Concentration Sensing in Crowded Environments

Signal transduction within crowded cellular compartments is essential for the physiological function of cells and organisms. While the accuracy with which receptors can probe the concentration of ligands has been thoroughly investigated in dilute systems, the effect of macromolecular crowding on the inference of concentration remains unknown. In this work we develop a novel algorithm to simulate reversible reactions between reacting Brownian particles. This facilitates the calculation of reaction rates and correlation times for ligand-receptor systems in the presence of macromolecular crowding. Using this method, we show that it is possible for crowding to increase the accuracy of estimated ligand concentration based on receptor occupancy. In particular, we find that crowding can enhance the effective association rates between small ligands and receptors to a large enough degree to overcome the increased chance of rebinding due to caging by crowding molecules. For larger ligands, crowding decreases the accuracy of the receptors estimate primarily by decreasing the microscopic association and dissociation rates. SIGNIFICANCEDeveloping an understanding of how cells effectively transmit signals within or between compartments under physical constraints is an important challenge for biophysics. This work investigates the effect that macromolecular crowding can have on the accuracy of a simple ligand-receptor signaling system. We show that the accuracy of an inferred ligand concentration based on the occupancy of the receptor can be enhanced by crowding under certain circumstances. Additionally, we develop a simulation algorithm that speeds the calculation of reaction rates in crowded environments and can be readily applied to other, more complex systems.