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arXiv · 1511.07652

Binding constants of membrane-anchored receptors and ligands: a general theory corroborated by Monte Carlo simulations

Guang-Kui Xu·Jinglei Hu·Reinhard Lipowsky·Thomas R. Weikl
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Abstract

Adhesion processes of biological membranes that enclose cells and cellular organelles are essential for immune responses, tissue formation, and signaling. These processes depend sensitively on the binding constant K2D of the membrane-anchored receptor and ligand proteins that mediate adhesion, which is difficult to measure in the 'two-dimensional' (2D) membrane environment of the proteins. An important problem therefore is to relate K2D} to the binding constant K3D} of soluble variants of the receptors and ligands that lack the membrane anchors and are free to diffuse in three dimensions (3D). In this article, we present a general theory for the binding constants K2D and K3D of rather stiff proteins whose main degrees of freedom are translation and rotation, along membranes and around anchor points 'in 2D', or unconstrained 'in 3D'. The theory generalizes previous results by describing how K2D depends both on the average separation and thermal nanoscale roughness of the apposing membranes, and on the length and anchoring flexibility of the receptors and ligands. Our theoretical results for the ratio K2D/K3D of the binding constants agree with detailed results from Monte Carlo simulations without any data fitting, which indicates that the theory captures the essential features of the 'dimensionality reduction' due to membrane anchoring. In our Monte Carlo simulations, we consider a novel coarse-grained model of biomembrane adhesion in which the membranes are represented as discretized elastic surfaces, and the receptors and ligands as anchored molecules that diffuse continuously along the membranes and rotate at their anchor points.

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Guang-Kui Xu, Jinglei Hu, Reinhard Lipowsky, Thomas R. Weikl. 2015-11-24. Binding constants of membrane-anchored receptors and ligands: a general theory corroborated by Monte Carlo simulations. https://doi.org/10.1063/1.4936134

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