ArticleMathematical biosciences2021
A general model of multivalent binding with ligands of heterotypic subunits and multiple surface receptors.
Article in Mathematical biosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 18 citations in OpenAlex.
- Review
- A multivalent binding model infers antibody Fc species from systems serology.PLoS computational biology · 2024Article
- Mechanistic computational modeling of monospecific and bispecific antibodies targeting interleukin-6/8 receptors.PLoS computational biology · 2024Article
- Multivalent, asymmetric IL-2-Fc fusions show enhanced selectivity for regulatory T cells.Science signaling · 2023Article
- Design of cell-type-specific hyperstable IL-4 mimetics via modular de novo scaffolds.Nature chemical biology · 2023Article
- Mixed IgG Fc immune complexes exhibit blended binding profiles and refine FcR affinity estimates.Cell reports · 2023Article
- Mixed IgG Fc immune complexes exhibit blended binding profiles and refine FcR affinity estimates.bioRxiv : the preprint server for biology · 2023Article
- Engineered human cytokine/antibody fusion proteins expand regulatory T cells and confer autoimmune disease protection.Cell reports · 2022Article
- A quantitative view of strategies to engineer cell-selective ligand binding.Integrative biology : quantitative biosciences from nano to macro · 2021Article
- Tensor-structured decomposition improves systems serology analysis.Molecular systems biology · 2021Article
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Authors and funding
2 authors at 1 institution in 1 country.
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Abstract
Multivalent cell surface receptor binding is a ubiquitous biological phenomenon with functional and therapeutic significance. Predicting the amount of ligand binding for a cell remains an important question in computational biology as it can provide great insight into cell-to-cell communication and rational drug design toward specific targets. In this study, we extend a mechanistic, two-step multivalent binding model. This model predicts the behavior of a mixture of different multivalent ligand complexes binding to cells expressing various types of receptors. It accounts for the combinatorially large number of interactions between multiple ligands and receptors, optionally allowing a mixture of complexes with different valencies and complexes that contain heterogeneous ligand units. We derive the macroscopic predictions and demonstrate how this model enables large-scale predictions on mixture binding and the binding space of a ligand. This model thus provides an elegant and computationally efficient framework for analyzing multivalent binding.
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