Computer simulation model helps understand why resistance to chemotherapy occurs

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Understanding why and how resistance to chemotherapy occurs is a major step towards optimizing cancer treatments. A team of scientists, including Markus Seeliger, PhD, of Stony Brook University’s Renaissance School of Medicine, believe they have discovered a new process by which drug resistance occurs. They use a computer simulation model that helps them understand exactly how molecules interact with the cancer drug Imatinib (known as Gleevec) in the process of chemotherapy resistance. Imatinib treats chronic myeloid leukemia (CML) very effectively, but many late-stage patients have drug resistance, making the drug poorly effective at this stage.

The research is highlighted in an article published in Angewandte Chemiea leading chemistry journal, and builds on previous research detailed in 2021 in PNAS.

Imatinib inhibits BCR-Abl protein kinase, an overactive cell signaling machinery in CML. In the PNAS study, the researchers showed that variations in the building plan of the kinase can make it more difficult for imatinib to bind to the kinase and also accelerate the release of the drug from the kinase. In the Angewandte Chemie article, the research team took computational methodology – developed by co-author Pratyush Tiwary from the University of Maryland – which allowed them to study the very slow release of Imatinib from the kinase.

This method in itself is a major technical achievement that extends the computational capabilities for drug resistance research and most importantly allowed us to predict how quickly healthy and mutant proteins would release this drug. For the first time, we have been able to see the release of a drug from a protein in such detail and precision. Additionally, we were able to show that the mutation fundamentally changes the drug exit pathway of the protein.


This is important because the rate of drug release can be just as important to a drug’s therapeutic effect as the strength with which a drug binds to protein.”


Markus Seeliger, PhD, Associate Professor, Department of Pharmacological Sciences, Stony Brook University Renaissance School of Medicine

Seeliger further explains that the method could provide a basis for understanding the molecular mechanisms behind chemotherapy resistance.

More broadly, the implications of what they found are that if scientists can understand how drugs are released from their proteins, they might be able to design drugs with slower release and greater therapeutic impact. Additionally, if rapid drug release can lead to drug resistance, and clinicians can show that this is happening, they may be able to reactivate the drug’s effectiveness by instructing the patient to take the drug more frequently.

The basic work for mutation testing via the computational method has been described in the PNAS paper. Seeliger and colleagues tested how imatinib binds to mutations in patients with imatinib-resistant CML. They found that the majority of mutations readily bind imatinib, raising the question of how do these mutations cause resistance in patients? The researchers then identified several mutants that readily bind imatinib but release the drug much faster.

After identifying these mutants with faster drug release, the team used nuclear magnetic resonance (NMR) and molecular dynamics to link the protein to drug dissociation, highlighting the importance of drug dissociation kinetics. for drug efficacy. This allowed them to identify a new mechanism of resistance to imatinib.

The work that led to the article published in PNAS involved the collaborative efforts of Seeliger and colleagues at Stony Brook, and researchers at Memorial Sloan Kettering Cancer Center and Goethe University in Frankfurt, Germany.

The research that led to the most recent paper was led by Tiwary and his colleagues at the University of Maryland, in collaboration with Seeliger and scientists from the Broad Institute at MIT and Harvard University.

Source:

Journal reference:

Shekhar, M. et al. (2022 Protein flexibility and differentiation of dissociation pathways may explain the occurrence of resistance mutations in kinases. Angewandte Chemie. doi.org/10.1002/anie.202200983.

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