Identification of metabolites of a substance P (neurokinin 1 receptor) antagonist in rat hepatocytes and rat plasma

The Importance of Tracking "Missing" Metabolites: How and Why?

Technologies currently employed to find and identify drug metabolites in complex biological matrices generally yield results that offer a comprehensive picture of the drug metabolite profile. However, drug metabolites can be missed or are captured only late in the drug development process. This could be due to a variety of factors, such as metabolism that results in partial loss of the molecule, covalent bonding to macromolecules, the drug being metabolized in specific human tissues, or poor ionization in a mass spectrometer. These scenarios often draw a great deal of attention from chemistry, safety assessment, and pharmacology. This review will summarize scenarios of missing metabolites, why they are missing, and associated uncovering strategies from deeper investigations. Uncovering previously missed metabolites can have ramifications in drug development with toxicological and pharmacological consequences, and knowledge of these can help in the design of new drugs.

Copper-Catalyzed Chan-Lam Cyclopropylation of Phenols and Azaheterocycles

Small molecules containing cyclopropane-heteroatom linkages are commonly needed in medicinal chemistry campaigns yet are problematic to prepare using existing methods. To address this issue, a scalable Chan-Lam cyclopropylation reaction using potassium cyclopropyl trifluoroborate has been developed. With phenol nucleophiles, the reaction effects O-cyclopropylation, whereas with 2-pyridones, 2-hydroxybenzimidazoles, and 2-aminopyridines the reaction brings about N-cyclopropylation. The transformation is catalyzed by Cu(OAc)₂ and 1,10-phenanthroline and employs 1 atm of O₂ as the terminal oxidant. This method is operationally convenient to perform and provides a simple, strategic disconnection toward the synthesis of cyclopropyl aryl ethers and cyclopropyl amine derivatives bearing an array of functional groups.

In vivo metabolite detection and identification in drug discovery via LC-MS/MS with data-dependent scanning and postacquisition data mining

An important aspect in drug discovery is the early structural identification of the metabolites of potential new drugs. This gives information on the metabolically labile points in the molecules under investigation, suggesting structural modifications to improve their metabolic stability, and allowing an early safety assessment via the identification of metabolic activation products. From an analytical point of view, metabolite identification still remains a challenging task, especially for in vivo samples, in which they occur at trace levels together with high amounts of endogenous compounds. Here we describe a method, based on LC-ion trap tandem MS, for the rapid in vivo metabolite identification. It is based on the automatic, data-dependent acquisition of multiple product ion MS/MS scans, followed by a postacquisition search, within the entire MS/MS data set obtained, for specific neutral losses or marker ions in the tandem mass spectra of parent molecule and putative metabolites. One advantage of the method is speed, since it requires minimum sample preparation and all the necessary data can be obtained in one chromatographic run. In addition, it is highly sensitive and selective, allowing detection of trace metabolites even in the presence of a complex matrix. As an example of application, we present the studies of the in vivo metabolism of the compound MEN 15916 (1). The method allowed identification of monohydroxy ([M + H](+) = m/z 655), dihydroxy ([M + H](+) = m/z 671), and trihydroxy ([M + H](+) = m/z 687) metabolites, as well as some unexpected biotransformation products such as a carboxylic acid ([M + H](+) = m/z 669), a N-dealkylated metabolite ([M + H](+) = m/z 541), and its hydroxy-analog ([M + H](+) = m/z 557).

Accelerated throughput metabolic route screening in early drug discovery using high-resolution liquid chromatography/quadrupole time-of-flight mass spectrometry and automated data analysis

The resource investment required to characterise the metabolic fate of a compound is relatively large, meaning that within a drug discovery environment relatively few compounds are characterised in depth. Rate-limiting steps include the setting up of a complex array of mass spectrometry experiments and the subsequent analysis of the large data sets produced. We describe here a strategy for the evaluation of metabolic routes using full-scan high-resolution liquid chromatography/quadrupole time-of-flight mass spectrometry (LC/QToFMS) with automated data analysis using Metabolynx, a commercially available software package. Data from several structurally diverse compounds taken from the literature illustrate that, with careful setting of key parameters, this approach is able to indicate the presence of a wide range of metabolites with only a limited requirement for manual intervention.