MS-Based Molecular Networking of Designer Drugs as an Approach

Apr 16, 2019 - The NBOMe family is a group of new psychoactive substances (NPSs). In this study, the fragmentation patterns of NBOMe derivatives were ...
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Letter

MS based molecular networking of designer drugs as an approach for the detection of unknown derivatives for forensic and doping applications: a case of NBOMe derivatives Jun Sang Yu, Hyewon Seo, Gi Beom Kim, Jin Hong, and Hye Hyun Yoo Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.9b00294 • Publication Date (Web): 16 Apr 2019 Downloaded from http://pubs.acs.org on April 17, 2019

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

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Analytical Chemistry

MS based molecular networking of designer drugs as an approach for the detection of unknown derivatives for forensic and doping applications: a case of NBOMe derivatives

Jun Sang Yu†,a, Hyewon Seo‡,a, Gi Beom Kim†, Jin Hong‡, Hye Hyun Yoo†,*



Institute of Pharmaceutical Science and Technology and College of Pharmacy, Hanyang

University, Ansan, Gyeonggi-do, 15588, Republic of Korea. ‡

Pharmacological Research Division, Toxicological and Research Department, National

Institute of Food and Drug Safety Evaluation, Ministry of Food and Drug Safety, 28159, Republic of Korea.

* Corresponding Author. Hye Hyun Yoo; E-mail: [email protected]; Tel.: +82-31-400-5804; Fax: +82-31-4004783

a

Jun Sang Yu and Hyewon Seo equally contributed to this work.

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Abstract The NBOMe family is a group of new psychoactive substances (NPS). In this study, the fragmentation patterns of NBOMe derivatives were analyzed using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF/MS). The MS/MS spectral data was used to establish a molecular networking map for NBOMe derivatives. The fragmentation patterns of nine NBOMe derivatives were interpreted based on their product ion spectral data. NBOMe derivatives generally showed similar product ion spectral patterns; among them, the halogen-substituted methoxybenzyl ethanamine type derivatives showed a characteristic product ion of a radical cation. Molecular network analysis of the MS/MS data revealed that all NBOMe derivatives formed one integrated networking cluster that discriminated them from other types of NPS. NBOMe derivatives were spiked into human urine and identified by connection to the NBOMe database network. Furthermore, the NBOMe compounds that were not registered in the database were also recognized as an NBOMe-related substance by molecular networking. These results demonstrate the potential of using molecular networking-based screening methods for designer drugs and the proposed method would be useful in forensic or doping analysis.

Keywords: NBOMe, new psychoactive substances, fragmentation patterns, molecular networking, open screening

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Analytical Chemistry

Introduction The NBOMe family is a group of hallucinogenic new psychoactive substances (NPS) that mimics lysergic acid diethylamide. These are potent chemicals that act as full agonists for the human 5-HT2A receptor.1-7 The most common member of this family is 25I-NBOMe, which was discovered in 2003 and first synthesized in 2010. Since then, a number of derivatives have been synthesized.1,6,8-10 These NBOMe compounds are regulated as controlled substances in many countries, but new derivatives are continuously emerging to avoid the legal regulations imposed on other NPS. Illegal substances are typically detected or quantified using targeted analytical methods that are mainly based on mass spectrometry. New NPS are continuously being synthesized, so forensic analysts need detection methods for these newly emerging substances. However, these so-called ‘designer drugs,’ can be overlooked by targeted methods that focus on known substances. Accordingly, a need exists for generally applicable non-targeted screening methods. Many papers have reported screening methods for detecting illegal or doping substances based on mass spectrometry.11-13 Some studies have employed infrared spectroscopy combined with statistical tools11 however, most of the existing methods are designed to detect specific target substances. For example, one published paper by Polet et al. demonstrated a generally applicable method that uses liquid chromatography-electrospraytandem mass spectrometry that can comprehensively detect anabolic steroids, including unknown anabolic steroids.12 They determined the common fragment ions generated from steroid structures and proposed a detection method using precursor ion scanning. Tandem mass spectrometry with precursor ion scanning can therefore be useful for the screening of classes of substances with common fragment ions. Alternatively, substances that show common neutral loss during collision energy induced dissociation (CID) can be 3

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screened by neutral loss scanning.14 However, some designer drugs, including NBOMe derivatives, may not show either common fragment ions or common neutral loss due to their substituents, even though fragmentation occurs according to a certain pattern under CID in the tandem mass spectrometer. These aspects restrict the application of precursor ion scanning or neutral loss scanning for universal screening. In the present study, we propose a novel approach for detecting unknown designer drugs by adopting molecular networking analysis. Molecular networking is an approach that organizes tandem mass spectrometry (MS/MS) data by mining MS/MS fragmentation similarity. It was first introduced in the field of natural products analysis and is now extensively applied for various purposes, including drug discovery and metabolomics studies.15-27 Molecular networking determines the MS/MS structural similarity by calculating the cosine scores for the vectors generated from an m/z value and the respective intensity of the product ions. Consequently, structurally related compounds may network with each other even though they do not have common fragment ions or neutral loss. Therefore, even unknown but structurally related substances can be recognized by molecular networking based on MS/MS spectral data of existing molecules. In this context, molecular networking could be a powerful and efficient tool for the detection of designer drugs in the forensic field. In this study, the fragmentation patterns of NBOMe derivatives were characterized using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF/MS) analysis. The resulting MS/MS spectral data was used to establish a molecular networking map for NBOMe derivatives and used NBOMe derivatives as model substances to demonstrate a screening method for designer drugs based on molecular networking.

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Analytical Chemistry

Results and discussion MS/MS analysis of NBOMe derivatives using QTOF MS We analyzed 9 NBOMe derivatives using LC-QTOF/MS. The fragmentation pattern of each NBOMe species was interpreted based on the product ion spectral data. The MS2 spectra of the protonated NBOMe derivatives and the proposed fragmentation pathways are depicted in Figure 1. Accurate mass information for the product ion spectra is provided in the Supporting Information section (Table S3) The protonated molecular ions for 25H-NBOMe, 25B-NBOMe, 25E-NBOMe, and 25NNBOMe were observed at m/z 302.1751 (C18H23NO3), 380.0856 (C18H22BrNO3), 330.2064 (C20H27NO3), and 347.1601 (C18H22N2O5), respectively (Figure 1A-1D). They yielded common major product ions at m/z 121.0653 (C8H9O) and 91.0548 (C7H7) in MS2 analysis. The MS2 product ion at m/z 121.0653 was assigned as product ion corresponding to the 1methoxy-2-methylbenzene ring moiety generated by the C-N bond cleavage and the product ion at m/z 91.0551 was generated by the loss of the methoxy from the 1-methoxy-2methylbenzene ring. 25E-NBOMe yielded additional product ion at m/z 193.1229 (C12H17O3), which was assigned as a product ion corresponding to the 1,4-diethyl-2,5-dimethoxybenzene ring moiety generated by the C-N bond cleavage. The protonated molecular ions for 25C-NBOH and 25I-NBOH were observed at m/z 322.1204 (C17H20ClNO3) and 414.0561 (C17H20INO3), respectively (Figure 1E and 1F). Their major product ions were generated by the C-N bond cleavage; 25C-NBOH yielded product ions at m/z 107.0497 (C7H7O) and 199.0526 (C10H12ClO2) and 25I-NBOH yielded product ions at m/z 107.0497 (C7H7O) and m/z 290.9902 (C10H12IO2). The protonated molecular ions for 25B-NBF, 25C-NBF, and 25I-NBF were observed at m/z 368.0656 (C17H19BrFNO2), 324.1161 (C17H19ClFNO2), and 416.0517 (C17H19FINO2), 5

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respectively (Figure 1G–1I). Their fragmentation pattern was similar to those of 25C-NBOH and 25I-NBOH. The major fragment ions were produced via the C-N bond cleavage. x10 6

x10 5

A

O

121.0659

1

H N

121

0.9

91

0.8

H N

121

8

121

91

O

Br

7

O

C

H N

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O

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O

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121

193

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0 100 150 200 250 300 350 400 450 Counts vs. Mass-to-Charge (m/z)

121.0657

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O

3.5

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121 O

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O

N O

5

91

O

100 150 200 250 300 350 400 450 Counts vs. Mass-to-Charge (m/z)

107.0503

199.0536 199

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184 199 216

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291 OH

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276

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308

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2 91

1

308

1 184

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347.1617

225.0898

216

322.1212

100 150 200 250 300 350 400 450 Counts vs. Mass-to-Charge (m/z)

G

4.5

O H N

164

4 3.5 243

3

228

100 150 200 250 300 350 400 450 Counts vs. Mass-to-Charge (m/z)

H

199

4 109

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184

6 F

Cl

3.5

109

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2.5

109

1

228

370.0668

164

0.5

109.0462

1.5

109.0460

0 100 150 200 250 300 350 400 450 Counts vs. Mass-to-Charge (m/z)

4

290.9905

H N

291 F

I

276

109

O

291

184

2

109

1

324.1190

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0.5

276

109.0463

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0 50

O

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5

100 150 200 250 300 350 400 450 Counts vs. Mass-to-Charge (m/z)

I

O

199

3

243

H N

164

50 x10 5

O

199.0538

4.5 F

Br

0 50

x10 5 245.0017

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164

0 50

414.0588

164.0842

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164

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290.9902

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164

3

O

100 150 200 250 300 350 400 450 Counts vs. Mass-to-Charge (m/z)

F

4 OH

Cl

2

3

50 x10 5

E

2.5

121

4

330.2077

193

0 50

x10 5

D

193.1232

91

0.2

382.0857

245.0014

0 50

x10 5

O

121.0660

1.2 1

O

6

0.5

x10 5

x10 6 O

121.0656

9 O

0.7 0.6

B

416.0549

164

0 50

100 150 200 250 300 350 400 450 Counts vs. Mass-to-Charge (m/z)

50

100 150 200 250 300 350 400 450 Counts vs. Mass-to-Charge (m/z)

Figure 1. Representative product ion spectra of the nine NBOMe derivatives. A, 25HNBOMe; B, 25B-NBOMe; C, 25E-NBOMe; D, 25N-NBOMe; E, 25C-NBOH; F, 25I-NBOH; G, 25B-NBF; H, 25C-NBF; I, 25I-NBF. The product ion spectra were measured at 20 eV (CE).

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Analytical Chemistry

Formation of radical cation fragment ions from halogen-substituted NBOMe derivatives Interestingly, among the NBOMe derivatives, halogen-substituted derivatives (25B-NBF, 25C-NBF, 25C-NBOH, 25I-NBF, and 25I-NBOH) showed unusual fragment ions in the CID spectra. These ions have common features, as they are fragment ions with a halogensubstituted benzyl moiety. The product ions corresponding to the theoretically expected structure (i.e., a protonated cation) were not detected; instead, the product ions corresponded to the structure lacking one hydrogen atom. In halogenated aromatic compounds, losses of halogen substituents are common as radicals (X∙) or HX.28,29 However, these fragment ions still have a halogen substituent. The ChemDraw estimation indicated the radical cation of the halogen-substituted benzene moiety, which was further confirmed by its isotopic ions (Table S3). In addition, the product ion of m/z 164 was commonly detected in the five halogensubstituted derivatives mentioned above. This fragment ion was also estimated to be a radical cation which is produced by the loss of a halogen substituent. The postulated chemical structures of the radical cationic fragment ions are presented in Figure S1-A. Formation of a radical cation is a common phenomenon observed in GC-MS that utilizes electron impact ionization (EI) source.30,31 Factors that can lead to generation of radical cations in EI include certain structural properties: the presence of pi-bonds, such as in alkenes, aldehydes, and ketones, and the presence of heteroatoms or electrons that tend to fall away from the nucleus.31 This phenomenon is rare but also found in the electrospray ionization (ESI) source. Thus, some compounds (even-electron ions) can produce radical cations (oddelectron ions) by homolytic cleavage under CID conditions in the ESI source. The formation of radical fragment ions depends on the charge and radical sites.32 According to Hiserodt et al., doubly allylic alkenamides fragmented to yield distonic radical cations by low energy collisional activation in a triple quadrupole mass spectrometer with ESI.33 The authors 7

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proposed a mechanism whereby these radical cations are formed by charge-remote homolytic cleavage, which can be stabilized by resonance structures. In addition, radical fragment ions (as radical cations or anions) are observed in the MS/MS spectra of flavonoids, which are generated by the elimination of ∙ CH3 from the methoxy phenyl moiety.32 In this context, the halogen-substituted NBOMe derivatives have a halogen-substituted benzyl moiety, which may satisfy the condition that is favorable to yield radical cations as these derivatives have conjugated pi bonds as well as halogen atoms with unshared electron pairs. Thus, the halogen-substituted NBOMe derivatives may easily fragment into a radical cation during CID, and this cation could be stabilized by resonance occurring over the parahalogen-substituted benzyl moiety. Meanwhile, 25B-NBOMe is also a halogenated derivative but did not present a radical cation fragment ion (Figure 1B). Such fragment pattern appeared generally constant at different collision energies (10~50 eV) (data not shown). It may be because 25B-NBOMe has a methoxybenzyl ethanamine moiety. This difference will be further discussed in the following section on molecular networking. The proposed mechanism for the generation of a radical cation in the CID spectrum of 25C-NBOH is depicted in Figure S1-B. The predominant fragment ions (m/z 107.0497 and m/z 199.0526) observed at a CE of 20 are generated by the cleavage of the C-N in the right and left sides of the amine group (Figure 1E). Among these fragment ions, the product ion at m/z 199.0526 undergoes a hydrogen shift and fragmentation to yield distonic radical cations. The radical cation is predominately generated via O-demethylation and some are generated by dehalogenation. The O-demethylation radical cation may further fragment by losing a methyl group. The energy-resolved mass spectrometric data explains more about the characteristics of the radical cationic fragment ions. As shown in Figure S2, the intensity of the 8

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Analytical Chemistry

ethyldimethoxyphenyl cations peaked at 20 eV and thereafter decreased (Figure S2-A), while the intensity of the O-demethylated radical cationic fragment ions increased up to 30–40 eV and then decreased (Figure S2-B). Subsequently, the cyclohexadienedione cation increased after 30 eV (Figure S2-C). These plots reveal the fragment ions were formed via consecutive fragmentation pathway. Meanwhile, the intensity of the dehalogenated radical cationic fragment ions increased up to 30 eV or 40 eV and then decreased (Figure S2-D). The formation of dehalogenated radical cations are not the major fragment pathway but seemed to be competitive with the O-demethylated radical cation formation.

MS/MS molecular network analysis Generally, a series of compounds that share a structural backbone exhibit a common and characteristic MS/MS fragmentation pattern in the CID spectra due to their structural similarity. Most illegal substances can be categorized according to their structural characteristics. Therefore, interpretation and organization of their fragmentation data using bioinformatics may allow rapid identification of their structures and assign a class. This can still be used for newly emerging designer drugs, as long as their chemical structures are related to existing drugs. Recently, the molecular networking approach has been extensively utilized as an effective tool to organize MS/MS spectral data. Accordingly, the molecular network analysis was performed based on the MS/MS data of nine NBOMe derivatives. The resulting MS/MS molecular networks for the nine NBOMe derivatives are shown in Figure 2. Initially, the cosine cut-off was set for molecular networking at 0.5, and the nine NBOMe derivatives formed two clusters on the networking map: the groups with and without a methoxybenzyl ethanamine moiety (data not shown). When the cosine threshold value was adjusted downward to 0.3, all NBOMe derivatives formed one integrated network. Generally, 9

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a cosine value is set at greater than 0.5 to obtain interpretable data for similarity17. Therefore, the significance of the networking formed among NBOMe derivatives was validated with a cosine cut-off at 0.3 by reanalyzing the dataset composed of the MS/MS data of other types of NPS along with nine NBOMe derivatives. The added NPS were the cathinone derivatives including cathinone, ephedrine, pseudoephedrine, methcathinone, MDPV, MDPPP, fluoroephedrine, α-PPP, α-PBP, 5-IAI, 4-EMC, 4-MMC, and 3,4-DMMC. The analysis showed that the cathinone derivatives were not connected to the NBOMe cluster, indicating that MS networking with a cosine cut-off at 0.3 is still effective for discriminating between NBOMes and other types of drugs. However, if we categorize the NBOMes into two subtypes (methoxybenzyl ethanamine and non-methoxybenzyl ethanamine types), their networking can be identified more clearly in complex matrix samples by upward adjustment of the cosine threshold. Meanwhile, the cathinone derivatives also formed their own molecular networking cluster. The cathinone derivatives were all connected except for 5-IAI that has a distinctly different chemical structure compared to other cathinone derivatives. Ephedrine and pseudoephedrine were recognized as the same node because they are optical isomers. 4-EMC and 3,4-DMMC were also indicated as the same node since they are structural isomers with the same precursor and product ions. These findings demonstrate that molecular networking can be a useful tool to screen and categorize different classes of NPS.

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Analytical Chemistry

NBOMe derivatives Cathinone derivatives

O H N O H N

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Figure 2. Molecular networks for NBOMe and cathinone derivatives. The molecular networking map was generated from the whole dataset composed of 9 NBOMe and 13 cathinone derivative. C, cathinone; E, ephedrine; PE, pseudoephedrine; MC, methcathinone, FE, fluoroephedrine. The molecular network can be visualized directly on GNPS via the following

link

https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=db99d5742d774b97a396286e070b1662.

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MS networking-based NPS screening system Spiked urine samples were tested to evaluate the feasibility of using this molecular networking based method as a screening system for detecting unknown NPS. The MS/MS database for molecular networking was constructed using the MS/MS spectral data of seven selected NBOMe derivatives (25H-NBOMe, 25B-NBOMe, 25N-NBOMe, 25B-NBF, 25CNBF, 25C-NBOH, and 25I-NBOH) prior to analyzing the spiked urine samples, which contained 9 NBOMes; two substances (25E-NBOMe, 25I-NBF) were assumed as unknowns. A generally used screening system was simulated: a simple linear gradient elution with mobile phases consisting of water and acetonitrile was used for chromatographic separation and the auto MS/MS mode was used for mass detection. The resulting spectral data were then subjected to molecular network analysis. The spiked nine NBOMe derivatives were all recognized on the molecular network map (Figure 3). Among them, the seven NBOMe were identified by their matches with the nodes of the database. The other two compounds (as unknowns) were recognized by connection to the nodes of the database. The networking cluster was sufficiently well generated to be recognizable at a concentration of 1 μg/mL. Meanwhile, some nodes which are not connected to the NBOMe cluster were observed. These are considered to result from endogenous molecules in human urine. They were obviously separated and differentiated from NBOMe derivatives. These results confirmed the potential of the molecular network-based screening system with biological samples. Thus, if an MS/MS database for illegal or prohibited substances is established, even unknown designer drugs can be readily recognized by connection to the network of the database. This approach would enable the rapid detection and identification of unknown NPS.

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Analytical Chemistry

Recently, Pozo et al. proposed an open screening method for doping substances using gas chromatography quadrupole time of flight mass spectrometry.13 The authors emphasized the advantage of high resolution mass spectrometry-based screening method in terms of retrospectivity and compatibility with libraries. Nevertheless, this method cannot detect unknown substances in the initial screening unless the substances are registered in the library, although retrospective data analysis could be performed to search for unknown designer drugs. However, our proposed method can detect the presence of unknown drugs in the initial screening through molecular networking and can readily conduct a structural identification of unknowns. Furthermore, the information provided on the relevant molecular network would shorten the time required to identify unknown substances.

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NBOMe database set NBOMe spiked human urine Unknown(25I-NBF)

Unknown(25E-NBOMe) 25C-NBF

25B-NBF

25N-NBOMe 25I-NBOH

25B-NBOMe 25H-NBOMe

25C-NBOH

Figure 3. Molecular networks for the nine NBOMes in human urine. 25E-NBOMe and 25INBF were assumed unknown. The node size is arbitrary and the thickness of the edge between nodes is proportional to the cosine score. The molecular network can be visualized directly

on

GNPS

via

the

following

https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=1a3f713259004f2396cd75fa1dbd16a0.

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Analytical Chemistry

Conclusions In this study, the MS/MS fragmentation profiles and molecular networking of NBOMe derivatives were investigated using LC-QTOF MS. A series of NBOMes generally showed a similar fragmentation behavior; however, no common fragment ions or common neutral loss were shown. This limited universal screening for NBOMes by adopting precursor ion or neutral loss scanning. The use of molecular network analysis resulted in recognition of all NBOMe derivatives as one integrated network. The NBOMes were successfully identified in urine samples by molecular networking with a pre-established NBOMe MS/MS database. These results suggest that molecular networking-based screening methods could be promising tools for open screening of designer drugs for forensic or doping analysis.

Supporting Information Experimental section, accurate mass data for the product ions of NBOMe derivatives, proposed mechanism for the formation of the radical cationic fragment ion, energy-resolved mass spectrometric data

Conflicts of interest The authors declare that they have no conflict of interest.

Acknowledgments The authors thank Prof. Hyukjae Choi for the helpful advice on molecular network analysis. This work was supported the National Research Foundation of Korea [2017R1A2B4001814].

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D.; Watrous, J.; Kapono, C. A.; Luzzatto-Knaan, T.; Porto, C.; Bouslimani, A.; Melnik, A. V.; Meehan, M. J.; Liu, W. T.; Crusemann, M.; Boudreau, P. D.; Esquenazi, E.; SandovalCalderon, M.; Kersten, R. D., et al. Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking. Nat Biotechnol 2016, 34, 828-837. (17) Watrous, J.; Roach, P.; Alexandrov, T.; Heath, B. S.; Yang, J. Y.; Kersten, R. D.; van der Voort, M.; Pogliano, K.; Gross, H.; Raaijmakers, J. M.; Moore, B. S.; Laskin, J.; Bandeira, N.; Dorrestein, P. C. Mass spectral molecular networking of living microbial colonies. Proc Natl Acad Sci U S A 2012, 109, E1743-1752. (18) Olivon, F.; Roussi, F.; Litaudon, M.; Touboul, D. Optimized experimental workflow for tandem mass spectrometry molecular networking in metabolomics. Anal Bioanal Chem 2017, 409, 5767-5778. (19) Terrell, J. L.; Payne, G. F.; Bentley, W. E. Networking biofabricated systems through molecular communication. Nanomedicine (Lond) 2016, 11, 1503-1506. (20) Ding, C. Y. G.; Pang, L. M.; Liang, Z. X.; Goh, K. K. K.; Glukhov, E.; Gerwick, W. H.; Tan, L. T. MS/MS-Based Molecular Networking Approach for the Detection of Aplysiatoxin-Related Compounds in Environmental Marine Cyanobacteria. Mar Drugs 2018, 16. (21) Oppong-Danquah, E.; Parrot, D.; Blumel, M.; Labes, A.; Tasdemir, D. Molecular Networking-Based Metabolome and Bioactivity Analyses of Marine-Adapted Fungi Cocultivated With Phytopathogens. Front Microbiol 2018, 9, 2072. (22) Quinn, R. A.; Nothias, L. F.; Vining, O.; Meehan, M.; Esquenazi, E.; Dorrestein, P. C. Molecular Networking As a Drug Discovery, Drug Metabolism, and Precision Medicine Strategy. Trends Pharmacol Sci 2017, 38, 143-154. 18

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(23) Beste, M. T.; Pfaffle-Doyle, N.; Prentice, E. A.; Morris, S. N.; Lauffenburger, D. A.; Isaacson, K. B.; Griffith, L. G. Molecular network analysis of endometriosis reveals a role for c-Jun-regulated macrophage activation. Sci Transl Med 2014, 6, 222ra216. (24) Boya, P. C.; Fernandez-Marin, H.; Mejia, L. C.; Spadafora, C.; Dorrestein, P. C.; Gutierrez, M. Imaging mass spectrometry and MS/MS molecular networking reveals chemical interactions among cuticular bacteria and pathogenic fungi associated with fungusgrowing ants. Sci Rep 2017, 7, 5604. (25) Nothias, L. F.; Nothias-Esposito, M.; da Silva, R.; Wang, M.; Protsyuk, I.; Zhang, Z.; Sarvepalli, A.; Leyssen, P.; Touboul, D.; Costa, J.; Paolini, J.; Alexandrov, T.; Litaudon, M.; Dorrestein, P. C. Bioactivity-Based Molecular Networking for the Discovery of Drug Leads in Natural Product Bioassay-Guided Fractionation. J Nat Prod 2018, 81, 758-767. (26) Reher, R.; Kuschak, M.; Heycke, N.; Annala, S.; Kehraus, S.; Dai, H. F.; Muller, C. E.; Kostenis, E.; Konig, G. M.; Crusemann, M. Applying Molecular Networking for the Detection of Natural Sources and Analogues of the Selective Gq Protein Inhibitor FR900359. J Nat Prod 2018, 81, 1628-1635. (27) Allard, S.; Allard, P. M.; Morel, I.; Gicquel, T. Application of a molecular networking approach for clinical and forensic toxicology exemplified in three cases involving 3-MeOPCP, doxylamine, and chlormequat. Drug Test Anal 2018. doi: 10.1002/dta.2550. [Epub ahead of print] (28) de Vlieger, J. S.; Giezen, M. J.; Falck, D.; Tump, C.; van Heuveln, F.; Giera, M.; Kool, J.; Lingeman, H.; Wieling, J.; Honing, M.; Irth, H.; Niessen, W. M. High temperature liquid chromatography hyphenated with ESI-MS and ICP-MS detection for the structural characterization and quantification of halogen containing drug metabolites. Anal Chim Acta 2011, 698, 69-76. 19

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?

25N-NBOMe

Unknown

25B-NBF

25I-NBOH

Unknown

?

25B-NBOMe

25C-NBOH

25C-NBF

25H-NBOMe

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