This Article Full Text Full Text (PDF) All Versions of this Article: biophysj.105.065300v1 89/6/3686    most recent Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Gopalakrishnan, M. Articles by Täuber, U. C. Search for Related Content PubMed PubMed Citation Articles by Gopalakrishnan, M. Articles by Täuber, U. C.

Effects of Receptor Clustering on Ligand Dissociation Kinetics: Theory and Simulations

Manoj Gopalakrishnan ^* , Kimberly Forsten-Williams , Matthew A. Nugent  and Uwe C. Täuber 

^* Department of Biological Physics, Max-Planck-Institut für Physik Komplexer Systeme, Dresden, Germany; Department of Physics and Center for Stochastic Processes in Science and Engineering, Department of Chemical Engineering and Virginia Tech-Wake Forest University School of Biomedical Engineering and Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia; and Department of Biochemistry, Boston University School of Medicine, Boston, Massachusetts

Correspondence: Address reprint requests to Kimberly Forsten-Williams, Tel.: 540-231-4851; E-mail: kfw{at}vt.edu.

Receptor-ligand binding is a critical first step in signal transduction and the duration of the interaction can impact signal generation. In mammalian cells, clustering of receptors may be facilitated by heterogeneous zones of lipids, known as lipid rafts. In vitro experiments show that disruption of rafts significantly alters the dissociation of fibroblast growth factor-2 (FGF-2) from heparan sulfate proteoglycans (HSPGs), co-receptors for FGF-2. In this article, we develop a continuum stochastic formalism to address how receptor clustering might influence ligand rebinding. We find that clusters reduce the effective dissociation rate dramatically when the clusters are dense and the overall surface density of receptors is low. The effect is much less pronounced in the case of high receptor density and shows nonmonotonic behavior with time. These predictions are verified via lattice Monte Carlo simulations. Comparison with FGF-2-HSPG experimental results is made and suggests that the theory could be used to analyze similar biological systems. We further present an analysis of an additional cooperative internal-diffusion model that might be used by other systems to increase ligand retention when simple rebinding is insufficient.