A New Psychoactive Substance (NPS) is defined by United Nation Office of Drugs and Drug Addiction (UNODC) as a “substance of abuse, either in a pure form or a preparation, that is not controlled by the 1961 Single Convention on Narcotic Drugs or the 1971 Convention on Psychotropic Substances, but which may pose a public health threat”. To date, more than 1,100 molecules have been identified as NPS in the illicit market and every year a variable number of new alternatives appears for the first time. The mutating nature of the NPS market represents one of the most challenging aspects of the fight against this public health issues because little is known about the toxicological profile of these substances when they appear for the first time. To this concern, the in vitro metabolic studies are considered the first step in the understanding of the pharmacology of NPS, allowing the individuation of possible biomarkers of consumption. We studied the in vitro metabolism of three different NPS, two fentanyl analogues and one synthetic cathinone, in two different incubation batches according to a consolidated protocol. First, we studied phenylfentanyl and b’-phenylfentanyl metabolic fate using in silico predictions with GLORYx freeware, human hepatocyte incubations, and liquid chromatography-high-resolution tandem mass spectrometry (LC-HRMS/MS). We applied a specific targeted/untargeted workflow using data-mining software to allow the rapid and partially automated screening of LC-HRMS/MS raw data. Although the similar structure of phenylfentanyl and b’-phenylfentanyl, we observed several differences in the metabolic fate of the two analogues. The first difference is in the number of metabolites, in fact we characterized 13 phenylfentanyl metabolites and 27 b’phenylfentanyl metabolites. Furthermore, the in vitro formation of 4-anilino-phenethylpiperidine, one of the most common fentanyl analogue metabolites, was observed only for phenylfentanyl. The hydroxylation reactions were preferred for b’phenylfentanyl, targeting the lateral alkyl chain and the phenyl rings. Moreover, phase II metabolites were found only in b’-phenylfentanyl, such as glucuronides and O-methylated metabolites. However, the most intense signal was produced by the N-dealkylated metabolite, the so called nor-metabolites, in both the chromatographic separations. The differences in the metabolic fate suggest an important role of the lateral alkyl chain of fentanyl analogues. An extended in silico metabolic prediction strategy was applied for the prediction of 3fuoro-a-pyrrolidovalerophenon (3f-a-PVP), using three specific freeware to obtain a more comprehensive prediction. The same analytical and data-mining strategy was then applied for the 3f-a-PVP study. The same analytical strategy and data-mining approach was successfully applied to investigate the metabolites produced during the incubations. Ten metabolites were identified after 3 h incubation, including hydrogenated, hydroxylated, oxidated, and N-dealkylated metabolites. A total of 51 phase I and II metabolites were predicted, among which 7 were detected in the incubations. We suggest 3F-α-PVP N-butanoic acid, 3F-α-PVP pentanol, and 3F-α-PVP 2-ketopyrrolidinyl-pentanol as specific biomarkers of 3F-α-PVP consumption. This is the first time that an N-ethanoic acid is detected in the metabolic pathway of a pyrrolidine SC, demonstrating the importance of a dual targeted/untargeted data mining strategy

Profiling of in vitro metabolism of New Psychoactive Substances

DI TRANA, ANNAGIULIA
2022-06

Abstract

A New Psychoactive Substance (NPS) is defined by United Nation Office of Drugs and Drug Addiction (UNODC) as a “substance of abuse, either in a pure form or a preparation, that is not controlled by the 1961 Single Convention on Narcotic Drugs or the 1971 Convention on Psychotropic Substances, but which may pose a public health threat”. To date, more than 1,100 molecules have been identified as NPS in the illicit market and every year a variable number of new alternatives appears for the first time. The mutating nature of the NPS market represents one of the most challenging aspects of the fight against this public health issues because little is known about the toxicological profile of these substances when they appear for the first time. To this concern, the in vitro metabolic studies are considered the first step in the understanding of the pharmacology of NPS, allowing the individuation of possible biomarkers of consumption. We studied the in vitro metabolism of three different NPS, two fentanyl analogues and one synthetic cathinone, in two different incubation batches according to a consolidated protocol. First, we studied phenylfentanyl and b’-phenylfentanyl metabolic fate using in silico predictions with GLORYx freeware, human hepatocyte incubations, and liquid chromatography-high-resolution tandem mass spectrometry (LC-HRMS/MS). We applied a specific targeted/untargeted workflow using data-mining software to allow the rapid and partially automated screening of LC-HRMS/MS raw data. Although the similar structure of phenylfentanyl and b’-phenylfentanyl, we observed several differences in the metabolic fate of the two analogues. The first difference is in the number of metabolites, in fact we characterized 13 phenylfentanyl metabolites and 27 b’phenylfentanyl metabolites. Furthermore, the in vitro formation of 4-anilino-phenethylpiperidine, one of the most common fentanyl analogue metabolites, was observed only for phenylfentanyl. The hydroxylation reactions were preferred for b’phenylfentanyl, targeting the lateral alkyl chain and the phenyl rings. Moreover, phase II metabolites were found only in b’-phenylfentanyl, such as glucuronides and O-methylated metabolites. However, the most intense signal was produced by the N-dealkylated metabolite, the so called nor-metabolites, in both the chromatographic separations. The differences in the metabolic fate suggest an important role of the lateral alkyl chain of fentanyl analogues. An extended in silico metabolic prediction strategy was applied for the prediction of 3fuoro-a-pyrrolidovalerophenon (3f-a-PVP), using three specific freeware to obtain a more comprehensive prediction. The same analytical and data-mining strategy was then applied for the 3f-a-PVP study. The same analytical strategy and data-mining approach was successfully applied to investigate the metabolites produced during the incubations. Ten metabolites were identified after 3 h incubation, including hydrogenated, hydroxylated, oxidated, and N-dealkylated metabolites. A total of 51 phase I and II metabolites were predicted, among which 7 were detected in the incubations. We suggest 3F-α-PVP N-butanoic acid, 3F-α-PVP pentanol, and 3F-α-PVP 2-ketopyrrolidinyl-pentanol as specific biomarkers of 3F-α-PVP consumption. This is the first time that an N-ethanoic acid is detected in the metabolic pathway of a pyrrolidine SC, demonstrating the importance of a dual targeted/untargeted data mining strategy
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11566/300345
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