Exploiting the triple quadrupole mass analyzer for the open detection and tentative identification of synthetic cannabinoid receptor agonists based on common fragmentation pathways

Exploiting the triple quadrupole mass analyzer for the open detection and tentative identification of synthetic cannabinoid receptor agonists based on common fragmentation pathways María Mata-Pesquera a , David Fabregat-Safont a,b , Juan V. Sancho a , María Ib´ a˜ nez a,* a Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avda. Sos Baynat s/n, 12071, Castell´ o de la Plana, Spain b Applied Metabolomics Research Group, Hospital del Mar Research Institute, 88 Doctor Aiguader, 08003, Barcelona, Spain HIGHLIGHTS GRAPHICAL ABSTRACT •UHPLC-MS/MS strategy for the detection and tentative identification of SCRAs. •Use of precursor ion scan and neutral loss scan QqQ working modes. •Proposal of the main PIs and NLs derived from 179 SCRAs and database creation. •Applicability demonstrated through the analysis of 30 blind research chemicals. •Identification of an O-demethylated SCRA metabolite in a consumer urine sample. ARTICLE INFO Handling Editor: L. Liang Keywords: New psychoactive substances Synthetic cannabinoids receptor agonists Liquid chromatography Tandem mass spectrometry Precursor ion scan Neutral loss scan ABSTRACT Background: The use of new psychoactive substances (NPS) has emerged as a significant public health concern globally, due to their unknown and unpredictable effects on both physical and mental health. Among them, synthetic cannabinoids receptor agonists (SCRAs) currently stand as the most widely consumed NPS family in Europe. Since the detection of JWH-018 in 2008, the structures of these compounds have evolved to circumvent legislation and/or enhance their effects, consequently increasing the number of reported SCRAs to be monitored. Therefore, new strategies are needed to identify these compounds, whether in seized products or in biological samples. Results: This study presents the development of an open method for detecting SCRAs employing a “pseudo-target” screening approach, a strategy previously developed and used in our laboratory for synthetic cathinones identification. The methodology involves monitoring the main product ions and neutral losses derived from 179 * Corresponding author. E-mail address: [email protected] (M. Ib´ a˜ nez). Contents lists available at ScienceDirect Analytica Chimica Acta journal homepage: www.elsevier.com/locate/aca https://doi.org/10.1016/j.aca.2024.343226 Received 5 July 2024; Received in revised form 5 September 2024; Accepted 8 September 2024 Analytica Chimica Acta 1329 (2024) 343226 Available online 10 September 2024 0003-2670/© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/bync-nd/4.0/ ). SCRAs of the third and fourth generations, based on their fragmentation pathways. This approach allows for the tentative identification of the SCRAs, supported also by the created database. The versatility of the developed methodology is highlighted, extending its utility beyond seizure products or ‘legal highs’, to biological samples. In this sense, it has been successfully applied not only to the detection of SCRAs in research chemicals but also in authentic urine from an anonymous SCRAs consumer, through the identification of a metabolite. Significance: This strategy will be particularly useful for the rapid detection of SCRAs in forensic and toxicological laboratories equipped with low-resolution MS/MS instrumentation. This is a valuable tool for the identification and monitoring of SCRAs across various contexts, significantly contributing to public health and forensic security efforts. It is especially beneficial for healthcare providers, enabling them to make informed treatment decisions. 1. Introduction The continued diversification and worldwide use of new psychoactive substances (NPS) remain not only a public health problem but also a legal and drug policy challenge, with science, surveillance and law enforcement struggling to keep up with the growing range of new NPS designers [1]. NPS represent a multitude of synthetic and natural compounds marketed as legal alternatives to conventional illicit drugs, being the synthetic cannabinoids receptor agonists (SCRAs) family the most consumed in Europe nowadays [2]. In fact, by the end of 2023, the European Union Drugs Agency (EUDA) was monitoring a total of 254 SCRAs [2]. Initially, SCRAs were synthetized for various medical research purposes, such as the treatment of neurodegenerative diseases, pain disorders or cancer [3–5]. Nevertheless, several SCRAs started to be synthetized in clandestine laboratories at the beginning of the century and introduced in the NPS market, typically mixed with dried herbal mixtures, as legal alternatives to cannabis [3]. More recently, these compounds have been found in tablet form, powder, or even in the refill liquid of e-cigarette cartridges [5,6]. Psychoactive effects of SCRAs are produced by their binding affinity to the CB1 and CB2 cannabinoid receptors. Generally, the structures of SCRAs tend to have a higher affinity for these receptors compared to Δ 9 - THC, resulting in more adverse reactions and toxicities [4]. The pharmacological and toxicological effects of most SCRAs are unknown, so their consumption results in numerous cases of intoxication and deaths [7,8]. The first notification of an SCRA reported to the EU Early Warning System (EU EWS) was in 2008 with the detection of JWH-018 in an herbal product in Germany and Austria [9,10]. This compound gave rise to the first generation of SCRAs, the JWH family, named after John W. Huffman, through minor modifications of its structure [6,11]. After that, new generations of SCRAs have emerged by modifying their structures with the aim of evading legislation and/or increase their effects [4]. Although SCRAs are very diverse, molecular structures are commonly divided into four components: tail, core, linker, and linked group (Fig. 1) [12,13]. These subunits can be modified and combined in very different ways leading to different families. SCRAs nomenclature and classification is quite difficult due to their wide structural variety. Recently, the EMCDDA has systematised an abbreviated nomenclature method that assigns a code name to each component of the structure and relates it with format name ‘LinkedGroup-TailCoreLinker’ [5]. In this way, the synthetic cannabinoid N-(1-adamantyl)-1-pentyl-1H-indole-3-carboxamide is known as APICA [5]. However, despite this, there are SCRAs known by two or more different names. The high number and structural variety of SCRAs is a challenge for analytical chemists and toxicologists, often related to limited capacity for detecting and monitoring these compounds. Identifying SCRAs in biological samples poses an even greater challenge due to their fast and extensive metabolism and limited information available on literature [17]. This makes essential to explore novel approaches to prospect new sensing strategies. Liquid chromatography coupled to hybrid high resolution mass spectrometry instruments (LC-HRMS) is the gold-standard for obtaining structural information about SCRAs, as it provides accurate-mass full acquisition data as well as fragmentation Fig. 1. General chemical structure of SCRAs and common core, linker, tail and linked groups [12]. M. Mata-Pesquera et al. Analytica Chimica Acta 1329 (2024) 343226 2 information. Nevertheless, HRMS instruments are complex and expensive, and are not as readily available in regular laboratories as low-resolution tandem mass spectrometry (MS/MS) instruments. For this reason, it is mandatory to implement new LC-MS/MS methodologies that allow the detection of the highest number of SCRAs. The most common working mode in LC-MS/MS using triple quadrupole mass analyser (QqQ) is the Selected Reaction Monitoring (SRM). This mode provides the best selectivity, sensitivity and robustness, but the number of SRM simultaneously acquired is limited, so it can be only used for the targeted determination of a certain number of compounds. Nevertheless, other working modes are available when using QqQ instruments, such as precursor ion scan (PIS) and neutral loss scan (NLS), which can be useful for the detection of related compounds based on previously known fragmentation behaviour [14]. On the PIS working mode, the first quadrupole is scanning, while the second quadrupole is monitoring a certain product ion generated in the collision cell at a fixed collision energy [15]. This mode is especially useful for the identification of compounds with different structures that produce the same fragment ion. NLS mode consists of fixing a mass offset between the two quadrupoles, which are continuously scanning a determined mass range. This mass offset corresponds to a specific neutral loss characteristic of compounds with a particular structure [15]. For example, a neutral loss of 32 Da would correspond to the loss of one molecule of methanol. In this work, an open detection method for SCRAs has been developed using ultra-high performance LC coupled to MS/MS (UHPLC-MS/ MS). The method involves monitoring the main product ions (PIs) and neutral losses (NLs) obtained for the third and fourth generation of SCRAs. Based on the observed PIs and NLs, and supported by the database created, a tentative structure can be proposed, allowing for a tentative identification of the SCRA. This strategy is based on a previous approach developed in our laboratory for the identification of synthetic cathinones in seized products [14]. As a proof of concept, the method was applied to detect SCRA in authentic research chemicals samples but also in the urine from an anonymous SCRA consumer. This strategy will be particularly useful for rapid SCRAs detection in laboratories equipped only with low-resolution MS/MS instruments, as it allows effective analysis through six injections per sample. 2. Material and methods 2.1. Reagents and chemicals LC-MS grade water was obtained by purifying demineralized water using an Ultramatic Plus GR from Wasserlab (Navarra, Spain). LC-MS grade methanol (MeOH), formic acid (HCOOH), acetone and hydrochloric acid (HCl 37 %) were purchased from Scharlau (Scharlab, Barcelona, Spain). Diammonium hydrogen phosphate ((NH 4 ) 2 HPO 4 ) was acquired from Merck (Darmstadt, Germany). β-glucuronidase from E. Coli strain K12 (80 U/mL at 25 ◦C) was purchased from Roche (Indianapolis, IN, USA). (NH 4 ) 2 HPO 4 was dissolved in LC-MS grade water to prepare a 1 M H 2 PO 4 − /HPO 4 2− buffer and the pH was adjusted to 7 with HCl. Research chemicals were provided by Energy Control (Asociaci´ on Bienestar y Desarrollo, Barcelona, Spain) [16]. 2.2. Samples used for testing the strategy 30 samples were submitted by anonymous users to Energy Control’s drop-in service and analysed by gas chromatography-mass spectrometry with electron ionization (GC-EI-MS). One aliquot of the samples was also sent to our laboratory for analysis by UHPLC-MS/MS. A urine sample from an anonymous SCRAs consumer was collected in a polypropylene tube and kept at −20 ◦C until analysis. This sample was obtained following the approved ethical protocol from Universitat Jaume I (CEISH/19/2024), ensuring the anonymity of the consumer. 2.3. Sample treatment For research chemical samples, 10 mg of powder or seized material were extracted with 1 mL of acetone and vortexed for 1 min. After centrifugation, the supernatant was 10 5 -fold diluted with LC-MS grade water. Regarding urine sample, an enzymatic hydrolysis was applied. Briefly, 400 μ L of phosphate buffer and 16 μ L of β-glucuronidase were added to 1 ml of urine [17]. Sample was then incubated for 1 h at 55 ◦C and frozen at −20 ◦C for 2 h as clean-up for removing proteins and lipids. Finally, sample was centrifugated at 12000 rpm for 15 min and 10 μ L of supernatant were injected into the UHPLC-MS/MS system. 2.4. Instrumentation An Acquity UPLC H-Class ultra-high performance liquid chromatography system (Waters, Mildford, MA, USA) was coupled to a Xevo TQ-S triple quadrupole mass spectrometer (Waters, Manchester, UK) equipped with a Z-Spray electrospray. For chromatographic separation, a Cortecs C18 2.1 ×100 mm, 2.7 μ m analytical column (Waters Corp, Wexford, Ireland) maintained at 40 ◦C was used. Mobile phases consisted of water (solvent A) and MeOH (solvent B) both with 0.01 % formic acid, delivered at a flow rate of 0.3 mL/min and changing as follows: 5 % of B at 0 min, 100 % of B at 4 min linearly increased, 100 % of B maintained until 6 min and, finally, 5 % of B at 6.10 min maintained to 8 min. The injection volume was 10 μ L. ESI was operated in positive ionization mode using a capillary voltage of 1.5 kV. Nitrogen was used as desolvation (1200 L/h) and cone gas (250 L/h), while Argon (99.995 %, Praxair) was used as collision gas. Source and desolvation temperature were set to 150 ◦C and 650 ◦C, respectively. Cone voltage was stablished at 30 V and collision energy, at 25 eV. Table 1 lists the PIs and NLs included in the method. Due to the large number of PIs, they were divided across four injections, while NLs were split into two injections. Consequently, a total of six injections of 8 min each, are performed per sample. The mass range scanned in the first quadrupole was from m/z 230 to 430, with a scan time of 0.1 s and a duty cycle of 1.8 s. UHPLC-MS/MS data were acquired and processed using MassLynx 4.1. software (Waters Corp, Manchester, UK). Table 1 PIs and NLs selected for SCRAs identification. Working mode: PIS Working mode: NLS Injection 1 MS2 (Fixed at m/z) Injection 2 MS2 (Fixed at m/z) Injection 3 MS2 (Fixed at m/z) Injection 4 MS2 (Fixed at m/z) Injection 1 MS2 (Mass offset of) Injection 2 MS2 (Mass offset of) 91 219 270 314 179 Da 99 Da 97 222 272 317 176 Da 98 Da 109 226 279 318 164 Da 96 Da 127 227 283 319 159 Da 88 Da 135 228 284 320 158 Da 85 Da 144 229 286 323 157 Da 84 Da 145 232 289 324 145 Da 82 Da 155 233 290 325 144 Da 81 Da 158 234 297 326 143 Da 74 Da 198 235 298 333 135 Da 71 Da 199 240 299 334 131 Da 70 Da 200 241 300 337 130 Da 68 Da 201 243 303 338 119 Da 57 Da 212 248 304 351 116 Da 56 Da 213 249 305 352 108 Da 54 Da 214 252 308 359 107 Da 46 Da 215 253 311 360 104 Da 32 Da 218 266 312 364 102 Da 17 Da M. Mata-Pesquera et al. Analytica Chimica Acta 1329 (2024) 343226 3 3. Results and discussion 3.1. SCRAs chemical structures As it has already been commented, SCRAs have a complex molecular structure, consisting of four components. The core group consists in an aromatic ring structure, being the most common indoles, indazoles, carbazoles, and bi-cyclic azaindoles, among others [12]. The tail is generally formed by an alkyl chain to which a halogen atom can be added in some cases. The length and arrangement of this chain can vary, mainly affecting the binding to the CB1 receptor [6,12]. The linker is the group that binds the core with the linked group, being the most common methanone, acetamide, carboxamide and carboxylate ester groups [12]. Finally, the linked group can be aromatic (such as naphthyl, adamantyl, quinolinyl and cumyl) or non-aromatic (such as methyl-3-methylbutanoate, methyl-3,3-dimethylbutanoate, 3-methylbutanamide and 3,3-dimethylbutanamide, among others) [12]. The most common core, tail, linker and linked groups are shown in Fig. 1. This structural complexity offers multiple opportunities for chemical modification to evade drug control legislation based on chemical structure, and this explains the large number of individual products that have been detected [12]. In this study, the most common SCRAs with a core based on indole, indazole and azaindole groups have been selected. Concretely, a total of 179 SCRAs have been included. 3.2. Selection of PIs and NLs to be monitored Only 11 standards of SCRAs were available in our laboratory, for which the main PIs and NLs were selected. The fragmentation pathway for most of the remaining SCRAs included in the study were not found in the literature, so their PIs and NLs were deduced based on the information available [18–21]. For example, the fragmentation pathway of AMB-FUBINACA [22] was used to propose the product ions derived from SCRAs with a 4-fluorobenzyl tail and a butanoate linked group. In this way, the main PIs and NLs that can be originated from each of the 179 SCRAs selected were proposed and a database was created including all this information (see Supplementary Material). Finally, the common PIs and NLs were selected considering that, although some of them have different structure and molecular formula, they have the same nominal mass. Thus, PI of m/z 213 could be originated by a penten-4-yl or a cyclopentyl methyl tail linked to an indazole core. Finally, 72 PIs and 36 NLs were monitored for the open detection of SCRAs. As this is a high number of PIs and NLs for a single injection, PIs were divided into 4 injections, and NLs, into 2 injections (see Table 1). Consequently, 6 injections per sample are performed. After sample injection, data obtained are evaluated to elucidate the SCRA structure. Only chromatographic peaks that appear at the same retention time for different PIs and NLs are evaluated, while peaks observed in blanks or only in certain PIs and/or NLs are directly discarded. The positive PIs and NLs are then searched for in the database created, along with the m/z of the parent compound obtained from the mass spectra of any function. This approach allows for the tentative identification of the SCRA and the proposal of its structure based on the detected PIs and NLs. 3.3. Application to research chemical samples The applicability of the developed strategy was demonstrated through the analysis of 30 blind research chemicals collected by Energy Control, which had been previously analysed by GC-EI-MS. Additionally, HRMS experiments were performed a posteriori to confirm the structure of the compounds. Further information about GC-EI-MS and HRMS analyses can be found in literature [23,24]. The results obtained in each of the experiments are summarized in Table 2. Of the 30 samples analysed, 25 were successfully elucidated in accordance with the results obtained by GC-EI-MS; however, in some cases, there was more than one candidate due to the presence of structural or positional isomers. Concretely, in samples 14 and 15, it was not possible to distinguish whether the linked group was a methyl-3-methyl-butanoate or ethyl-3-methyl-butanoate as both lead to a neutral loss of 131 Da. The same occurred in sample 18 with the linked groups 3-methyl-butanamide and 2-aminopentanamide. In the case of samples 16 and 30, the fluorine atom of the tail could be in any position of the alkyl chain; whereas the SCRA present in sample 17 could have an indazole or azaindole core. In the case of sample 20, additional MS/MS experiments were performed to distinguish between two possible candidates, as their structures (and also PIs) have the same nominal mass. Finally, sample 19 contained a mixture of two SCRAs (please, see case study 2 for more details). This methodology also allowed the correct identification of SCRAs present in samples 6 and 19, which were not accurately named by GC-EIMS. This was surely due to the hard mass ionization technique used, which results in most cases in the absence of the molecular ion in the spectrum. Only 3 compounds (EG-018, 5F-CUMYL-PEGLACONE and AB-CHFUBPYCA) could not be identified using this methodology as they present significantly different structures compared to those based on indole, indazole and azaindole groups included in the database. Therefore, expanding the range of core structures could be considered for future work. To illustrate the methodology developed, different case studies are shown below. 3.3.1. Case 1 Product ions at m/z 144, 212 and 232 were identified in sample 24 Table 2 Summary of the results obtained for the analysed samples. Sample number GC-EI-MS identification LC-MS/MS identification LC-HRMS identification 1 THJ-2201 THJ-2201 THJ-2201 2 5F-MDMBPINACA 5F-MDMB-PINACA 5F-MDMB-PINACA 3 5F-AB-PINACA 5F-AB-PINACA 5F-AB-PINACA 4 5F-APP-PICA 5F-APP-PICA 5F-APP-PICA 5 AMB-FUBINACA AMB-FUBINACA AMB-FUBINACA 6 XLR-11 5F-MN-24 5F-MN-24 7 XLR-11 XLR-11 XLR-11 8 UR-144 UR-144 UR-144 9 EG-018 –EG-018 10 EMB-FUBINACA EMB-FUBINACA EMB-FUBINACA 11 AM-2201 AM-2201 AM-2201 12 5F-CUMYLPEGLACONE –5F-CUMYLPEGLACONE 13 5F-AEB 5F-AEB 5F-AEB 14 AMB-FUBINACA AMB-FUBINACA or MEP-FUBINACA AMB-FUBINACA or MEP-FUBINACA 15 AMB-FUBINACA AMB-FUBINACA or MEP-FUBINACA AMB-FUBINACA or MEP-FUBINACA 16 5F-AMB 2F-, 3F-, 4For 5FAMB 2F-, 3F-, 4For 5FAMB 17 5F-AKB48 5F-AKB48 or 5FAKB48-7 N 5F-AKB48 or 5FAKB48-7 N 18 AB-PINACA AEP-PINACA or ABPINACA AEP-PINACA or ABPINACA 19 5F–PCN MFUBINAC +ADBFUBINACA MFUBINAC +ADBFUBINACA 20 5F-PB-22 5F-PB-22 5F-PB-22 21 ADB-BUTINACA ADB-BUTINACA ADB-BUTINACA 22 AB-CHFUPYCA –AB-CHFUPYCA 23 5Cl-AB-PINACA 5Cl-AB-PINACA 5Cl-AB-PINACA 24 5F-CUMYL-PICA 5F-CUMYL-PICA 5F-CUMYL-PICA 25 AB-FUBINACA AB-FUBINACA AB-FUBINACA 26 4F-MDMB-BICA 4F-MDMB-BICA 4F-MDMB-BICA 27 AM-2201 AM-2201 AM-2201 28 ADB-FUBINACA ADB-FUBINACA ADB-FUBINACA 29 5Cl-AB-PINACA 5Cl-AB-PINACA 5Cl-AB-PINACA 30 5F-AMB 2F-, 3F-, 4For 5FAMB 2F-, 3F-, 4For 5FAMB M. Mata-Pesquera et al. Analytica Chimica Acta 1329 (2024) 343226 4 (Fig. 2A). PI 144 indicates that the SCRA belongs to the indole family while PI 232 indicates that the tail of this SCRA corresponds to fluoropentane, also confirmed by the presence of PI 212 obtained after the loss of HF [19]. On the other hand, the neutral losses of 88 and 135 Da were assessed (Fig. 2B). NL 135 indicates the presence of cumyl as linked group and NL 88 confirms the fluoropentane as tail group. Generally, the tail consists on 5-fluoropentane, although in some cases fluorine can also be found in the 2-, 3or 4-position [25–27]. Confirmation of the fluorine position was not possible with this strategy (with any MS strategy, in general), so an additional technique such as nuclear magnetic resonance (NMR) would be required. Finally, the mass spectrum was extracted from NL 135 function (Fig. 2C) showing the protonated molecule at m/z 367. Combining all the parts of the molecule and searching for in the database, the SCRA was identified as CUMYL-5F-PICA [28]. Fig. 2. Identification of CUMYL-5F-PICA in sample 24. Total Ion Chromatogram (TIC) of detected PIs (A) and NLs (B), and mass spectrum obtained from NL 135 (C). Fig. 3. Identification of a mixture of MFUBINAC (A) and ADB-FUBINACA (B) in sample 19. Total Ion Chromatogram (TIC) of detected PIs and NLs (left) and mass spectrum obtained from NL 176 and 130, respectively (right). M. Mata-Pesquera et al. Analytica Chimica Acta 1329 (2024) 343226 5 3.3.2. Case 2 Regarding sample 19, a double peak was observed for product ions of m/z 109 and 253 (Fig. 3) at 5.18 and 5.24 min, indicating the presence of two SCRAs. PI 109 corresponds to a fluorotropylium ion obtained after the N-alkyl core disconnection [29], whereas PI 253 is originated by the union of an indazole core with a para-fluorotoluene tail. Therefore, the two compounds of the mixture corresponded to the indazole family and contained a para-fluorotoluene tail. In order to know which linked and linker groups contained, it was necessary to assess NLs. Focusing on the peak at retention time 5.18 min, NLs of 176, 144 and 32 Da were observed, corresponding to methyl 1H-indazole-3-carboxylate, the loss of methanol from NL 176 and the methanol loss itself, respectively (Fig. 3A, left). In addition, mass spectrum showed the protonated molecule at m/z 285 (Fig. 3A, right). All this information was combined and searched for in the database and perfectly fitted with MFUBINAC [30]. On the other hand, the mass spectrum of the peak at retention time 5.24 min showed the precursor ion at m/z 383 (Fig. 3B, right), and also additional ions at m/z 366 and 338. These two ions could correspond to in-source fragments produced after an initial NH 3 loss and posterior CO loss, respectively, typically observed for terminal amide moieties [31]. In addition, NLs of 130 and 85 Da were observed (Fig. 3B, left). NL 130 corresponds to 2-amino-3,3-dimethylbutanamide and NL 85 corresponds to 2,2-dimethylpropan-1-imine, obtained after the disconnection of the C–N amide bond once NH 3 and CO are lost. All this information allowed the identification of ADB-FUBINACA [32]. Therefore, sample 19 contained a mixture of MFUBINAC and ADB-FUBINACA. 3.3.3. Case 3 On some occasions, compound identification was not as direct as in the previous examples. Fig. 4A and B shows the PIs (at m/z 144, 212 and 232) and NLs (145 and 88 Da) identified in sample 20, respectively. The presence of PI 144 indicates an indole core. PI 232 and PI 212 indicate a fluoropentane tail, which was also confirmed by the presence of NL 88. Nevertheless, NL 145 may be due to two different structures: 8-quinolinol or methyl 2-amino-3,3-dimethylbutanoate. The mass spectrum (Fig. 4C) showed the protonated molecule at m/z 377. When searching for in the database, two candidates appeared: 5F-MDMB-PICA and 5FPB-22. These compounds are isobaric and, in addition, their main PIs and NLs also have the same nominal mass. The absence of the NL 32, 85 and 145 Da corresponding to methanol, 2-methylpropan-1-imine and methyl 2-amino-3,3-dimethylbutanoate, respectively, derived from the methyl 2-amino-3,3-dimethylbutanoate termination suggests that the compound is 5F-PB-22. Nonetheless, as the method developed did not allow to directly differentiate between both possibilities, an additional QqQ working mode was used to obtain the complete fragmentation spectra of the suspect compound. In this way, a product ion scan was performed at different collision energies (5–60 eV). In addition to the PIs already observed when applying the methodology developed (m/z 144, 212 and 232), the MS/MS spectrum at 45 eV showed PI at m/z 116, 89, 130, and 69 from highest to lowest intensity (Fig. 5A). PI 116 is obtained after a CO loss from PI 144, PI 89 is characteristic of SCRAs with an indole ring [18] and PI 69 corresponds to pent-4-en-1-ylium ion, therefore not resulting useful in the elucidation. Minor PI 130 could be justified by a loss of water from quinolin-8-yloxonium, making 5F-PB-22 (also known as 5F-QUPIC) the most plausible option [33,34]. The whole proposed fragmentation pathway of 5F-PB-22 can be found in Fig. 5B. 3.4. Application to a urine sample from a SCRA user Finally, the versatility of the developed methodology was assessed by applying it to a urine sample obtained from an anonymous SCRAs consumer. As it is shown in Fig. 6A and B, PIs of m/z 145 and 213 and NLs of 131 and 85 Da were observed, respectively. In addition, the mass Fig. 4. Identification of SCRA present in sample 20: 5F-PB-22 vs 5F-MDMB-PICA. Total Ion Chromatogram (TIC) of detected PIs (A) and NLs (B), and mass spectrum obtained from PI 232 (C). M. Mata-Pesquera et al. Analytica Chimica Acta 1329 (2024) 343226 6 spectrum obtained from PI 253 showed the precursor ion at m/z 344 (Fig. 6C). These PIs and NLs were searched for in the database and they could fit with MDMB-4en-PINACA and ADB-4en-PINACA, but the [M+H] + of neither of them was 344. As SCRAs are rapidly metabolised, it is unlikely to find the unaltered compound in urine [35]; so the observed PIs and NLs surely correspond to a metabolite of the consumed compound, and probably a phase I metabolite based on the observed m/z and the use of enzymatic hydrolysis for glucuronide cleavage. The m/z of the unknown compound was 14 Da lower than the m/z of MDMB-4en-PINACA and 1 Da higher Fig. 5. Identification of 5F-PB-22 in sample 20. MS/MS spectra at 45 eV (A) and proposed fragmentation pathway (B). Fig. 6. Identification of MDMB-4en-PINACA O-demethyl metabolite in a urine sample from a consumer. Total Ion Chromatogram (TIC) of detected PIs (A) and NLs (B), and mass spectrum obtained from PI 232 (C). M. Mata-Pesquera et al. Analytica Chimica Acta 1329 (2024) 343226 7 than the m/z of ADB-4en-PINACA. Considering the structure of each of them, MDMB-4en-PINACA could be easily demethylated resulting in O-demethyl metabolite, a process that involves a mass loss of 14 Da [36]. Based on the structure of this metabolite, the PIs and NLs observed were explained. PI 145 is typical of SCRAs corresponding to the indazole family and PI 213 corresponds to the union of the indazole core with a pentene tail. Regarding neutral losses, NL 131 corresponds to 2-amino-3, 3-dimethylbutanoic acid and NL 85, to 2,2-dimethylpropan-1-imine. In this way, it could be concluded that the consumer had taken MDMB-4en-PINACA. This example shows the high potential of the developed methodology not only for seizure products or ‘legal highs’, but also to identify which substance has been consumed by detecting a metabolite in urine. This rapid response is particularly valuable for administering effective treatment in cases of intoxication, enabling the management of symptoms and alleviating adverse effects. 4. Conclusion In this study, a strategy for the open detection and tentative identification of the last generations of SCRAs using UHPLC-MS/MS has been developed. The methodology is based on the common fragmentation pathways observed and/or expected for 179 SCRAs. The strategy combines 72 PIs and 36 NLs, although the MS/MS method can be periodically updated to include new SCRAs as they appear on the market. The main drawback of this method is that each sample must be injected 6 times to adequately acquire all the PIS and NLS, which increases the total analysis time to 50 min per sample. This methodology has proven its applicability to research chemicals, even those containing mixtures of SCRAs. For isobaric compounds sharing isobaric PIs and NLs, the handicap has been addressed without the need for a high-resolution mass analyser, by performing additional MS/MS experiments. Similarly to HRMS, an orthogonal technique, such as NMR, is required for unequivocal identification of isomeric SCRAs. Moreover, the potential of the developed methodology for the detection of SCRAs in a consumer urine sample has also been demonstrated by identifying an O-demethylated SCRA metabolite not included in the database created. Funding sources This work was supported by Conselleria d’Educaci´ o, Universitats i Ocupaci´ o of the Generalitat Valenciana (CIAICO/2022/041) and Universitat Jaume I (UJI-B2022-04) CRediT authorship contribution statement María Mata-Pesquera: Writing – original draft, Visualization, Validation, Methodology, Investigation. David Fabregat-Safont: Writing – review & editing, Visualization, Validation, Methodology, Investigation, Conceptualization. Juan V. Sancho: Writing – review & editing, Supervision, Funding acquisition, Conceptualization. María Ib´ a˜ nez: Writing – review & editing, Writing – original draft, Validation, Supervision, Methodology, Investigation, Funding acquisition, Conceptualization. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Data availability Data will be made available on request. Acknowledgements Authors acknowledge Energy Control for providing the research chemicals used to prove the applicability of the developed methodology. D. Fabregat-Safont was supported by the Margarita Salas postdoctoral contract MGS/2021/15(UP2021–021) financed by the European UnionNextGenerationEU. M. Mata-Pesquera acknowledges Ministerio de Universidades in Spain for her predoctoral grant (FPU21/00120). Appendix A. 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