A new computational model from Scott Bornheimer, Shankar Subramaniam, and colleagues (University of California, San Diego, CA) predicts how the GTPase cycle operates in one of several modes.
Several GTPase cycle models exist, but many include only the G protein, its activator (often a receptor), GTP, GDP, and phosphate. Subramaniam's group added a GAP, the G protein deactivator, to the equations, and used experimental data from the GTPase cycle of a mouse G protein stimulated by a acetylcholine receptor (largely from Mukhopadhyay and Ross. PNAS. 96:9539–9544) to build their model.
“Variability in the concentration of the players in vivo is common,” says Subramaniam. “How will the cell achieve maximum or moderate turnover? What happens when it's starved of GAP? How can the cell compensate to accomplish the same end point?” The model can now predict answers to these questions.
Four modes were found in which G protein activity is unaltered by changes in receptor or GAP concentrations. Between these extremes are infinite variations. In some modes, particularly when G protein levels are low, the cycle operates while the G protein and receptor are not physically clustered. In this mode, GAPs are able to shut down G protein signaling entirely.
In other situations, clustering is required for G protein activity, and GAPs can change the signaling amplitude but cannot eliminate it. The authors are now using FRET to determine how local clustering changes with altered component concentrations.