Tags Posts tagged with "Markus Seeliger"

Markus Seeliger

Markus Seeliger, third from left, with members of his lab, from left, Terrence Jiang. Aziz Rangwala, Ian Outhwaite, Victoria Mingione,YiTing Paung, and Hannah Philipose. Photo from Markus Seeliger

By Daniel Dunaief

When a dart hits the center of a target, the contestant often gets excited and adds points to a score. But what if that well-placed dart slipped off the board before someone could count the points, rendering such an accurate throw ineffective?

With some cases of cancer treatments, that’s what may be happening, particularly when a disease develops a mutation that causes a relapse. Indeed, people who have chronic myeloid leukemia typically receive a treatment called Imatinib, or Gleevac.

The drug works, hitting a target called a kinase, which this white blood cell cancer needs to cause its cells to continue to divide uncontrollably. Patients, however, develop a mutation called N368S, which reduces the effectiveness of the drug.

While mutations typically make it more difficult for a drug to bind to its target, that’s not what’s happening with this specific mutation. Like the dart hitting the center of a board, the drug continues to reach its target.

Instead, in a model of drug resistance several scientists have developed, the mutation causes the drug to decouple.

Pratyush Tiwary with this year’s US top 20 students who are going to the international chemistry olympiad. Photo from Toward

A team of experimental and computational researchers including Markus Seeliger, Associate Professor of Pharmacological Sciences at Stony Brook University, and Pratyush Tiwary, Associate Professor in the Department of Chemistry & Biochemistry at the University of Maryland, published two research papers explaining a process that may also affect the way mutations enable resistance to other drugs.

Seeliger described how different disease-associated mutations bind to Gleevac in a paper published in the Proceedings of the National Academy of Sciences. 

Working with scientists at Memorial Sloan Kettering Cancer Center and Goethe University in Frankfurt, Germany, Seeliger used nuclear magnetic resonance spectroscopy, or NMR. The researchers showed how the drug bound to its target and then released.

Understanding the way diseases like cancer develop such resistance could affect drug discovery, giving pharmaceutical companies another way to prepare for changes diseases make that reduce the effectiveness of treatments.

A ‘hot paper’

Tiwary published research in which Seeliger was a coauthor in late April in the journal Angewandte Chemie that the publication labeled a “hot paper” for its implications in the field. Tiwary developed a way to simulate the kinetic processes that enable the mutated kinases to release the drug.

Tiwary created an artificial intelligence model that extended the time he analyzed the drug-protein interaction from milliseconds all the way out to thousands of seconds.

“Even within the simulation world, if you can quantitatively predict a binding affinity, that’s amazing,” Seeliger said. “It’s extremely hard to calculate kinetics, and he got that right.”

Tiwary, who started talking with Seeliger about five years ago and has been actively collaborating for about three years, uses experimental data to inform the dynamics that affect his simulations.

Seeliger “had done the experiments of the dissociation rates beforehand, but did not have a way to explain why they were what they were,” Tiwary explained in an email. “Our simulations gave him insights into why this was the case and … insight into how to think about drugs that might dissociate further.”

Drug discovery

Tiwary hopes the work enables researchers to look at structural and kinetic intermediates in reactions, which could provide clues about drug design and delivery. While he worked with a single mutation, he said he could conduct such an analysis on alterations that affect drug interactions in other diseases.

He wrote that the computations, while expensive, were not prohibitive. He used the equivalent of 16 independent 64 CPUs for one to two weeks. He suggested that computing advances could cut this down by a factor of 10, which would enable the exploration of different mutations.

“The methods are now so easy to automate that we could run many, many simulations in parallel,” Tiwary explained. Machine learning makes the automation possible.

Given what he’s learned, Tiwary hopes to contribute to future drug begin that addresses mutation or resistance to treatment in other cancers. He also plans to continue to work with Seeliger to address other questions.

Next steps

Seeliger said he plans to extend this work beyond the realm of this specific type of cancer.

He will explore “how common these kinetic mutations are in other systems, other diseases and other kinases,” Seeliger said.

He would also like to understand whether other proteins in the cell help with the release of drugs or, alternatively, prevent the release of drugs from their target. The cell could have “other accessory proteins that help kick out the drug from the receptor,” Seeliger said.

The concept of drug resistance time comes from infectious disease, where microbes develop numerous mutations.

Seeliger, who is originally from Hanover, Germany, said he enjoys seeing details in any scene, even outside work, that others might not notice. 

He described how he was driving with postdoctoral fellows in Colorado when he spotted a moose. While the group stopped to take a picture, he noticed that the moose had an ear tag, which is something others didn’t immediately notice.

As for the research collaboration, Seeliger is pleased with the findings and the potential of the ongoing collaboration between experimental and computational biologists.

“The computational paper, aside from using interesting new methodology, describes why things are happening the way they are on a molecular level,” he said.

Markus Seeliger with a model of a protein kinase. Photo from SBU

By Daniel Dunaief

They are like couples looking for each other on a dating website. Each side could theoretically find a range of connections. The focus in this dating game, however, has heavily favored understanding the preferences of one side. 

Markus Seeliger, an associate professor in the Department of Pharmacological Sciences at the Stony Brook University Renaissance School of Medicine, has taken important steps to change that, albeit in a completely different area. Instead of working with two people who are searching for a date, Seeliger studies the interactions among protein kinases, which are like switches that turn on or off cellular signals, and inhibitors, which researchers and drug companies are creating to slow down or stop the progression of diseases.

Markus Seliger

Most scientists have looked at the pairing of these molecules and protein kinases from the perspective of the inhibitor, trying to figure out if it would bind to one of the 500 protein kinases in the human body.

Seeliger, however, is exploring the coupling from the other side, looking at the selectivity of the kinases. He published recent research in the journal Cell Chemical Biology.

“People have only ever looked at the specificity from the point of view of an inhibitor,” Seeliger said. “We’ve turned it around. We’re looking at it from the perspective of kinases,” adding that kinases have been important drug targets for decades.

In an email, Michael Frohman, a SUNY distinguished professor and the chair of the Department of Pharmacological Sciences, applauded Seeliger’s efforts and said his research “is representative of the innovative work going on in many of the labs here.” 

On a first level, Seeliger discovered eight kinases that bind to a range of potential inhibitors, while the others are more selective.

Within the smaller group that binds a range of inhibitors, there was no sequence relationship between the base pairs that formed the kinases. The kinases are also not closely related in the cellular functions they regulate. They all trigger similar signaling cascades. 

Seeliger wanted to know why these eight kinases were four to five times more likely to couple with an introduced inhibitor than their more selective kinase counterparts. The Stony Brook scientist performed a three-dimensional analysis of the structure of one of these kinases at Brookhaven National Laboratory.

“They have a very large binding pocket that can accommodate many different inhibitors,” Seeliger said. Indeed, he discovered this higher level of receptivity by separating out this group of eight, which also had more flexible binding sites. If the match between the configuration of the inhibitor and the kinase isn’t perfect, the kinase can still find a way to allow the molecule to connect.

For any potential inhibitor introduced into the human body, this more flexible and accommodating group of kinases could cause unintended side effects regardless of the level of specificity between the inhibitor or drug and other targets. This could have health implications down the road, as other researchers may use the properties of these kinases to switch off programs cancer or other diseases use to continue on their destructive paths.

“Studies point to the roles of protein kinases as driving (to at least allowing and permitting) cancer growth and development,” Yusuf Hannun, the director of the Stony Brook University Cancer Center, explained in an email. “Therefore, one needs to inhibit them.”

Hannun described Seeliger as “very rigorous” and suggested he was an “up and coming scientist” whose “novel approach” shed significant new light on protein kinases.

In his research, Seeliger’s next step is to look at the existing database to see what other groups of kinases he finds and then determine why or how these switches have similarities to others in other systems or regions of the body.

Seeliger likened kinases to a control panel on a space shuttle. “Nothing about the sequence tells you about the role of the switches,” which would make it difficult for astronauts to know which switch to turn and in what order to bring the shuttle home.

Another question he’d like to address involves a greater understanding of the complexity of a living system. So far, he’s looked at properties of these kinases under controlled conditions. When he moves into a more complex environment, the inhibitors will likely interact and yield unexpected binding or connections.

Frohman appreciated Seeliger’s overall approach to his work and his contribution to the field. He cited the popularity of a review article Seeliger wrote that documents how drug molecules find their target binding site. Frohman said this work, which was published in the Journal of the American Chemical Society, was cited over 400 times in other articles.

Seeliger has been “very dedicated to moving this field forward. We were very excited about the topic and have been very pleased with the work he’s done on it since arriving at SBU,” Frohman said.

A resident of Stony Brook, Seeliger lives with his wife Jessica Seeliger, an assistant professor in the Department of Pharmacological Sciences who works on developing drugs for tuberculosis. The couple has two young children.

“We are all very happy they are both here as independent scientists,” Frohman added.

Indeed, Hannun called Jessica Seeliger an “outstanding and highly talented scientist,” as well.

Seeliger grew up in Hanover, Germany. He became interested in science in high school when he watched “The Double Helix,” which showed the development of the structural model of DNA.

His lab currently has two postdoctoral researchers and two doctoral candidates. Ultimately, Seeliger hopes his research helps establish an understanding of the way various kinases are functionally similar in how they interact with drugs.

“We wish we would be able to design more specific inhibitors without having to test dozens and dozens of compounds by trial and error,” he explained. He hopes to continue to build on his work with kinases, including exploring what happens when mutations in these switches cause disease.