Photo by Darren Baker
Researchers say they have created a model that can show how nearly any drug behaves in P-glycoprotein (P-gp), a protein associated with chemotherapy failure.
The team developed this computer-generated model to overcome the problem of relying on static images for the structure of P-gp.
When the researchers introduced drugs into the model, the drugs responded the way they do in real life and behaved according to predictions.
John G. Wise, PhD, of Southern Methodist University in Dallas, Texas, and his colleagues described the model in Biochemistry.
“The value of this fundamental research is that it generates dynamic mechanisms that let us understand something in biochemistry, in biology,” Dr Wise said. “And by understanding P-gp in such detail, we can now think of ways to better and more specifically inhibit it.”
Dr Wise and his colleagues noted that P-gp protects cells by pumping out toxins, but that can include chemotherapy drugs. So inhibiting P-gp’s pumping action might circumvent chemotherapy failure.
With than in mind, the team tested tariquidar, a P-gp inhibitor in clinical trials, in their model.
It hasn’t been clear exactly where tariquidar binds in P-gp. But the model showed the drug prefers to bind high in the protein. Tariquidar also behaved as expected. It wasn’t effectively pumped from the cell.
“Now we have more details on how tariquidar inhibits P-gp, where it inhibits, and what it’s actually binding to,” Dr Wise said.
He and his colleagues also used their model to uncover additional details about the behavior of other drugs in P-gp.
“For a long time, it’s been thought that there are at least a couple of distinct binding sites for drugs,” Dr Wise said.
“Sure enough, with our models, we found that [the chemotherapeutic agent] daunorubicin, at least, prefers to bind on one side of the P-gp model, while verapamil—a commonly prescribed blood pressure medicine—prefers the other side.”
Not only did the researchers show computationally that there are 2 different starting points for drugs, they also showed that there are 2 different pathways to get the drugs through.
“The 2 different drugs start at different sites, and they’re funneled to the outside by being pushed by the protein,” Dr Wise said. “But the actual parts of the protein that are pushing the drugs out are different.”
Drug discovery
Being able to watch molecular machinery up close, while it is doing its job the way it does in real life, may spark new drug discoveries to fight cancer, Dr Wise said.
“Having an accurate model that actually moves—that shows the dynamics of the thing—is incredibly helpful in developing therapies against a molecular target to inhibit it,” Dr Wise said. “The only other ways to do it are blind, and the chances of success using blind methods are very low.”
“Scientists have tried for 30 years to find inhibitors of this pump and have done it without knowing the structure and with only little knowledge about the mechanism, screening more or less blindly for compounds that inhibit the thing.”
“They found drugs that worked in the test tube and that worked in cultured cells but that didn’t work in the patient. With our model, because we can see the pump moving, we can probably predict better what’s going to make an inhibitor actually work well.”
Dr Wise and his colleagues used the P-gp model to virtually screen millions of publicly available compounds. They discovered 3 new drug leads that could ultimately inhibit P-gp and offer better odds of survival to prostate cancer patients.
The researchers reported these findings in Pharmacology Research & Perspectives.
Creating the model
To build the P-gp model, Dr Wise and his colleagues used static structures from the US Protein Data Bank repository. They used structures showing various stages of transport to simulate 4 points of reference.
From there, the team fed a supercomputer parameters and characteristics of the protein, as well as how it should behave physically, including when kinetic energy was added to bring the protein and its surrounding membrane and water up to body temperature.
The animated model resulted from calculating differences between 2 structures and using targeted molecular dynamics programs to slightly nudge the model to the next step.
“You do that several million times and make several trillion calculations, and you arrive at the next structure,” Dr Wise said. “In this way, we can nudge P-gp through a full catalytic transport cycle.”
Finally, using a docking program, the researchers individually introduced daunorubicin and other drugs into the protein and watched the drugs move through P-gp’s catalytic cycle.
“What happened was: the drugs moved,” Dr Wise said. “And they moved the way they should move, clinically, biochemically, physiologically, to pump the compounds out of the cell.”
Challenging the model
The researchers ran a critical control to further test if the model worked.
“We thought maybe anything you put in the protein, relevant or not, would get pumped through,” Dr Wise said. “So we put in something that is not a transport substrate of P-gp, something that, biochemically, would never be transported by P-gp.”
“We put it in, starting where daunorubicin is effectively pumped out, and, very quickly, the compound left the protein. But it left the opposite way, back into the cell. This experiment gave us more confidence that what we are seeing in these models is reflecting what happens in the cell.”
Dr Wise admitted that, until he saw it for himself, he had doubts the virtual P-gp model would behave like real-life P-gp.
“It’s a crude approximation of a complex, sophisticated human protein, but it’s so much better than the static images available now,” Dr Wise said.
“I’ve got to emphasize for all the disbelievers, for the ‘culture of doubters’ out there, that this model works. It moves the drugs through the membrane. That speaks for itself. What P-gp does in the cell, cancerous or normal, it does in our simulations.”
