期刊
JOURNAL OF THEORETICAL BIOLOGY
卷 229, 期 2, 页码 157-168出版社
ACADEMIC PRESS LTD ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jtbi.2004.03.012
关键词
dimerization; G-protein coupled receptor; Monte Carlo simulation; self-organization; internalization; signal transduction; protein-protein interactions; drug design; dimerization algebra; dimerization networks; dopamine; somatastatin; FRET
资金
- NIGMS NIH HHS [T32 GM145304, GM08353, R01 GM62930-01] Funding Source: Medline
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 D-2 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. (C) 2004 Elsevier Ltd. All rights reserved.
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