engleski

CorrelaCorrelation Studies between Computed Molecular Descriptors and Predicted ADMET Parameters in a Series of Pregnancy Category X Drugs

Unfavourable absorption, distribution, metabolism, elimination and toxic (ADMET) properties have been identified as a major cause of failure for candidate molecules in drug development and adverse drug reactions (ADRs) and are main reasons for withdrawal drugs from market. Consequently, there is an increasing interest in the early prediction of ADMET properties, with the objective of increasing the success rate of compounds reaching development [1, 2]. In this study we aimed to explore molecular features of selected pregnancy category X drugs [3], including retinol, retinal and retinoic acid [4], by correlation studies between computed molecular descriptors and predicted ADMET properties using MedChem StudioTM and ADMET PredictorTM 6.5 (Simulations Plus. Inc. USA). Molecular descriptors (a relative molecular mass, Mr ; a lipophilicity, MLogP ; a molar volume, V ; a total polar surface area, TPSA) were computed and correlated with predicted ADMET parameters: ADMET Risk, S + Absn Risk, CYP Risk, TOX Risk, TOX MUT Risk, TOX hERG, TOX Rat, TOX BRM Rat and TOX BRM Mouse. The study results revealed that investigated molecules are characterized with MLogP -1 to 6, TPSA 12.47 to 143.72, while eleven of them violated the Lipinski’s Rule–of-5. Figure 1. The relationship between MLogP and TOX hERG in a group of investigated X drugs 1 - 37. Figure 2. Relationships between computed ADMET Risk, TOX Risk and TOX MUT Risk of investigated X drugs [1 - retinoic acid, 2 – retinal, 3 – retinol, 4 – etretinate, 5 – tazarotene, 6 – misoprostol, 7 – leflunomide, 8 – methotrexate, 9 – estradiol, 10 – ethynyl estradiol, 11 – mestranol, 12 – estron sulfate, 13 – methyltestostron, 14 – fluoxymestranol, 15 – medroxyprogesterone, 16 – norgestrel, 17 – norethisterone, 18 – mifepristone, 19 – danazol, 20 – chenodiol, 21 – raloxifene, 22 – chlomiphene, 23 – dienestrol, 24 – diethylstilbestrol, 25 – simvastatin, 26 – lovastatin, 27 – parvastatin, 28 – fluvestatin, 29 – atorvastatin, 30 – ribavirin, 31 – quinine, 32 – methysergide, 33 – warfarin, 34 – flurazepam, 35 – temazepam, 36 – triazolam and 37 – thalidomide] The collinear relationships were obtained for Mr v.s. V (y = 1.090x + 6.247, r = 0.809), MLogP v.s. TPSA (y = -16.474 + 107.974, r = 0.708), MLogP v.s. Mr (y = - 21.354x + 128.567, r = 0.633), MLog P v.s. S + LogP (y = 1.243x – 0.210, r = 0.633). A two subgroups, one in cluster form and the other with high collinearities were revealed in correlations of MLogP v.s TOX hERG with r = 0.977 (y = 0.619x + 3.918, for 8, 21, 22, 30, 31, 34 and 37, Figure 1) and TPSA v.s. hERG, r = 0.912 (y = -0.016x + 7.024, for 4, 8, 21, 22, 29 and (34), respectively. For all retinoids included in this study, predicted ADMET Risk scores of 4, CYP Risk 0, TOX Risk 2, while TOX MUT Risk score 1 were predicted for retinol (3) and etretinate (4) (Figure 2). Keywords: X drugs, lipophilicity, ADMET Risk, TOX Risk, TOX MUT Risk, TOX hERG Acknowledgements: The support for this study was provided by the Ministry of Science, Education and Sports of the Republic of Croatia, Grant no. 006-0982929-2940. References: 1. Khakar, PS ; Two-dimensional (2D) in silico models for absorption, distribution, metabolism, excretion and toxicity (ADME/T) in drug discovery, Curr Top Med Chem, 10, 2010, 116-126 ; 2. Briggs, GG ; Freeman, RK ; Yaffe, SJ ; Drugs in Pregnancy and Lactation: A Reference Guide to Fetal and Neonatal Risk, 9th ed., Lippincott Williams & Wilkins Publishers, 2011 ; 3. Butina, D ; Segall, MD Frankcombe, K ; Predicting ADME properties in silico: methods and models, Drug Discov Today 7, 2002, S83-88 ; 4. Crnek-Kunstelj, V ; Ester, K ; Stipic, J ; Role of retinoic acid and DNA methylation in differentiation of mammalian embryo in vitro, Period Biol, 104, 2002, 55-66.

pregnancy category X drugs; retinoids; toxicity; teratogenicity; molecular descriptors; ADMET properties

Rad je objavljen i u Knjizi sazetaka ; Milena Jadrijević-Mladar Takač (ur.) ; str. 66-66 ; ISBN 978-953-7897-01-7.