Kinetic analysis during the metabolite identification process

Fitting Kinetic equations derived from metabolic pathways to LC/MS-MS integrated peak areas

64th ASMS Conference on Mass Spectrometry and Allied Topics, San Antonio, TX (United States of America) 05 June 2016 

Abstract

Introduction WebMetabase allows drawing metabolic pathways to describe how a parent compound is transformed into metabolites in in vitro or in vivo experiments. Assuming that reactions occur in a single compartment (like is the case for an in vitro incubation) and also that each arrow corresponds to a single-step irreversible Chemical reaction (even though it’s not true, i.e., they are often catalyzed by enzymes) we can build a system of differential equations whose equations, when solved, can be fitted to the MS area integrated signals. This theoretical curve and the integrated signal MS area often fit well, and when they do not, information useful to improve the metabolic pathway can be extracted from it. Methods LC/MS of several compounds was processed by MassMetaSite and loaded into WebMetabase. A metabolic pathway was built for each parent compound, and the system of differential equations, assuming single step irreversible chemical reactions, was built, solved, and fitted to the experimental integrated MS area using Maxima. Visual inspection of the plot of the theoretical MS area curve and experimental MS area points vs. time sometimes allows, when the fitting quality is bad, to derive information that can be used to change the position of the compound in the metabolic pathway and improve the fitting quality Preliminary Data Chemical kinetics theory is a good approximation of enzyme kinetics in in vitro assays because typically cytochromes do not have a high affinity for the compounds they metabolize, and also because the concentration of metabolites is much lower than the enzyme affinity, thus simplifying the Michaelis-Menten enzyme kinetics equation to a first order chemical kinetics equation. We used chemical kinetics analysis of metabolic pathway, as implemented in WebMetabase, as guidance to build metabolic pathways for several compounds. In several cases, the observed MS area vs. time of compounds included in the metabolic pathways fitted the theoretical equation that would correspond to them if the metabolic pathway scheme would consist of single-step irreversible chemical equations, thus confirming that the assumptions made were correct in these cases. There were some cases where experimental MS area vs. time points does not fit the theoretical chemical kinetics curve and could not be improved by rearranging them in the metabolic pathway. In these cases where fitting was bad or failed, probably one of the previous assumptions is false, for instance they are not formed or metabolized in single-step reactions, or chemical kinetics theory is not a good approximation of the real enzyme kinetics. Novel Aspect To the best of our knowledge, chemical kinetics theory has not been previously used to verify a metabolic pathway scheme. 

Enhanced metabolite identification with MS(E) and a semi-automated software for structural elucidation

Enhanced metabolite identification with MS(E) and a semi-automated software for structural elucidation

November 2010.

Bonn B; Leandersson C; Fontaine F; Zamora I

Abstract

The identification of metabolites is almost exclusively done with liquid chromatography/tandem mass spectrometry (LC/MSMS) and despite the enormous progress in the development of these techniques and software for handling of data this is a time-consuming task. In this study the use of quadrupole time-of-flight (QTOF)-generated MS(E) and MS/MS data were compared with respect to rationalization of metabolites. In addition Mass-MetaSite, a semi-automated software for metabolite identification, was evaluated. The program combines the information from MS raw data, in the form of collision-induced dissociation spectra, with a prediction of the site of metabolism in order to assign the structure of a metabolite. The aim of the software is to mimic the rationalization of fragment ions performed by a biotransformation scientist in the process of structural elucidation. For this evaluation, metabolite identification in human liver microsomes was accomplished for 19 commercially available compounds and 15 in-house compounds. The results were very encouraging and for 96% of the metabolites the same structures were assigned using MS(E) compared with MSMS acquired data. The possibility of using MS(E) could considerably reduce the analysis time. Moreover, Mass-MetaSite performed well and the correct assigned structure, compared to manual inspection of the data, was picked in the first rank in ∼80% of the cases. In conclusion MS(E) could be successfully used for metabolite identification in order to reduce time of analysis and Mass-MetaSite could alleviate the work of a biotransformation scientist and decrease the workload by assigning the structure for a majority of the metabolites.

Update on hydrocodone metabolites in rats and dogs aided with a semi-automatic software for metabolite identification MassMetaSite

Update on hydrocodone metabolites in rats and dogs aided with a semi-automatic software for metabolite identification MassMetaSite

May 2013.

Li AC; Chovan JP; Yu E; Zamora I

Abstract

There has been a lack of in vivo metabolite profiling update of hydrocodone since the original report on species differences was published in 1978. As such, the mechanism for its analgesic activity in different species has been ambiguous. To address safety concern from regulatory agencies, hydrocodone metabolite profiles in rats and dogs are updated herein aided by a newly developed software, Mass-MetaSite. 2. Samples collected from rats and dogs dosed orally with hydrocodone were analyzed with reversed phase liquid chromatography coupled with LTQ-Orbitrap. The exact mass measurement data collected with data-dependent acquisition methodology were analyzed both traditionally, using Xcalibur Qual Browser and MetWorks, and by Mass-MetaSite. 3. Profiling of hydrocodone metabolites in rat and dog plasma reflected previously reported species differences in circulating metabolites. While hydrocodone mainly underwent O-demethylation and ketone reduction in rats forming hydromorphone and reduced hydromorphone, which were then subsequently cleared via glucuronide conjugation, hydrocodone in dogs was cleared predominantly by N-demethylation and N-oxidation. 4. Given the success ratio of metabolite detection offered by Mass-MetaSite, the software will be able to aid chemists in early identification of drug metabolites from complex biomatrices.

Software automation tools for increased throughput metabolic soft-spot identification in early drug discovery

Software automation tools for increased throughput metabolic soft-spot identification in early drug discovery

May 2013.

Zelesky V; Schneider R; Janiszewski J; Zamora I; Ferguson J; Troutman M

Abstract

Background: The ability to supplement high-throughput metabolic clearance data with structural information defining the site of metabolism should allow design teams to streamline their synthetic decisions. However, broad application of metabolite identification in early drug discovery has been limited, largely due to the time required for data review and structural assignment. The advent of mass defect filtering and its application toward metabolite scouting paved the way for the development of software automation tools capable of rapidly identifying drug-related material in complex biological matrices. Two semi-automated commercial software applications, MetabolitePilot™ and Mass-MetaSite™, were evaluated to assess the relative speed and accuracy of structural assignments using data generated on a high-resolution MS platform.

Results/conclusion: Review of these applications has demonstrated their utility in providing accurate results in a time-efficient manner, leading to acceleration of metabolite identification initiatives while highlighting the continued need for biotransformation expertise in the interpretation of more complex metabolic reactions.

 

High-throughput, computer assisted, specific MetID. A revolution for drug discovery

High-throughput, computer assisted, specific MetID. A revolution for drug discovery

Spring 2013.

Zamora I; Fontaine F; Serra B; Plasencia G

Abstract

One of the key factors in drug discovery is related to the metabolic properties of the lead compound, which may influence the bioavailability of the drug, its therapeutic window, and unwanted side-effects of its metabolites. Therefore, it is of critical importance to enable the fast translation of the experimentally determined metabolic information into design knowledge. The elucidation of the metabolite structure is the most structurally rich and informative end-point in the available range of metabolic assays. A methodology is presented to partially automate the analysis of this experimental information, making the process more efficient. The computer assisted method helps in the chromatographic peak selection and the metabolite structure assignment, enabling automatic data comparison for qualitative applications (kinetic analysis, cross species comparison).