Using cheminformatics to predict cross reactivity of “designer drugs” to their currently available immunoassays

Abstract

BackgroundA challenge for drug of abuse testing is presented by ‘designer drugs’, compounds typically discovered by modifications of existing clinical drug classes such as amphetamines and cannabinoids. Drug of abuse screening immunoassays directed at amphetamine or methamphetamine only detect a small subset of designer amphetamine-like drugs, and those immunoassays designed for tetrahydrocannabinol metabolites generally do not cross-react with synthetic cannabinoids lacking the classic cannabinoid chemical backbone. This suggests complexity in understanding how to detect and identify whether a patient has taken a molecule of one class or another, impacting clinical care.MethodsCross-reactivity data from immunoassays specifically targeting designer amphetamine-like and synthetic cannabinoid drugs was collected from multiple published sources, and virtual chemical libraries for molecular similarity analysis were built. The virtual library for synthetic cannabinoid analysis contained a total of 169 structures, while the virtual library for amphetamine-type stimulants contained 288 compounds. Two-dimensional (2D) similarity for each test compound was compared to the target molecule of the immunoassay undergoing analysis.Results2D similarity differentiated between cross-reactive and non-cross-reactive compounds for immunoassays targeting mephedrone/methcathinone, 3,4-methylenedioxypyrovalerone, benzylpiperazine, mephentermine, and synthetic cannabinoids.ConclusionsIn this study, we applied 2D molecular similarity analysis to the designer amphetamine-type stimulants and synthetic cannabinoids. Similarity calculations can be used to more efficiently decide which drugs and metabolites should be tested in cross-reactivity studies, as well as to design experiments and potentially predict antigens that would lead to immunoassays with cross reactivity for a broader array of designer drugs.

Synthetic cannabinoid: prevalence, mechanisms of addiction development, mental disorders associated with the use of synthetic cannabinoid

“…[42]. Данная методика является одной из первых среди подобных на рынке лабораторной диагностики [43][44][45]. Существующие в настоящее время тесты для определения в моче СКБ типа JWH-018, JWH-019, JWH-073, JWH-250, AM -2201, показывают точность до 9 %, а чувствительность и специфичность составляют более 95% [44].…”

“…Другая существующая методика иммуноферментного анализа, позволяет типировать 27 разновидностей СКБ и 37 активных метаболитов последних, с точностью до %, а чувствительность и специфичность составляют 5% [45]. При разработке новых тестов для типирования СКБ предлагается учитывать перекрестные реакции между различного типа СКБ, и их метаболитами [43]. [47], внезапная остановка сердца [47], кома [75], профузное потоотделение, гипертермия [7 ].…”

Synthetische Cannabinoide: Verbreitung, Suchtbiologie & aktuelle Perspektive der persönlichen Gesundheitsgefährdung

“…In der Entwicklung neuer Tests können inzwischen durch chemo-informatorische Verfahren voraussichtliche Kreuzreaktivitäten berechnet werden, die bei der Identifizierung möglichst vieler SCBs bzw. ihrer Metaboliten hilfreich sein können[43].…”

Preparation of Translated, Scaled, and Rotated ATS Drugs 3D Molecular Structure for the Validation of 3D Moment Invariants-based Molecular Descriptors

“…Searching for relationships between molecular structures and complex properties can often be performed efficiently by using 3D descriptors, exploiting their large information content [27][28][29]. This paper believes that molecular similarity can also be used to detect the similarity between unknown compound and reference compounds, and consequently, can be used to detect new brand of ATS drugs to the known samples of ATS drugs based on their molecular structure [12,13,16].…”

“…Despite the apparent need of reliable methods to detect and identify ATS drugs in the field of forensic toxicology, the use of cheminformatics is only starting to be incorporated recently [12][13][14][15][16][17][18]. Cheminformatics researchers use molecular similarity to seek structurally similar compounds, since the drug design efforts are based on a principle which states that structurally similar compounds are more likely to exhibit comparable properties [19][20][21][22][23].…”