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Aug 1, 2010 (Vol. 30, No. 14)

Metabolite Profiling Powered by Mass Spec

MS-Based Methods Are Gold Standard for Identification of Metabolic Byproducts

  • Improving Pharmacokinetic Liability

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    Metabolite identification is one of the methodologies employed by Cubist Pharmaceuticals’ scientists to improve the pharmacokinetics of its novel compounds in development for use in the acute-care environment.

    Scott Coleman, Ph.D., director of discovery toxicology and pharmacokinetics at Cubist Pharmaceuticals, described his company’s research into microsomal stability and metabolite identification and how information from this work can help project teams move novel compounds forward by eliminating potential metabolic liability early in the development process.

    “We identified a key moiety on a scaffold that was responsible for the metabolism that occurs in vitro, and we could correlate that to an in vivo finding. Modifications around that moiety can help us improve in vivo pharmacokinetics.”

    Using liver microsomal preparations and an Orbitrap LC-MS instrument from Thermo Fisher Scientific, Dr. Coleman and his team were able to identify, with a high degree of confidence, the structure of the metabolite of interest and then propose alternate scaffolds and medicinal chemistry opportunities to improve pharmacokinetic liability.

  • Nontargeted Analysis

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    Waters has collaborated with a professor at Roger Williams University to develop proper feed for clownfish by profiling metabolites in their eggs. The partners observed changes in metabolite levels over the eggs’ nine-day incubation period and identified major biomarkers that could be investigated.

    Waters recently collaborated with Stephen O’Shea, Ph.D., associate professor of chemistry at Roger Williams University, on a metabolic profiling project. The collaborators developed two different workflows—a targeted and a nontargeted approach.“We developed these workflows for the purpose of resolving metabolic-profiling challenges,” explained Kate Yu, principal scientist at Waters, who is a member of the metabolic profiling business development group that worked on the project.

    The entire workflow is called UPLC-QTof-MSE coupled with multivariate statistical analysis for sample profiling. In this workflow, Waters’ Acquity UltraPerformance LC (UPLC) system and Waters’ Synapt mass spectrometer were employed for the metabolic profiling.

    “One of the key components was  MarkerLnx software, which allows us to identify the key biomarkers from complex samples,” Yu said. When these samples are separated on UPLC you can see that they are complex, but when you dig down deeper into the chromatogram by using multivariate statistical analysis, for example, you will be able to clearly identify more key biomarkers by using their exact mass.”

    Dr. O’Shea is working on developing an aquaculture system for breeding clownfish for use as domestic pets and as model species for other marine tropical fish. “Our targeted analysis focused on developing proper feeds, which have a specific fatty acid component, for these fish,” said Dr. O’Shea, who added that, traditionally, fatty acid analysis had been performed using an HPLC/quadrupole MS before this collaboration work.

    With UPLC-QTof-MSE, the analysis is performed faster and with less starting material, which is why the collaboration was undertaken. Using nontargeted analysis on whole fish eggs, the team was able to establish biomarkers to determine the identity of required dietary components, which will enable them to develop better diets for breeding.

    “The fish eggs have a nine-day incubation and we were able to do metabolic profiling with Waters technology over that nine-day period, i.e., to see changes in metabolite levels over that period and also pick up major biomarkers that could be investigated.”



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