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 to account for multiple ligands and receptors, optionally allowing heterogeneous complexes. We derive the macroscopic pre-dictions for both specifically arranged and randomly assorted complexes, and demonstrate how this model enables large-scale predictions on mixture binding and the binding space of a ligand. This model provides an elegant and computationally efficient framework for analyzing multivalent binding.
Competing Interest Statement
The authors have declared no competing interest.
