Research: Computer model of key protein helps predict how cancer drugs will work

Drugs important in the battle against cancer behaved according to predictions when tested in a computer-generated model of P-glycoprotein, one of the cell’s key molecular pumps.

The new model allows researchers to dock nearly any drug in the P-gp protein and see how it will actually behave in P-gp’s pump, said Associate Professor John G. Wise, lead author on the journal article announcing the advancement and a faculty member in SMU’s Department of Biological Sciences, Dedman College of Humanities and Sciences.

SMU biologists developed the computer generated model to overcome the problem of relying on only static images for the structure of P-gp. The protein is the cellular pump that protects cells by pumping out toxins.

But that’s a problem when P-gp targets chemotherapy drugs as toxic, preventing chemo from killing cancer cells. Scientists are searching for ways to inhibit P-gp’s pumping action.

“The value of this fundamental research is that it generates dynamic mechanisms that let us understand something in biochemistry, in biology,” Wise said. “And by understanding P-gp in such detail, we can now think of ways to better and more specifically inhibit it.”

The SMU researchers tested Tariquidar, a new P-gp inhibitor still in clinical trials. Inhibitors offer hope for stopping P-gp’s rejection of chemotherapeutics by stalling the protein’s pumping action. Pharmacology researchers disagree, however, on where exactly Tariquidar binds in P-gp.

When run through the SMU model, Tariquidar behaved as expected: It wasn’t effectively pumped from the cell and the researchers observed that it prefers to bind high in the protein.

“Now we have more details on how Tariquidar inhibits P-gp, where it inhibits and what it’s actually binding to,” Wise said.

Written by Margaret Allen

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