The annual meeting of the American Association of Mass Spectrometry held in June featured the debut of many improved and modified mass spec instruments and ancillary devices. The focus, however, was on applications of the technology for molecular identification and characterization. Metabolic profiling, evaluation of biomarkers, drug metabolite identification, and many related topics were addressed.
Of late, there has been much concern over the slow pace of drug discovery. Pharma companies have experienced difficulty bringing their discoveries through clinical trials. The efforts of small biotech companies also haven’t been much more successful. Attempts to reduce the attrition rates and expedite drug development have focused on a number of rational approaches, meaning that investigators are striving to understand the fundamental biology behind a particular biological system.
The assumption driving this approach is that this knowledge will give drug discoverers a solid understanding of the disease process, thus avoiding the waste of resources on fruitless pursuits.
While logical, this hypothesis has some serious drawbacks. In many cases, biotech companies pursue technologies that are so poorly understood that years of back breaking basic science is required before a sufficiently detailed understanding points a direction toward a viable pharmaceutical.
Among the principle reasons for failure of potential drugs are serious side effects and adverse reactions. To identify these factors early in the drug discovery process and avoid wasted time and resources, the elucidation of the transformation of drugs into their metabolic products plays a pivotal role.
Pursuing Lifestyle Diseases
Klaus Weinberger, Ph.D., CSO of Biocrates discussed life style diseases, representing the collection of self-inflicted human ills that run rampant through society. These include obesity, disorders in lipid metabolism, and type 2 diabetes, all conditions in which many organ systems are affected.
“Since the mid 1990s, mass spec has been standardized for newborn screening and today includes around 20 major hereditary conditions in the U.S. and EU,” said Dr. Weinberger. “This comprises two main groups: amino acid metabolism disorders and mitochondrial disorders of lipid oxidation. We have improved the technology and expanded it to a variety of other classes, including sugar metabolism, phospholipids, prostaglandins, prostacyclins, thromboxanes, leukotrienes, and inflammation mediators.”
Evaluation of inborn errors of metabolism in newborns has a history that goes back to the 1930s, with the discovery of phenylketonuria, a genetic disorder due to an inability of the child to convert the amino acid phenylalanine to tyrosine. It was recognized that early implementation of a low phenylalanine diet would prevent the mental retardation associated with the accumulation of dietary phenylalanine in the serum.
Modern newborn screening, however, measures phenylalanine to tyrosine ratios in dried blood spots, rather than the presence of the enzyme. In combination with the simultaneous and extremely accurate measurement of a number of other amino acids, the diagnostic specificity for phenylketonuria and other inborn disorders was dramatically increased.
While each metabolic error is a rare genetic condition, the sum total of all the disorders that are included in current mass spec-based screening of newborns is a substantial number.
Biocrates’ approach to biomarker discover, Dr. Weinberger explained, is investigating metabolic parameters first in homogenates of solid tissues (muscle, adipose tissue, tumors, and other sources) and then determining whether these aberrations can be detected in plasma or serum.
“Type 2 diabetes isn’t just a problem of high glucose levels,” he added. “Diseases of industrialized countries are a rapidly expanding class diagnosed by fuzzy criteria such as the hip-to-waist-ratio in obesity and high cholesterol in dyslipidemia. Metabolomics combined with systems biology offers an opportunity to establish the conditions on a sound scientific basis.
“Another strength of metabolomics is in the fact that it can monitor many parameters simultaneously, looking for deviations that provide clues to the mechanism of pathology of the disorder,” concluded Dr. Weinberger.
Searching for Anticancer Therapies
When drugs are metabolized, their intermediate metabolites are often extremely toxic, obviating their value as therapeutics. This outcome is due to the body’s effort to produce polar intermediates that are soluble and more easily excreted. For this reason, determination of the optimum choice of a drug molecule requires an intimate knowledge of its metabolic processing.
Inhibitors of the ERB-B2 receptor tyrosine kinase have been actively investigated for their potential as anticancer drugs. Chandra Prakash, Ph.D., and coworkers at Pfizer Global Research Development have characterized metabolites of several potential inhibitors using mass spectrometry and other technologies. One of these, 2-methoxy-N-(3-{4-[3-methyl-4-(6-methyl-pyridin-3- yloxy)-phenylamino]-quinazolin-6-yl}-ally)-acetamide has been moved to Phase I clinical trials for the treatment of cancer based on these characterizations.
Determination of the optimum choice of a drug molecule requires an intimate knowledge of its metabolic processing. In general, drug metabolites are less toxic than their corresponding parent compound. This outcome is due to the body’s effort to produce polar intermediates that are soluble and more easily excreted.
These more hydrophilic molecules are greatly enhanced in terms of their elimination from the body. However, unwanted results of these metabolic transformations may be too rapid drug clearance, drug-drug interactions via inhibition or induction of drug metabolizing enzymes, and/or formation of toxic metabolites. Therefore, determination of metabolic fate of the new chemical entities in animals and humans metabolites are critical to pharmaceutical research and compound progression.
Dr. Prakash and his colleagues at Pfizer have investigated the in vitro metabolism of two similar compounds in rat, monkey, dog, and human-liver microsomes by measuring the radioactivity in the individual peaks that were separated on HPLC and identified by LC/MS/MS operating with electrospray positive ion mode.
A total of 11 metabolites were identified. Full-scan mass spectrometry data of two major metabolites indicated the addition of an oxygen atom to the molecule. The N-oxide metabolite was found to undergo further metabolism to form several secondary metabolites.
Dr. Prakash found that frequently mass spec alone is insufficient to identify the exact position of the oxidation reaction, differentiate isomers, or provide the precise structure of metabolites. For this reason, the Pfizer researchers use multiple analytical and wet chemistry techniques such as NMR, chemical derivatization, and hydrogen deuterium exchange.
For example, when investigating the in vitro metabolism of two similar compounds in rats, monkeys, dogs, and human-liver microsomes, Dr. Prakash and his colleagues measured the radioactivity in the individual peaks that were separated on HPLC and identified by LC/MS/MS operating with electrospray positive ion mode.
A total of 11 metabolites were identified. Full-scan mass spec data of two major metabolites indicated the addition of an oxygen atom to the molecule. The N-oxide metabolite was found to undergo further metabolism to form several secondary metabolites.
Statistical Analysis of MS Data
The vast amount of data generated by metabolomics analyses calls on the use of software packages that incorporate statistical tools to search for meaningful relationships, a requirement that goes to the heart of the systems biology approach. Agilent Technologies introduced an informatics software solution, GeneSpring MS, for the discovery of protein and metabolite biomarkers using mass spectrometry data.
The system uses statistical analysis and visualization tools to profile proteins or small molecules, including one-way and two-way analysis of variance, principle component analysis, and class prediction algorithms. GeneSpring MS can detect changes in the profile of proteins, peptides, and metabolites across many samples. The package also enables researchers to identify biological pathways to which potential biomarkers belong and infer specific molecular interactions relevant to the discovery.
“We rely solely on mass spec because of its high throughput and sensitivity,” stated Gerard Hopfgartner, Ph.D., professor of pharmaceutical analytical chemistry at the University of Geneva. “Other techniques such as protein NMR are more powerful but they require larger samples and are more cumbersome. So for this reason, we are building software that can define metabolites.”
Dr. Hopfgartner and his colleagues at the Life Sciences Mass Spectrometry Facility at the University of Geneva and Shimadzu ISS reported on their approach to identify metabolite through a statistical analysis of mass spectrometry data. Applying a partial least squares approach to data mining for metabolite signals together with high mass accuracy MSn analysis, they seek to meet the needs of the pharmaceutical industry and regulatory authorities for more and better detailed metabolite information.
“We strive to build a predictive metabolomics database and for this reason, we concentrate on statistical tools,” he continued. Such an approach allows data processing in a reliable manner, so as to efficiently identify metabolites without the use of wet chemistry, as is presently done.
Dr. Hopfgartner and his team studied the potential of off-line analysis and newly designed software for the enhancement of metabolite identification with a nonradiolabeled parent drug. As a model system they investigated two compounds with well-characterized metabolism, tolcapone and talinolol. The parent drugs were incubated with either human or rat microsomes and samples were measured by electrospray ion-trap time-of-flight mass spectrometry and data mined using a partial least squares algorithm.
They report that oxidative metabolites of talinolol can be observed in the positive mode, while for tolcapone a larger variety of metabolites can be observed in the negative or positive mode. Using fragment ions from the parent molecule acquired with high mass accuracy MSn, a partial least squares statistical approach was applied to in vitro metabolite samples to identify novel metabolite signals. This approach was investigated as an alternative to existing methods of identifying metabolites in nonradio-labeled pharmacodynamic studies.
“In the past, drug metabolite identification focused on oxidation as the major processing mechanism through the classical P450 route,” said Dr. Hopfgartner, “But, here we seek a much more unbiased approach without preconceptions concerning critical intermediates.”
Future of Metabolite Identification
Although mass spec is proving to be a powerful tool for metabolomics studies, often, identification of structures requires supplementation with a bevy of approaches, including wet chemistry. As the sensitivity of the technology constantly increases, there may be a point where it becomes too sensitive, detecting insignificant quantities.
Dr. Hopfgartner believes metabolomics to be a more fruitful approach to drug discovery and biomarker validation than proteomics. “With proteomics, you are working on a peptide level, and sample analysis can run from 20 to 40 hours. Metabolomic studies have the potential to be much more rapid. I believe that the basic science of metabolomics should receive a lot more academic funding, since we’re looking at a global understanding of metabolite processing, rather than development of a specific drug. You simply can’t resolve such complex basic science in the 12 months that many drug companies use as a time frame.”
Another major challenge for drug development is understanding the basis for the genetic variability in drug responses in human populations. In cases where the percent of responders to a drug is small, it becomes impossible to achieve regulatory approval. If metabolomic investigations can be used to partition that population, drugs targeted at a subset of the population could be identified and investigated in clinical trials.
“We know that animal studies are flawed, since there are so many differences in metabolism between rats and humans,” said Dr. Hopfgartner. “Human studies are essential, and we are working through our predictive modeling to lower reliance on animal trials and decrease the risk to humans. As we develop a better knowledge of the kinetics of drug metabolism, we are moving toward fewer and safer in vivo investigations.”
Human and animals trials can never be completely abandoned, but metabolite identification and characterization will go a long way toward obviating reliance on these approaches.
K. John Morrow, Jr., Ph.D., is president of Newport Biotech and contributing editor for GEN. E-mail: [email protected].
