Naslov
Estimating the Toxic Potential of Entactogens – In silico Study

Autori
Jadrijević-Mladar Takač, Milena ; Takač, Tin

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, prošireni sažetak, znanstveni

Izvornik
International Conference on Advances in Pharmaceutical Drug Development, Quality Control and Regulatory Sciences, Acta Pharmaceutica Hungarica, APH 91: 85348 (2021) / Klebovich, Imre ; Janaky, Tamas - Budimpešta : Hungarian Society for Pharmaceutical Sciences, 2021, 240-242

Skup
International Conference on Advances in Pharmaceutical Drug Development, Quality Control and Regulatory Science (DDRS 2021)

Mjesto i datum
Budimpešta, Mađarska, 15.11.2021. - 17.11.2021

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Entactogens, ADMET, Toxicity, QSAR, Membrane transporters

Sažetak
1. Introduction Ecstasy (MDMA) and its structural analogs are capable of inducing an ”entactogenic syndrome”, a reversible controlled alteration of consciousness in humans characterized by emotional relaxation, feelings of happiness, and empathy. This makes MDMA the most popular recreational drug with a high potential for abuse. Recently there has been increasing evidence that MDMA may be used in MDMA-assisted psychotherapy to treat post-traumatic stress disorder (PTSD), autism anxiety, alcoholism, and mood disorders. There is a widespread belief among adolescents and younger adults that ecstasy is a safe drug. However, the “street drugs” that are very commonly sold under this name can vary widely in purity and often contain adulterants or undeclared entactogens with unknown properties. (1‒4) Entactogens (Figure 1) and reference molecules, the antidepressants paroxetine (SSRI) and venflaxine (SNRI), were studied for their toxic potential and affinity for drug-drug interactions (DDI) via membrane transporters. 2. Materials and methods Entactogens (1‒25) and references paroxetine and venflaxine were evaluated using ADMET PredictorTM software package (SimulationsPlus Inc., USA, www.simulations-plus.com) and the MetaTox web application (http://way2drug.com/mg). 3. Results For the studied entactogens (Figure 1), the calculated MlogP ranged from 0.839 to 2.977 and of paroxetine 2.561. ADMET_Risk was calculated in the range from 0.000 (DiFMDA, R1=R2=R4=R5=H ; R3=CH3, R6= R7=F) to MlogP 3.505 (MDBU, R1= CH2CH2CH2CH3, R3=CH3, R2=R4=R5=R6=R7=H). The main ADMET risks were related to CYP metabolism (CYP1A2, 2C19 and 2D6), volume of distribution (Vd) and mutagenicity (MUT) (Table 1). Lipophilicity (MlogP) was the only physicochemical parameter linearly correlated with cardiotoxicity expressed as hERG_pIC50 (mol/L), although TOX_hERG was not predicted to be TOX_risk by ADMET PredictorTM (Figure 2). A linear correlation was also observed between MlogP and oral toxicity LD50 (mg/mL) predicted by MetaTox software (Figure 3). The toxicity between entactogens and their most toxic metabolites is shown in Figure 4. Toxicity analysis by the MetaTOX web application revealed the following main side effects: Hepatotoxicity‒ MDA (1), MDMA (2), MDDM (3), MDEA (4), MDPR (5), MDBU (6), MDIP (7), MDPL (9), MDBZ (11), MDOH (12), MDMEO (14), Ethyl-K (18), MMDA-2 (21), 2, 3-MDA (25) and venlafaxine (26) ; Cardiac arrhythmia ‒ paroxetine ; Heart failure ‒ MDHOET (13) and MDMOET (15) ; Myocardial infarction and heart failure ‒ DiFMDA (23) ; No predicted side effect ‒ MDAL (8), MDCPM (10), BDB (16), MBDB (17), 5-MeMDA (19), MMDA (20), MMDPEA (22) and EIDA (24). Membrane transporters (MT) can significantly affect the pharmacodynamics (PK) and pharmacokinetics (PD) of drugs, contributing to drugdrug interactions that very often lead to side effects or even serious toxic effects. The study of affinity to membrane transporters of entactogens and references paroxetine and venflaxine by ADMET PredictorTM revealed that they interact via transporters Pgp (P-glycoprotein, ABCB1), OCT1 and OCT2 (organic cation transporter 1 and 2), OAT3 (organic anion transporter 3), and BCRP (breast cancer resistance protein) as substrates, while the affinity of inhibitors was predicted mainly for OCT1 and OCT2. Substrates of Pgp (MDPL, MDHOET, MMDPEA and paroxetine) ; OCT1 (MDA, MDDM, MDOH, MDMEO, BDB, 5-Me-MDA, MMDA, MMDA-2, MMDPEA, DiFMDA, EIDA and 2, 3-MDA) ; OCT2 (all except DiFMDA, paroxetine and venflaxine) ; OATP1B1 (MDDM) ; OAT3 (MDOH and MDMEO) ; OAT2 (MDPL) ; BCRP (DiFMDA and venflaxine) ; Inhibitors ‒ Pgp (venflaxine) ; OCT1 (MDDM, MDEA, MDPR, MDBU, MDIP, MDAL, MDPL, MDCPM, MDBZ, MBDB, Ethyl-K, 5-Me-MDA, venflaxine ) ; OCT2 (the same as for OCT1 except MDMEOET, 5-Me-MDA, plus paroxetine) ; OAT3 (MDMEO). Table 1 Predicted ADMET codes for entactogens:1A2, 2C19 or 2D6 – excessive clearance by CYP 1A2, 2C19 or 2D6, respectively ; Vd ‒ volume of distribution ; MUT ‒ mutagenicity 1A2 MDA, MDDM, MDOH, EIDA, 2, 3-MDA 1A2, 2C19 MDMA, MDHOET, 5-MeMDA, MMDA, MMDPEA 1A2, 2C19, 2D6 MDBZ, MDMOET, BDB, MBDB ; Vd, 1A2, 2C19, 2D6 MDEA, MDPR, MDBU, MDIP, MDAL, MDCPM, paroxetine MUT, 1A2, 2C19 MDMEO Vd, MUT, 1A2, 2C19, 2D6 MDPL Figure 1 Entactogens’ general formula and structure of paroxetine. R1 = H or CH3 ; R2 = H, CH3, CH2CH3, CH2CH2CH3, CH2CH2CH2CH3, CH2(CH3)CH3, CH2CH=CH2, CH2C≡CH, CH2C3H5, CH2C6H5, OH, CH2CH2OH, OCH3 or CH2CH2OCH3 ; R3 = H, CH3, CH2CH3 or CH2CH2CH3 ; R4 = H or OCH3, R5 = H, CH3, or OCH3 ; R6 = H, F or CH3 ; R7 = H or F. Figure 2 Relationship between MlogP and TOX_hERG, the affinity for the hERG potassium channel calculated for entactogens and references by ADMET PredictorTM Figure 3 Figure 3 Relationship between MlogP and oral toxicities (LD50 in mg/kg) of entactogens and paroxetine calculated by the MetaTox Figure 4 Relationship between toxicity, calculated by MetaTox for entactogens and their most toxic metabolites primarily catalyzed by CYP enzymes and references paroxetine and venflaxine 4. Conclusions There are limited data on the potential toxicity of many of the entactogens abused today. Therefore, the results of this in silico study provide useful information on their potential toxic effects as well as their potential for drug-drug-interactions (DDI). QSAR analysis revealed a high linear correlation between MlogP and toxicity parameters (hERG_pIC50 in mol/L, and oral toxicity LD50 in mg/kg), and this finding may be useful in predicting these properties for the new entactogens. Misuse of entactogens in parallel with usual drug therapy may affect the therapeutic outcome due to their affinity for the same membrane transporters. 5. Acknowledgements We are thankful to the University of Zagreb for the financial support to this project. References 1. Sessa, B., Higbed, L., Nutt, D., A Review of 3, 4-methylenedioxymethamphetamine (MDMA) assisted psychotherapy. Front. Psychiatry, 10:138 (2019). 2. Parrott, A. C., Downey, L. A., Roberts, C. A., Montgomery, C., Bruno, R., Fox, H. C., Recreational 3, 4-methylenedioxymethamphetamine or ’ecstasy’: current perspective and future research prospects, J. Psychopharmacol., 31: 959-966 (2017). 3. Kalant, H., The pharmacology and toxicology of "ecstasy" (MDMA) and related drugs, CMAJ, 165: 917-928 (2001). 4. Jadrijevic-Mladar Takac, M., Magina, J. D. C., Takac, T., Evaluation of phenylethylamine type entactogens and their metabolites relevant to ecotoxicology – a QSAR study, Acta Pharm. 69: 563–584 (2019).

Izvorni jezik
Engleski

Znanstvena područja
Farmacija

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