Tag: John Wise

Drugs behave as predicted in computer model of key protein, enabling cancer drug discovery

Post author By Margaret Allen
Post date September 8, 2015

New model allows pharmacological researchers to dock nearly any drug and see how it behaves in P-glycoprotein, a protein in the cell associated with failure of chemotherapy

Drugs important in the battle against cancer responded the way they do in real life and behaved according to predictions when tested in a computer-generated model of one of the cell’s key molecular pumps — the protein P-glycoprotein, or P-gp.

Biologists at Southern Methodist University, Dallas, developed the computer generated model to overcome the problem of relying on only static images for the structure of P-gp, said biologist John G. Wise, lead author on the journal article announcing the advancement.

The new SMU 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 Wise, an associate professor in SMU’s Department of Biological Sciences.

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

P-gp 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 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.

SMU researchers report that their computer model simulation reveals the binding sites of Tariquidar — a P-gp inhibitor — as the “pump” opens and closes. (Image: James McCormick) — SMU researchers report that their computer model simulation reveals the binding sites of Tariquidar (orange blob) — a P-gp inhibitor. (Image: James McCormick)

Also using the model, the researchers discovered greater detail than previously known about the behavior of other drugs as well, and how those drugs bind in P-gp to stop its pumping action.

The study was funded in part by the National Institutes of Health. The lab was recently awarded a second NIH grant for the research.

The findings are published in the journal Biochemistry. The article, “Multiple drug transport pathways through human P-glycoprotein,” is published online in advance of print at NIH’s PubMed Central.

A still image of the modeled protein in action will appear on the cover of the October through December issues of Biochemistry.

Testing the virtual P-gp model by virtually docking real drugs
Wise and his colleagues tested one of the workhorse drugs of chemotherapy, daunorubicin, a close cousin of Adriamycin.

An aggressive chemotherapeutic, daunorubicin stops DNA replication in the cell, and is a classic target for P-gp to pump out of a cell, Wise said.

“For a long time, it’s been thought that there are at least a couple of distinct binding sites for drugs,” Wise said. “Sure enough, with our models, we found that 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 two different starting points for drugs, they also showed that there are two different pathways to get the drugs through.

“The two different drugs start at different sites and they’re funneled to the outside by being pushed by the protein,” Wise said. “But the actual parts of the protein that are pushing the drugs out are different.”

Wise and his co-authors, SMU biologists Pia Vogel and James McCormick, created the P-gp computer-generated simulation using SMU’s High Performance Computer, ManeFrame.

Molecular model can aid in fight against multi-drug resistance of cancer cells
The capability of watching molecular machinery up close, while doing its job the way it does in real life, may spark new drug discoveries to fight cancer.

“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. The only other ways to do it are blind, and the chances of success using blind methods are very low,” Wise said.

“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,” Wise said. “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.”

Vogel and Wise led a team of researchers in using the P-gp model to virtually screen millions of publically available drug-like compounds.

Verapamil (green blob), inhibits the P-gp pump. But until now, the workings of the pump could not be observed so researchers could only speculate where Varapamil “binds” in P-gp. SMU researchers report that their computer model simulation reveals Varapamil’s binding sites while the “pump” opens and closes. (Image: McCormick) — Verapamil (green blob), inhibits the P-gp pump. Until now, the workings of the pump could not be observed so researchers didn’t know exactly where Varapamil “binds” in P-gp. SMU researchers report that their simulation reveals the binding sites. (Image: McCormick)

They discovered three new drug leads that could ultimately inhibit P-gp and offer better odds of survival to prostate cancer patients. The researchers reported those findings this month in the journal Pharmacology Research & Perspectives, http://bit.ly/1XGjN5w.

New SMU model simulates molecular machinery in action
Researchers look for drug compounds that can temporarily stop or inhibit the P-gp pump, so that the chemotherapy drugs that enter the cancer cell will stay there and do the job of killing the cancer. Finding the right pump inhibitor requires understanding the pumping action. That’s difficult without seeing the pump at work.

The structures of proteins similar to P-gp have been previously available in a static state through X-ray crystallography. Scientists use X-ray crystallography as a tool that essentially draws the details of biological structures by identifying their atomic and molecular structure through diffraction of X-rays by the atoms themselves.

Scientists often contribute the resulting protein structures to the U.S. Protein Data Bank repository for public use.

Detailed data combined with several trillion calculations produced model
To build the P-gp model, Wise used structures from the repository, showing various stages of transport, to simulate four points of reference. From there, SMU’s ManeFrame supercomputer was fed 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 two 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,” 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,” Wise said. “And they moved the way they should move, clinically, biochemically, physiologically, to pump the compounds out of the cell.”

Vogel added that, “in some of the zoom-ins of the model, you can actually see the amino acids paddle down the drugs.”

Further challenging and testing 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. So we put in something that is not a transport substrate of P-gp, something that biochemically would never be transported by P-gp,” Wise said. “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.”

Wise admits that until he saw it for himself, even 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,” 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.”

Tags Dedman College, James McCormick, John Wise, Pia Vogel, SMU Department of Biological Sciences

Health & Medicine Researcher news Videos

Researchers discover new drug-like compounds that may improve odds for men battling prostate cancer

Post author By Margaret Allen
Post date September 8, 2015

New drug-like compounds have low toxicity to noncancerous cells, but inhibit the human protein often responsible for chemotherapy failure

Researchers at Southern Methodist University, Dallas, have discovered three new drug-like compounds that could ultimately offer better odds of survival to prostate cancer patients.

The drug-like compounds can be modified and developed into medicines that target a protein in the human body that is responsible for chemotherapy resistance in cancers, said biochemist Pia D. Vogel, lead author on the scientific paper reporting the discovery.

So far there’s no approved drug on the market that reverses cancer chemotherapy resistance caused by P-glycoprotein, or P-gp for short, said Vogel, a biochemistry professor at SMU. One potential drug, Tariquidar, is currently in clinical trials, but in the past, other potential drugs have failed at that stage.

“The problem when a person has cancer, is that the treatment itself is composed of cellular toxins — the chemotherapeutics that prevent the cells from dividing. Usually upon the first chemotherapy treatment the cancer responds well, and initially goes away. Ideally it doesn’t come back,” said Vogel, director of SMU’s Center for Drug Discovery, Design and Delivery.

Three drug-like compounds bind in human P-glycoprotein, reversing chemotherapy resistance in prostate cancer cells in culture. (Image, James McCormick)

“Sometimes, however, the cancer returns,” she said. “The reason often is that some of the cancer cells “learn,” after the first rounds of chemotherapy, how to make a lot of this P-gp pump. The normal function of P-gp is to pump toxins from cells, so it has evolved to protect cells against a large variety of toxins, including almost all currently available chemotherapeutics. After initial exposure, the cells surviving the chemo make so much P-gp that it allows the cells to pump the chemotherapy drugs straight back out of the cells during subsequent rounds of treatment.”

As a result, P-gp causes resistance of the diseased cells to a majority of drugs currently available for the treatment of cancer, as well as drugs used for treatment of infectious diseases like HIV/AIDS.

Using computer-generated model speeds up the drug discovery process
The new drug-like compounds discovered by Vogel and her co-authors offer hope that using a computer-generated P-gp model, developed to accurately mimic the physical, chemical and biological functions of the protein in the human body, will speed up the drug discovery process and work in real life as well.

P-glycoprotein's pumping action is stalled, when a drug-like compound (dark blue) prevents the power source (red) from being used by P-glycoprotein, the protein that transports toxins from a cell. (Image: James McCormick) — P-glycoprotein’s pumping action is stalled, when a drug-like compound (dark blue) prevents the power source (red) from being used by P-glycoprotein, the protein that transports toxins from a cell. (Image: James McCormick)

“These are not drugs yet. We still have to develop them before they can go in the clinic,” Vogel said. “But what we know now is that they’re not toxic — they have low toxicity to noncancerous cells, so that’s a pretty good predictor that they may be good candidates for drug development. But we need to do much more work.”

A pharmaceutical hit compound, like those discovered by Vogel and her co-authors, is a compound that is a promising candidate for chemical modification so it can eventually be delivered to patients as a therapeutic drug. In the case reported here, the compounds were commercially available for testing. The timeline from drug discovery to development to clinical trials and approval can take a decade or more.

Vogel and her co-authors, SMU biologist John G. Wise, and doctoral candidates Courtney A. Follit and Frances K. Brewer, reported their findings in the journal Pharmacology Research & Perspectives. The article, “In silico identified targeted inhibitors of P-glycoprotein in culture,” is published online at http://bit.ly/1JjFizg.

The research was funded in part by the National Institutes of Health. The lab was recently awarded a second grant from the Institute.

Researchers virtually screened 15 million drug-like compounds via SMU supercomputer
The SMU researchers discovered the three hit compounds after virtually screening more than 15 million small drug-like compounds made publically available in digital form from the pharmacology database Zinc at the University of California, San Francisco.

Using SMU’s ManeFrame high performance computer, Wise ran the compounds through a computer-generated model of P-gp. The virtual model, designed and built by Wise, is the first computational microscope of its kind to simulate the actual behavior of P-gp in the human body, including interactions with drug-like compounds while taking on different shapes.

The ultra-high throughput computational searches by ManeFrame led the researchers to 300 compounds that looked like they may inhibit P-gp. The researchers then tested 38 of those in their physical lab and found four that inhibited the biochemical function of P-gp, stopping it in its action.

Each of the four compounds was then tested in the lab to see how it would affect a line of prostate cancer cells relatively sensitive to the chemotherapeutic Paclitaxel, commonly used to treat prostate cancer patients. Also, each was tested on a companion cell line already multi-drug resistant, as if the patient already had undergone chemotherapy using Paclitaxel.

The researchers found that with three of the four compounds, they were able to push back the sensitivity of the resistant cancer line to the level of the non-resistant one.

“So the compounds re-sensitized the cancer cell lines to a really high degree, just as if the cancer was seeing the chemotherapy for the first time,” Vogel said.

About 14 percent of men will be diagnosed over their lifetime with prostate cancer, according to the National Cancer Institute. Survival is highest if diagnosed early before it has spread, the institute reports.

Tags Center for Drug Discovery, Courtney A. Follit, Dedman College, Frances K. Brewer, John Wise, Pia Vogel, SMU Department of Biological Sciences

Learning & Education Researcher news Technology

The power of ManeFrame: SMU’s new supercomputer boosts research capacity

Post author By Margaret Allen
Post date March 20, 2014

The enormous capacity of SMU’s new supercomputer ranks it among the largest academic supercomputers in the nation.

ManeFrame, previously known as MANA, was relocated to Dallas from its previous location in Maui, Hawaii. (Courtesy of mauinow.com) — ManeFrame, previously known as MANA, was relocated to Dallas from its former location in Maui, Hawaii. (Courtesy of mauinow.com)

SMU now has a powerful new tool for research – one of the fastest academic supercomputers in the nation – and a new facility to house it.

With a cluster of more than 1,000 Dell servers, the system’s capacity is on par with high-performance computing (HPC) power at much larger universities and at government-owned laboratories. The U.S. Department of Defense awarded the system to SMU in August 2013.

SMU’s Office of Information Technology added the system to the University’s existing – but much smaller – supercomputer. The system is housed in a new facility built at the corner of Mockingbird and Central Expressway. In a contest sponsored by Provost and Vice President for Academic Affairs Paul W. Ludden, faculty and students chose the name “ManeFrame” to honor the Mustang mascot.

The enormous capacity and speed of HPC expands scientific access to new knowledge around key questions about the universe, disease, human behavior, health, food, water, environment, climate, democracy, poverty, war and peace.

“World-changing discoveries rely on vast computing resources,” says President R. Gerald Turner. “ManeFrame quintuples the University’s supercomputing capacity. Our scientists and students will keep pace with the increasing demand for the ever-expanding computing power that is required to participate in global scientific collaborations. This accelerates our research capabilities exponentially.”

ManeFrame potential
With nearly 11,000 central processing unit cores, ManeFrame boasts 40 terabytes (one terabyte equals a trillion bytes) of memory and more than 1.5 petabytes of storage (a petabyte equals a quadrillion bytes), says Joe Gargiulo, SMU’s chief information officer, who led the installation team.

The sciences and engineering primarily use supercomputers, but that is expanding to include the humanities and the arts. So far, SMU’s heavy users are researchers in physics, math, biology, chemistry and economics.

“This technologically advanced machine will have an impact on shaping our world,” says Thomas M. Hagstrom, chair of the Department of Mathematics in Dedman College and director of SMU’s Center for Scientific Computing. “This makes research that solves problems on a large scale much more accessible. ManeFrame’s theoretical peak would be on the order of 120 Teraflops, which is 120 trillion mathematical operations a second.”

Supercomputers can use sophisticated software and step-by-step procedures for calculations, called algorithms, to solve complex problems that can’t be managed in a researcher’s lab, Hagstrom explains.

“We can’t put the Earth’s climate system or study the evolution of the universe in a physical lab,” he says. “You can only study these and other systems in a comprehensive way using high-performance computing.”

Making SMU competitive
Supercomputing gave University physicists a role in the Higgs Boson research at the Large Hadron Collider in Geneva, Switzerland. Joining the collaboration with thousands of scientists around the world, SMU’s team was led by Physics Professor Ryszard Stroynowski. SMU’s physicists tapped the existing HPC on campus to quickly analyze massive amounts of data and deliver results to their international colleagues.

SMU’s team will use ManeFrame to keep pace with an even larger flood of data expected from the Large Hadron Collider.

“ManeFrame makes SMU – which is small by comparison with many of its peer institutions at CERN – nimble and competitive, and that lets us be visible in a big experiment like CERN,” says Stephen Sekula, assistant professor of physics. “So we have to have ideas, motivation and creativity – but having a technical resource like ManeFrame lets us act on those things.”

SMU physicist Pavel Nadolsky has conducted “big data” analyses of subatomic particles on the supercomputer as part of an international physics collaboration. Big data refers to probability distributions that depend on many variables. As users ranging from retailers to the health industry collect multitudes of transactional data every day, requirements for big data analysis are rapidly emerging.

“To keep up in our field, we need resources like ManeFrame,” says Nadolsky, associate professor of physics.

“The world is moving into big-data analysis, whether it’s Google, Facebook or the National Security Administration,” Nadolsky says. “We learn a lot about the world by studying multidimensional distributions: It tells about the origins of the universe; it can win elections by using data mining to analyze voting probabilities over time in specific geographical areas and targeting campaign efforts accordingly; and it can predict what people are doing. To make students competitive they must be trained to use these tools efficiently and ethically.”

ManeFrame will have a high-profile role in the U.S. Department of Energy experiment called NOvA, which studies neutrinos, a little-understood and elusive fundamental particle that may help explain why matter, and not just light, exists in the universe today. SMU will contribute four million processing hours each year to the experiment, says Thomas E. Coan, associate professor of physics and a member of the international team.

“We’re in good company with others providing computing, including California Institute of Technology and Harvard,” Coan says. “It’s one way for SMU to play a prominent role in the experiment. We get a lot of visibility among all the institutions participating in NOvA, which are spread out across five countries.”

Advancing discovery
One of the heaviest users of SMU’s HPC is John Wise, associate professor of biological sciences, who models a key human protein to improve chemotherapy to kill cancer cells. Wise works with the SMU Center for Drug Discovery, Design and Delivery in Dedman College, an interdisciplinary research initiative of the Biology and Chemistry departments and led by Professor of Biological Sciences Pia Vogel.

Within the Mathematics Department, Assistant Professor Daniel R. Reynolds and his team use high-performance computing to run simulations with applications in cosmology and fusion reactors.

Looking to the future, high-performance computing will be increasing in research, business and the arts, according to James Quick, associate vice president for research and dean of graduate studies.

“High-performance computing has emerged as a revolutionary tool that dramatically increases the rates of scientific discovery and product development, enables wise investment decisions and opens new dimensions in artistic creativity,” says Quick, professor of earth sciences. “SMU will use the computational power of ManeFrame to expand research and creativity and develop educational opportunities for students interested in the application of high-performance computing in their fields – be it science, engineering, business or the arts.” – Margaret Allen

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Tags Daniel R. Reynolds, Dedman College, James E. Quick, Joe Gargiulo, John Wise, ManeFrame, Paul W. Ludden, Pia Vogel, R. Gerald Turner, Ryszard Stroynowski, Thomas E. Coan, Thomas Hagstrom

Health & Medicine Technology Videos

Moving 3D computer model of key human protein is powerful new tool in fight against cancer

Post author By Margaret Allen
Post date June 19, 2012

Powerful discovery tool is at work screening millions of drugs in the search to reverse chemotherapy drug resistance in cancer

A picture is worth 1,000 words when it comes to understanding how things work, but 3D moving pictures are even better. That’s especially true for scientists trying to stop cancer by better understanding the proteins that make some chemotherapies unsuccessful.

Researchers for decades have had to rely at best on static images of the key proteins related to recurring cancers.

Now SMU biochemist John G. Wise at Southern Methodist University, Dallas, has brought to life in a moving 3D computer model the structure of human P-glycoprotein, which is thought to contribute to the failure of chemotherapy in many recurring cancers.

“This is a very different approach than has been used historically in the field of protein structure biochemistry,” Wise said. “Historically, proteins are very often viewed as static images, even though we know that in reality these proteins move and are dynamic.”

The model is a powerful new discovery tool, says Wise, particularly when combined with high-performance supercomputing. The dynamic 3D model already has made it possible for Wise to virtually screen more than 8 million potential drug compounds in the quest to find one that will help stop chemotherapy failure. (Youtube video) (Flickr images)

So far, the supercomputer search has turned up a few hundred drugs that show promise, and Wise and SMU biochemist Pia Vogel have begun testing some of those compounds in their wet lab at SMU.

“This has been a good proof-of-principle,” said Wise, a research associate professor in the SMU Department of Biological Sciences.

“We’ve seen that running the compounds through the computational model is an effective way to rapidly and economically screen massive numbers of compounds to find a small number that can then be tested in the wet lab.”

Wise describes his research findings in Biochemistry in the article “Catalytic Transitions in the Human MDR1 P-Glycoprotein Drug Binding Sites” online.

The research is funded by the National Institute of General Medical Sciences, National Institutes of Health.

Seeking new drugs that would allow chemotherapeutic compounds to enter and destroy cancer cells
Since the 1970s it has been known that the so-called multidrug resistance protein, P-gp, is most likely responsible for the failure of many chemotherapy drugs. P-gp is nature’s way of pumping toxins from a cell, but if cancer cells express more P-gp than cells normally would, the chemotherapy is no longer effective because the protein considers it a toxin and pumps it out before it can destroy the cancer.

“We’re looking for small molecules that will temporarily inhibit the pump; a new drug that could be co-administered with the chemotherapeutic and that stops the sump pump in the cancer cell so that the cancer chemotherapy can remain in the cell and kill the cancer,” Wise said.

High-performance computer enables millions of digital screenings
Wise has run about 10.5 million computational hours since August 2009 and has screened roughly 8 million potential drugs against different protein structures.

SMU biochemists Pia Vogel and John Wise have paired a moving 3D computer model of a key human protein together with the SMU supercomputer to search for potential drugs to stop chemotherapy failure.
(Image: Hillsman Jackson, SMU)

“We are currently screening about 40,000 compounds per day on SMU’s High Performance Computer,” Wise said.

“We found a couple hundred compounds that were interesting, and so far we chose about 30 of those to screen in the lab,” Vogel said. “From those, we found a handful of compounds that do inhibit the protein. We were thrilled. Now we’re going back into the models and looking for other compounds that might be able to throw a stick in the pump’s mechanism.”

Massive increases in computational power in recent years have made the screening research possible, Wise said. “Ten years ago you couldn’t have docked 8 million compounds — there just wasn’t enough computational power.”

Human P-gp: “We don’t know what it looks like exactly.”
Every organism has a version of P-gp. Its structure has been previously determined for some organisms — mostly bacteria, but also in mice — by studying the arrangement of atoms within protein crystals. However, the exact structure of the human enzyme remains unclear. Wise deduced the structure of human P-gp by relying on evolutionary relationships and scientific understanding of how proteins are put together. He then used computer programs to model the protein in a way that brings the static picture of the human pump to life in the computer. (Youtube: Moving model)

To develop the model, Wise used freely available simulation software developed by researchers at the University of Illinois, the National Institutes of Health and the Scripps Research Institute. Wise and Vogel use compounds from ZINC, a free database of more than 21 million commercially available compounds for virtual screening. ZINC is provided by the Department of Pharmaceutical Chemistry at the University of California, San Francisco.

“We can physically build these molecules in the computer, in silico, and computationally we can model a variety of conditions: We can raise the temperature to 37 degrees Centigrade, we can have the right salts and all the right conditions, just like in a wet-lab experiment. We can watch them thermally move and we can watch them relax,” Wise said. “The software is good enough that the model will move according to the laws of physics and the principles of biochemistry. In this way we can see how these compounds interact with the protein in a dynamic way, not just in a snapshot way.”

Even with the 3D dynamic model and a supercomputer, the odds are stiff
Theoretically, if a drug can be found that temporarily knocks out the sump-pump proteins, then all those cancer chemotherapies that don’t work for a patient will work again.

“The ultimate goal of our research would be to find a compound that is safe and effective,” Wise said. Even with a supercomputer, however, the odds are steep.

“Out of a hundred good inhibitors that we might find, 99 of them might be extremely toxic and can’t be used. In the pharmaceutical industry there are many, many candidates that fall by the wayside for one reason or another,” he said. “They metabolize too quickly, or they’re too toxic, or they’re not soluble enough in the acceptable solvents for humans. There are many different reasons why a drug can fail. Finding a handful has been a great confirmation that we’re on the right track, but I would be totally amazed if one of the first we’ve tested was the one we’re looking for.”

Vogel is an associate professor and director of SMU’s Center for Drug Discovery, Design and Delivery. CD4 was launched by SMU’s Biological Sciences and Chemistry departments and has as its mission the search for new drug therapies and delivery methods that can be developed into clinical applications. — Margaret Allen

Tags Center for Drug Discovery Design and Delivery, Dedman College, John Wise, Pia Vogel, SMU Department of Biological Sciences

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Modeling the human protein in search of cancer treatment: An SMU Researcher Q&A

Post author By Margaret Allen
Post date March 27, 2012

SMU biologists tap supercomputer in fight against recurring cancer when chemotherapy fails

SMU biologists Pia Vogel and John Wise in the SMU Department of Biological Sciences are using the computational power of the SMU high-performance supercomputer to screen millions of drug compounds. They hope to find one that will aid in the fight against recurring cancer.

Vogel is an associate professor and director of SMU’s Center for Drug Discovery, Design and Delivery*. Wise is a research associate professor. Together they are seeking a compound that can be developed into a drug that re-enables chemotherapy when cancer recurs and chemotherapy appears no longer effective.

In the following interview, Vogel and Wise discuss their quest, made possible by the massive computational power supplied by supercomputers — a technique not possible even a decade ago.

Q: You’re searching for a cancer drug that provides hope for chemotherapy failure?

Vogel: Yes. Since the 1970s it’s been known that a sort of sump pump, the protein called P-glycoprotein, is most likely responsible for the failure of many chemotherapies — the drug is being pumped out of cancer cells by this sump pump that occurs naturally within all cells, even cancer cells.

Q: Tell us about P-glycoprotein.
Wise: This particular protein is one of nature’s great solutions to the problem of getting toxic things out of the cell. When a toxic substance enters a cell, the protein pumps it out.

This process may become a problem, however, once a cancer patient has been treated with chemotherapy, and appears to be cured.

If the cancer later returns, the cancer cells may express more P-glycoprotein than cells normally would. For that reason, chemotherapy is no longer effective because the protein considers it a “toxin” and pumps it out of the cells before the chemotherapy can destroy the cancerous cell.

Theoretically, if we can knock out the sump-pump proteins, then all those cancer chemotherapies that don’t work anymore, will work again.

Q: How does the sump pump work?
Wise: P-glycoprotein has a generic binding site for drugs. When the drug binds, that activates the part of the protein that uses the energy in ATP energy molecules by breaking the ATP down. This release of energy from ATP then moves the drug from one side of the protein to the other. It turns out that the “other side” of the protein is on the outside of the cell, so the drug has just been pumped out of the cell. The process takes only a fraction of a second and moves the drug from inside the cell, where it would kill the cancerous cell, to the outside where it is essentially harmless to the cancer.

So nature’s kind of outfoxing us here, because the pump has this beautiful generic toxin-binding site that allows the cells to survive. The downside is in cancer chemotherapy. Here the “toxin” is actually the drug we are hoping will kill the cancer and it will also be pumped out. So what we are doing is we’re looking for drugs that will temporarily inhibit the pump. What we’re hoping for is a new drug that stops the sump pump in the cancer cell so that the cancer chemotherapy can remain in the cell so it can kill the cancer.

Q: Tell us about the search.
Wise: Everything that lives has a version of this type of protein. So there are evolutionary connections between bacterial versions of this protein and the human versions. They all seem to work the same way, and are close in structure and function.

No one has actually determined the structure of the human P-glycoprotein directly. We don’t know what it looks like. Relying on these evolutionary relationships and with our understanding of how proteins are put together, I’ve deduced a structure of the human protein. We then use computer programs to model the protein in a way that brings the static picture of the human pump to life in the computer.

This is a very different tack than has been used historically in the field of protein structure biochemistry. Historically, proteins are very often viewed as static images, even though we know that in reality these proteins move and are dynamic.

Using simulation software (NAMD Molecular Dynamics, a freely downloadable software developed by researchers at the University of Illinois), we can physically build these molecules in the computer, in silico, and computationally we can model a variety of conditions: We can raise the temperature to 37 degrees centigrade, we can have the right pH, the right salts and all the right conditions, just like in a wet lab experiment. We can watch them thermally move and we can watch them relax.

The software is good enough that the model will relax and move according to the laws of physics and biochemistry. In this way we can see how these compounds interact with the protein in a dynamic way, not just in a snapshot way.

Q: How many screenings have you carried out on the supercomputer?
Wise: So far we’ve run about 8.8 million computational hours since August 2009, and screened roughly 8 million drugs. We are currently screening about 50,000 drugs per day on SMU’s High Performance Computer.

Vogel: We found a couple hundred compounds that were interesting, and so far we chose about 30 of those to screen in the lab. From those, we found a handful of compounds that do inhibit the protein. So we were very thrilled about that. Now we’re going back into the models that John has created and we’re looking for other compounds that might be able to throw a stick in the pump’s mechanism. We’re going at it in a selective way, so we don’t waste money with huge high-throughput screening assays in the lab.

Q: What have you learned so far?
Wise: This has been a good proof-of-principle. We’ve seen that running the compounds through the computational model is an effective way to rapidly and economically screen massive numbers of compounds to find a small number that can then be tested in the wet lab.

Q: Why is this kind of research possible now?
Wise: There have been huge increases in computational power in recent years. Ten years ago you couldn’t dock 8 million drugs — there just wasn’t enough computational power. Now SMU owns enough to do that.

Q: Has anyone else used the software in this way?
Wise: I don’t think anyone else has looked at 8 million drugs. And I’m almost positive that no one has looked at drug binding dynamically on that scale.

Q: How have you tested it in the lab?
Vogel: We use the purified protein itself and see whether those compounds really inhibit the power stroke, the ATP hydrolysis. We work with mouse protein, which is closely related to the human protein, but a little more stable.

Q: What’s the next step?
Vogel: We’ll collaborate with cell culture researchers here at SMU’s Center for Drug Discovery, Design and Delivery* and see if the compounds are toxic to cultured cancer cells and whether they will reverse chemo-resistance in some cell lines that we know do not respond to chemotherapeutics.

Wise: The ultimate goal of our research would be a compound that is safe and effective. To give an idea of the odds, out of a hundred good inhibitors that we might find, 95 of them might be extremely toxic and can’t be used. In the pharmaceutical industry, there are many, many candidates that fall by the wayside for one reason or another. They metabolize too quickly, or they’re too toxic, or they’re not soluble enough in the acceptable solvents for humans. There are many different reasons why a drug can fail. Finding a handful has been a great confirmation that we’re on the right track, but I would be totally amazed if one of the first we’ve tested was the one we’re looking for. — Margaret Allen

Tags Center for Drug Discovery Design and Delivery, Dedman College, John Wise, Pia Vogel, SMU Department of Biological Sciences

New model allows pharmacological researchers to dock nearly any drug and see how it behaves in P-glycoprotein, a protein in the cell associated with failure of chemotherapy

New drug-like compounds have low toxicity to noncancerous cells, but inhibit the human protein often responsible for chemotherapy failure

The enormous capacity of SMU’s new supercomputer ranks it among the largest academic supercomputers in the nation.

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