Identification and characterization of the metabolites of sinomenine using liquid chromatography combined with benchtop Orbitrap mass spectrometry and nuclear magnetic resonance spectroscopy

RATIONALE

Sinomenine, a major bioactive compound isolated from Sinomenium acutum, has been used for the treatment of rheumatoid arthritis and other cardio-cerebrovacular diseases. However, the metabolism of this drug has not been fully investigated. The current work was carried out to investigate the in vitro metabolism of sinomenine in liver microsomes.

METHODS

The metabolites were generated by incubating sinomenine (3 μM) with the liver microsomes in the presence of NADPH at 37°C. The structure of the metabolites was characterized using liquid chromatography coupled to high-resolution mass spectrometry (HRMS). Two major metabolites synthesized and their structures were further confirmed using nuclear magnetic resonance spectroscopy.

RESULTS

Under the current conditions, 12 metabolites were found and structurally identified using high resolution MS and MS2 spectra. Among these metabolites, M1, M2, M3, M4, M5, M6, M7, M9, M11, and M12 were first reported. The metabolites M8 and M10 were synthesized and unambiguously identified as N-desmethyl-sinomenine and sinomenine N-oxide, respectively. The phenotyping study revealed that the formation of M8 was catalyzed by CYP2C8, 2C19, 2D6, and 3A4, whereas the formation of M3, M6, and M10 were exclusively catalyzed by CYP3A4. The metabolic pathways of sinomenine include N-demethylation, O-demethylation, dehydrogenation, oxygenation, and N-oxygenation.

CONCLUSIONS

N-Demethylation and N-oxygenation were the primary metabolic pathways of sinomenine. This study provides new insight into the in vitro metabolism of sinomenine, which would help prospects of sinomenine disposition and safety assessments.

Determination of the compound class and functional groups in protonated analytes via diagnostic gas-phase ion-molecule reactions

Diagnostic gas-phase ion-molecule reactions serve as a powerful alternative to collision-activated dissociation for the structural elucidation of analytes when using tandem mass spectrometry. The use of such ion-molecule reactions has been demonstrated to provide a robust tool for the identification of specific functional groups in unknown ionized analytes, differentiation of isomeric ions, and classification of unknown ions into different compound classes. During the past several years, considerable efforts have been dedicated to exploring various reagents and reagent inlet systems for functional-group selective ion-molecule reactions with protonated analytes. This review provides a comprehensive coverage of literature since 2006 on general and predictable functional-group selective ion-molecule reactions of protonated analytes, including simple monofunctional and complex polyfunctional analytes, whose mechanisms have been explored computationally. Detection limits for experiments involving high-performance liquid chromatography coupled with tandem mass spectrometry based on ion-molecule reactions and the application of machine learning to predict diagnostic ion-molecule reactions are also discussed.

Effects of Analyte Concentration on the Protonation Sites of 4-Aminobenzoic Acid upon Atmospheric Pressure Chemical Ionization As Revealed by Gas-Phase Ion-Molecule Reactions

The most basic site of 4-aminobenzoic acid in aqueous solution is the amino nitrogen, while the carbonyl oxygen is calculated to be the most basic site in the gas phase. However, the preferred protonation site of 4-aminobenzoic acid upon electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) depends upon the ionization solvent and ion source parameters. The influence of the concentration of the analyte on the manifested protonation sites upon APCI has not been investigated and is reported here. Gas-phase ion-molecule reactions of trimethoxymethylsilane were used to identify the protonation sites of 4-aminobenzoic acid ionized using APCI with methanol or acetonitrile-water as the solvent. The nitrogen-protomer was found to be about twice as abundant as the oxygen-protomer at low analyte concentrations (10^-9-10^-6 M) in methanol solvent. This finding was rationalized on the basis of a previous finding that when the O-protomer is surrounded by more than eight methanol molecules in the gas phase it starts behaving as if it were in an aqueous solution and converts to the N-protomer. At greater analyte concentrations (≥10^-4 M), the amino group was predominantly protonated, which was rationalized based on the formation of a particularly stable proton-bound dimer of 4-aminobenzoic acid that preferentially dissociates to form the N-protomer. The above findings suggest that solution processes are much more important in APCI than commonly assumed, in agreement with recent literature. Indeed, when 1:1 (v/v) acetonitrile-water was used as the solvent system for 4-aminobenzoic acid, the N-protomer was predominantly generated at all analyte concentrations.

Graph-based machine learning interprets and predicts diagnostic isomer-selective ion-molecule reactions in tandem mass spectrometry

Diagnostic ion-molecule reactions employed in tandem mass spectrometry experiments can frequently be used to differentiate between isomeric compounds unlike the popular collision-activated dissociation methodology. Selected neutral reagents, such as 2-methoxypropene (MOP), are introduced into an ion trap mass spectrometer where they react with protonated analytes to yield product ions that are diagnostic for the functional groups present in the analytes. However, the understanding and interpretation of the mass spectra obtained can be challenging and time-consuming. Here, we introduce the first bootstrapped decision tree model trained on 36 known ion-molecule reactions with MOP. It uses the graph-based connectivity of analytes' functional groups as input to predict whether the protonated analyte will undergo a diagnostic reaction with MOP. A Cohen kappa statistic of 0.70 was achieved with a blind test set, suggesting substantial inter-model reliability on limited training data. Prospective diagnostic product predictions were experimentally tested for 13 previously unpublished analytes. We introduce chemical reactivity flowcharts to facilitate chemical interpretation of the decisions made by the machine learning method that will be useful to understand and interpret the mass spectra for chemical reactivity.

2-aminothiazoles in drug discovery: Privileged structures or toxicophores?

The 2-aminothiazole functionality has long been established as a privileged structural feature and therefore frequently exploited in the process of drug discovery and development. It has been introduced into numerous compounds due to its capacity for targeting a wide range of therapeutic target proteins. On the other hand, the aminothiazole group has also been classified as a toxicophore susceptible to metabolic activation and the ensuing reactive metabolite formation, hence caution is warranted when used in drug design. This review is divided into three parts entailing: (i) the general characteristics of the aminothiazole group, (ii) the advantages of the aminothiazole group in medicinal chemistry, and (iii) the impact of the integrated aminothiazole group on compound safety profile.

Pharmacokinetic and Metabolism Studies of Monomethyl Auristatin F via Liquid Chromatography-Quadrupole-Time-of-Flight Mass Spectrometry

A simple liquid chromatography–quadrupole-time-of-flight–mass spectrometric assay (LC-TOF-MS/MS) has been developed for the evaluation of metabolism and pharmacokinetic (PK) characteristics of monomethyl auristatin F (MMAF) in rat, which is being used as a payload for antibody-drug conjugates. LC-TOF-MS/MS method was qualified for the quantification of MMAF in rat plasma. The calibration curves were acceptable over the concentration range from 3.02 to 2200 ng/mL using quadratic regression. MMAF was stable in various conditions. There were no significant matrix effects between rat and other preclinical species. The PK studies showed that the bioavailability of MMAF was 0% with high clearance. Additionally, the metabolite profiling studies, in vitro/in vivo, were performed. Seven metabolites for MMAF were tentatively identified in liver microsome. The major metabolic pathway was demethylation, which was one of the metabolic pathways predicted by MedChem Designer. Therefore, these results will be helpful to understand the PK, catabolism, and metabolism behavior of MMAF comprehensively when developing antibody-drug conjugates (ADCs) in the future.

Identification of Protonated Sulfone and Aromatic Carboxylic Acid Functionalities in Organic Molecules by Using Ion-Molecule Reactions Followed by Collisionally Activated Dissociation in a Linear Quadrupole Ion Trap Mass Spectrometer

Gas-phase reactivity of protonated model compounds with different functional groups toward trimethoxymethylsilane (TMMS) was studied to explore the utility of this reagent in mass spectrometric identification of specific functionalities for potentially rapid characterization of drug metabolites. Only protonated analytes with a carboxylic acid, a sulfone, or a sulfonamide functionality formed diagnostic adducts that had lost a methanol molecule upon reactions with TMMS. Collisionally activated dissociation (CAD) of these methanol-eliminated adduct ions (MS³ experiments) produced characteristic fragment ions of m/z 75, 105, and 123 for sulfones, while an additional methanol elimination was observed for carboxylic acids and sulfonamides. CAD of latter products (MS⁴ experiments) resulted in elimination of diagnostic neutral molecules CO₂ (44 Da) and C₂H₆O₂Si (90 Da) for aromatic carboxylic acids. Both aliphatic carboxylic acids and sulfonamides yield several fragment ions in these MS⁴ experiments that are different from those observed for sulfones or aromatic carboxylic acids. Potential energy surfaces were calculated (at the M06-2X/6-311++G(d,p) level of theory) to explore the mechanisms of various reactions. In summary, sulfones and aromatic carboxylic acids can be differentiated from each other and also from sulfonamides and aliphatic carboxylic acids based on reactions with TMMS and one or two CAD experiments. Aliphatic carboxylic acids and sulfonamides could not be differentiated from each other.