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Metabolite Screening (metabolite + screening)

Distribution by Scientific Domains

Chemistry	100%

Selected Abstracts

Comparison of DNA-Reactive Metabolites from Nitrosamine and Styrene Using Voltammetric DNA/Microsomes Sensors

ELECTROANALYSIS, Issue 9 2009
Sadagopan Krishnan
Abstract Voltammetric sensors made with films of polyions, double-stranded DNA and liver microsomes adsorbed layer-by-layer onto pyrolytic graphite electrodes were evaluated for reactive metabolite screening. This approach features simple, inexpensive screening without enzyme purification for applications in drug or environmental chemical development. Cytochrome P450 enzymes (CYPs) in the liver microsomes were activated by an NADPH regenerating system or by electrolysis to metabolize model carcinogenic compounds nitrosamine and styrene. Reactive metabolites formed in the films were trapped as adducts with nucleobases on DNA. The DNA damage was detected by square-wave voltammetry (SWV) using Ru(bpy) as a DNA-oxidation catalyst. These sensors showed a larger rate of increase in signal vs. reaction time for a highly toxic nitrosamine than for the moderately toxic styrene due to more rapid reactive metabolite-DNA adduct formation. Results were consistent with reported in vivo TD50 data for the formation of liver tumors in rats. Analogous polyion/ liver microsome films prepared on 500,nm silica nanoparticles (nanoreactors) and reacted with nitrosamine or styrene, provided LC-MS or GC analyses of metabolite formation rates that correlated well with sensor response. [source]

Comparison of triple quadrupole, hybrid linear ion trap triple quadrupole, time-of-flight and LTQ-Orbitrap mass spectrometers in drug discovery phase metabolite screening and identification in vitro , amitriptyline and verapamil as model compounds

RAPID COMMUNICATIONS IN MASS SPECTROMETRY, Issue 7 2010
Timo Rousu
Liquid chromatography in combination with mass spectrometry (LC/MS) is a superior analytical technique for metabolite profiling and identification studies performed in drug discovery and development laboratories. In the early phase of drug discovery the analytical approach should be both time- and cost-effective, thus providing as much data as possible with only one visit to the laboratory, without the need for further experiments. Recent developments in mass spectrometers have created a situation where many different mass spectrometers are available for the task, each with their specific strengths and drawbacks. We compared the metabolite screening properties of four main types of mass spectrometers used in analytical laboratories, considering both the ability to detect the metabolites and provide structural information, as well as the issues related to time consumption in laboratory and thereafter in data processing. Human liver microsomal incubations with amitriptyline and verapamil were used as test samples, and early-phase ,one lab visit only' approaches were used with all instruments. In total, 28 amitriptyline and 69 verapamil metabolites were found and tentatively identified. Time-of-flight mass spectrometry (TOFMS) was the only approach detecting all of them, shown to be the most suitable instrument for elucidating as comprehensive metabolite profile as possible leading also to lowest overall time consumption together with the LTQ-Orbitrap approach. The latter however suffered from lower detection sensitivity and false negatives, and due to slow data acquisition rate required slower chromatography. Approaches with triple quadrupole mass spectrometry (QqQ) and hybrid linear ion trap triple quadrupole mass spectrometry (Q-Trap) provided the highest amount of fragment ion data for structural elucidation, but, in addition to being unable to produce very high-important accurate mass data, they suffered from many false negatives, and especially with the QqQ, from very high overall time consumption. Copyright © 2010 John Wiley & Sons, Ltd. [source]

Liquid chromatography/tandem mass spectrometric quantification with metabolite screening as a strategy to enhance the early drug discovery process

RAPID COMMUNICATIONS IN MASS SPECTROMETRY, Issue 12 2002
Philip R. Tiller
Throughput for early discovery drug metabolism studies can be increased with the concomitant acquisition of metabolite screening information and quantitative analysis using ultra-fast gradient chromatographic methods. Typical ultra-fast high-performance liquid chromatography (HPLC) parameters used during early discovery pharmacokinetic (PK) studies, for example, employ full-linear gradients over 1,2,min at very high flow rates (1.5,2,mL/min) on very short HPLC columns (2,×,20,mm). These conditions increase sample throughput by reducing analytical run time without sacrificing chromatographic integrity and may be used to analyze samples generated from a variety of in vitro and in vivo studies. This approach allows acquisition of more information about a lead candidate while maintaining rapid analytical turn-around time. Some examples of this approach are discussed in further detail. Copyright © 2002 John Wiley & Sons, Ltd. [source]

SyGMa: Combining Expert Knowledge and Empirical Scoring in the Prediction of Metabolites

CHEMMEDCHEM, Issue 5 2008
Lars Ridder Dr.
Abstract Predictions of potential metabolites based on chemical structure are becoming increasingly important in drug discovery to guide medicinal chemistry efforts that address metabolic issues and to support experimental metabolite screening and identification. Herein we present a novel rule-based method, SyGMa (Systematic Generation of potential Metabolites), to predict the potential metabolites of a given parent structure. A set of reaction rules covering a broad range of phase,1 and phase,2 metabolism has been derived from metabolic reactions reported in the Metabolite Database to occur in humans. An empirical probability score is assigned to each rule representing the fraction of correctly predicted metabolites in the training database. This score is used to refine the rules and to rank predicted metabolites. The current rule set of SyGMa covers approximately 70,% of biotransformation reactions observed in humans. Evaluation of the rule-based predictions demonstrated a significant enrichment of true metabolites in the top of the ranking list: while in total, 68,% of all observed metabolites in an independent test set were reproduced by SyGMa, a large part, 30,% of the observed metabolites, were identified among the top three predictions. From a subset of cytochrome P450 specific metabolites, 84,% were reproduced overall, with 66,% in the top three predicted phase,1 metabolites. A similarity analysis of the reactions present in the database was performed to obtain an overview of the metabolic reactions predicted by SyGMa and to support ongoing efforts to extend the rules. Specific examples demonstrate the use of SyGMa in experimental metabolite identification and the application of SyGMa to suggest chemical modifications that improve the metabolic stability of compounds. [source]