcbi.1004752.g005; https://journals.plos.org/ploscompbiol/article/figure?id=10.1371/journal.pcbi.1004752.g005; https://dx.doi.org/10.1371/journal.pcbi.1004752.g002; https://journals.plos.org/ploscompbiol/article/figure?id=10.1371/journal.pcbi.1004752.g002; http://dx.plos.org/10.1371/journal.pcbi.1004752.g002; http://dx.plos.org/10.1371/journal.pcbi.1004752; https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1004752&type=printable; http://dx.plos.org/10.1371/journal.pcbi.1004752.g003; http://dx.plos.org/10.1371/journal.pcbi.1004752.g004; http://www.plosone.org/article/metrics/info:doi/10.1371/journal.pcbi.1004752; http://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1004752&type=printable; http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004752; http://dx.plos.org/10.1371/journal.pcbi.1004752.g007; http://dx.plos.org/10.1371/journal.pcbi.1004752.g001; http://dx.plos.org/10.1371/journal.pcbi.1004752.g005; http://dx.plos.org/10.1371/journal.pcbi.1004752.g006; http://dx.plos.org/10.1371/journal.pcbi.1004752.t001

Cristiano De Michele; Paolo De Los Rios; Giuseppe Foffi; Francesco Piazza; Yanay Ofran

Public Library of Science (PLoS)

Agricultural and Biological Sciences; Mathematics; Environmental Science; Biochemistry, Genetics and Molecular Biology; Neuroscience; Computer Science

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