An algebra of dimerization and its implications for G-protein coupled receptor signaling.

Many species of receptors form dimers, but how can we use this information to make predictions about signal transduction? This problem is particularly difficult when receptors dimerize with many different species, leading to a combinatoric increase in the possible number of dimer pairs. As an example system, we focus on receptors in the G-protein coupled receptor (GPCR) family. GPCRs have been shown to reversibly form dimers, but this dimerization does not directly affect signal transduction. Here we present a new theoretical framework called a dimerization algebra. This algebra provides a systematic and rational way to represent, manipulate, and in some cases simplify large and often complicated networks of dimerization interactions. To compliment this algebra, Monte Carlo simulations are used to predict dimerization's effect on receptor organization on the membrane, signal transduction, and internalization. These simulation results are directly comparable to various experimental measures such as fluorescence resonance energy transfer (FRET), and as such provide a link between the dimerization algebra and experimental data. As an example, we show how the algebra and computational results can be used to predict the effects of dimerization on the dopamine D2 and somatastatin SSTR1 receptors. When these predictions were compared to experimental findings from the literature, good agreement was found, demonstrating the utility of our approach. Applications of this work to the development of a novel class of dimerization-modulating drugs are also discussed.