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Computational Assessment of Pharmacokinetics and Biological Effects of Some Anabolic and Androgen Steroids

  • Research Paper
  • 6th World Conference on Physico-Chemical Methods in Drug Discovery and Development & 3rd World Conference on ADMET and DMPK
  • Published:
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Abstract

Purpose

The aim of this study is to use computational approaches to predict the ADME-Tox profiles, pharmacokinetics, molecular targets, biological activity spectra and side/toxic effects of 31 anabolic and androgen steroids in humans.

Methods

The following computational tools are used: (i) FAFDrugs4, SwissADME and admetSARfor obtaining the ADME-Tox profiles and for predicting pharmacokinetics;(ii) SwissTargetPrediction and PASS online for predicting the molecular targets and biological activities; (iii) PASS online, Toxtree, admetSAR and Endocrine Disruptomefor envisaging the specific toxicities; (iv) SwissDock to assess the interactions of investigated steroids with cytochromes involved in drugs metabolism.

Results

Investigated steroids usually reveal a high gastrointestinal absorption and a good oral bioavailability, may inhibit someof the human cytochromes involved in the metabolism of xenobiotics (CYP2C9 being the most affected) and reflect a good capacity for skin penetration. There are predicted numerous side effects of investigated steroids in humans: genotoxic carcinogenicity, hepatotoxicity, cardiovascular, hematotoxic and genitourinary effects, dermal irritations, endocrine disruption and reproductive dysfunction.

Conclusions

These results are important to be known as an occupational exposure to anabolic and androgenic steroids at workplaces may occur and because there also is a deliberate human exposure to steroids for their performance enhancement and anti-aging properties.

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Abbreviations

AAS:

Anabolic androgen steroids

ADME-Tox:

Absorption, Distribution, Metabolization, Excretion and Toxicity

AR:

Agonistic conformation of the androgenic receptor

AR an :

Antagonistic conformation of the androgenic receptor

BBBP:

Blood brain barrier permeant

ER α :

Agonistic conformation of the estrogen receptor alpha

ER α an:

Antagonistic conformation of the estrogen receptor

ER β:

Estrogen receptor beta

ER β an :

Antagonistic conformation of the sstrogen receptor beta

FDA:

Food and drug administration

GI:

Gastrointestinal absorption

GR:

Agonistic conformation of the glucocorticoid receptor

GR an :

Antagonistic conformation of the glucocorticoid receptor

hARLBD:

Human androgen receptor ligand-binding domain

HSDB:

Hazardous substances data bank

IUPAC:

International union of pure and applied chemistry

LRX β:

Liver X receptor beta

LXR α:

Liver X receptor alpha

PASS:

Prediction of activity spectra of substances

PDB:

Protein data bank

P-gp:

P-glycoprotein

PPRA α:

Peroxisome proliferator activated receptor alpha

PPRA β:

Peroxisome proliferator activated receptor beta

PPRA γ:

Peroxisome proliferator activated receptor gamma

QSAR:

Quantitative structure-activity relationship

RXR α :

Retinoid X receptor alpha

TR α:

Thyroid receptor alpha

TR β:

Thyroid receptor beta

References

  1. Geyer H, Schänzer W, Thevis M. Anabolic agents: recent strategies for their detection and protection from inadvertent doping. Br J Sports Med. 2014;48(10):820–6.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Hall RC, Hall RC. Abuse of supraphysiologic doses of anabolic steroids. South Med J. 2005;98(5):550–5.

    Article  PubMed  Google Scholar 

  3. van Amsterdam J, Opperhuizen A, Hartgens F. Adverse health effects of anabolic-androgenic steroids. RegulToxicolPharmacol. 2010;57(1):117–23.

    Google Scholar 

  4. Kicman AT, Gower DB. Anabolic steroids in sport: biochemical, clinical and analytical perspectives. Ann ClinBiochem. 2003;40(4):321–56.

    CAS  Google Scholar 

  5. Cohen J, Collins R, Darkes J, Gwartney D. A league of their own: demographics, motivations and patterns of use of 1,955 male adult non-medical anabolic steroid users in the United States. J Int Soc Sports Nutr. 2007;4:12–2.

  6. Maravelias C, Dona A, Stefanidou M, Spiliopoulou C. Adverse effects of anabolic steroids in athletes. A Constant ThreatToxicol Lett. 2005;158(3):167–75.

    CAS  Google Scholar 

  7. Kicman AT. Pharmacology of anabolic steroids. Br J Pharmacol. 2008;154(3):502–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Lippi G, Franchini M, Banfi G. Biochemistry and physiology of anabolic androgenic steroids doping. Mini Rev Med Chem. 2011;11(5):362–73.

    Article  CAS  PubMed  Google Scholar 

  9. Kersey RD, Elliot DL, Goldberg L, Kanayama G, Leone JE, Pavlovich M, et al. National Athletic Trainers Association Position Statement: anabolic-androgenic steroids. J Athl Train. 2012;47(5):567–88.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Nieschlag E, Vorona E. Mechanisms in endocrinology: medical consequences of doping with anabolic androgenic steroids: effects on reproductive functions. Eur J Endocrinol. 2015;173(2):R47–58.

    Article  CAS  PubMed  Google Scholar 

  11. Gronbladh A, Nylander E, Hallberg M. The neurobiology and addiction potential of anabolic androgenic steroids and the effects of growth hormone. Brain Res Bull. 2016;126(Pt 1):127–37.

    Article  PubMed  Google Scholar 

  12. Handelsman D. Androgen physiology, pharmacology and abuse. Philadelphia: Elsevier Saunder; 2016.

    Book  Google Scholar 

  13. Fragkaki AG, Angelis YS, Koupparis M, Tsantili-Kakoulidou A, Kokotos G, Georgakopoulos C. Structural characteristics of anabolic androgenic steroids contributing to binding to the androgen receptor and to their anabolic and androgenic activities. Applied modifications in the steroidal structure. Steroids. 2009;74(2):172–97.

    Article  CAS  PubMed  Google Scholar 

  14. MacKrell JG, Yaden BC, Bullock H, Chen K, Shetler P, Bryant HU, et al. Molecular targets of androgen signaling that characterize skeletal muscle recovery and regeneration. NuclRecept Signal. 2015;13:e005.

    Google Scholar 

  15. Oberlander JG, Henderson LP. The Sturm und Drang of anabolic steroid use: angst, anxiety, and aggression. Trends Neurosci. 2012;35(6):382–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Pereira de Jésus-Tran K, Côté PL, Cantin L, Blanchet J, Labrie F, Breton R. Comparison of crystal structures of human androgen receptor ligand-binding domain complexed with various agonists reveals molecular determinants responsible for binding affinity. Protein Sci: Publ Protein Soc. 2006;15(5):987–99.

    Article  Google Scholar 

  17. Alvarez-Ginarte YM, Crespo R, Montero-Cabrera LA, Ruiz-Garcia JA, Ponce YM, Santana R, et al. A novel in-silico approach for QSAR studies of anabolic and androgenic activities in the 17β-hydroxy-5α-androstane steroid family. QSAR Comb Sci. 2005;24(2):218–26.

    Article  CAS  Google Scholar 

  18. Ciorsac AA, Popescu I, Isvoran A. Synthetic anabolic steroids binding to the human androgen receptor. Rom J Phys. 2015;60(7–8):1112–20.

    Google Scholar 

  19. Parr MK, Botrè F, Naß A, Hengevoss J, Diel P, Wolber G. Ecdysteroids: A novel class of anabolic agents? Biol Sport. 2015;32(2):169–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Joseph JF, Parr MK. Synthetic androgens as designer supplements. Curr Neuropharmacol. 2015;13(1):89–100.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Kim S, Thiessen PA, Bolton EE, Chen J, Fu G, Gindulyte A, et al. PubChem substance and compound databases. Nucleic Acids Res. 2016;44(D1):D1202–13.

    Article  CAS  PubMed  Google Scholar 

  22. Lagorce D, Sperandio O, Galons H, Miteva MA, Villoutreix BO. FAF-Drugs2: free ADME/tox filtering tool to assist drug discovery and chemical biology projects. BMC Bioinforma. 2008;9:396.

    Article  Google Scholar 

  23. Kingsley LJ, Wilson GL, Essex ME, Lill MA. Combining structure- and ligand-based approaches to improve site of metabolism prediction in CYP2C9 substrates. Pharm Res. 2015;32(3):986–1001.

    Article  CAS  PubMed  Google Scholar 

  24. Daina A, Michielin O, Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep. 2017;7:42717.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Cheng F, Li W, Zhou Y, Shen J, Wu Z, Liu G, et al. admetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties. J ChemInf Model. 2012;52(11):3099–105.

    Article  CAS  Google Scholar 

  26. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, et al. The Protein Data Bank. Nucleic Acids Res. 2000;28(1):235–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, et al. UCSF chimera--a visualization system for exploratory research and analysis. J Comput Chem. 2004;25(13):1605–12.

    Article  CAS  PubMed  Google Scholar 

  28. Grosdidier A, Zoete V, Michielin O. SwissDock, a protein-small molecule docking web service based on EADock DSS. Nucleic Acids Res. 2011;39(Web Server issue):W270–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Grosdidier A, Zoete V, Michielin O. EADock: docking of small molecules into protein active sites with a multiobjective evolutionary optimization. Proteins. 2007;67(4):1010–25.

    Article  CAS  PubMed  Google Scholar 

  30. Patlewicz G, Jeliazkova N, Safford RJ, Worth AP, Aleksiev B. An evaluation of the implementation of the Cramer classification scheme in the Toxtree software. SAR QSAR Environ Res. 2008;19(5–6):495–524.

    Article  CAS  PubMed  Google Scholar 

  31. Benigni R, Bossa C. Predictivity and reliability of QSAR models: the case of mutagens and carcinogens. ToxicolMech Methods. 2008;18(2–3):137–47.

    CAS  Google Scholar 

  32. Hengstler JG, Oesch F. Ames test. In: Encyclopedia of Genetics, eBrenner S, Miller JH, editors Academic Press; 2001. p. 51–54.

  33. Kolsek K, Mavri J, SollnerDolenc M, Gobec S, Turk S. Endocrine disruptome--an open source prediction tool for assessing endocrine disruption potential through nuclear receptor binding. J ChemInf Model. 2014;54(4):1254–67.

    Article  CAS  Google Scholar 

  34. Gfeller D, Grosdidier A, Wirth M, Daina A, Michielin O, Zoete V. SwissTargetPrediction: a web server for target prediction of bioactive small molecules. Nucleic Acids Res. 2014;42(Web Server issue):W32–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Poroikov V, Filimonov D, Lagunin A, Gloriozova T, Zakharov A. PASS: identification of probable targets and mechanisms of toxicity. SAR QSAR Environ Res. 2007;18(1–2):101–10.

    Article  CAS  PubMed  Google Scholar 

  36. Marwaha A, Goel RK, Mahajan MP. PASS-predicted design, synthesis and biological evaluation of cyclic nitrones as nootropics. Bioorg Med Chem Lett. 2007;17(18):5251–5.

    Article  CAS  PubMed  Google Scholar 

  37. Lagunin A, Filimonov D, Poroikov V. Multi-targeted natural products evaluation based on biological activity prediction with PASS. Curr Pharm Des. 2010;16(15):1703–17.

    Article  CAS  PubMed  Google Scholar 

  38. Goel RK, Singh D, Lagunin A, Poroikov V. PASS-assisted exploration of new therapeutic potential of natural products. Med Chem Res. 2011;20(9):1509–14.

    Article  CAS  Google Scholar 

  39. Kuhn M, Letunic I, Jensen LJ, Bork P. The SIDER database of drugs and side effects. Nucleic Acids Res. 2015;44(D1):D1075–9.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Hishigaki H, Kuhara S. hERGAPDbase: a database documenting hERG channel inhibitory potentials and APD-prolongation activities of chemical compounds. Database (Oxford). 2011:bar017.

  41. Alomar MJ. Factors affecting the development of adverse drug reactions. Saudi Pharm J. 2014;22(2):83–94.

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Biology-Chemistry and Advanced Environmental Research Laboratories, West University of Timisoara, 16 Pestalozzi, 300115, Timisoara, Romania

    Marin Roman, Diana Larisa Roman, Vasile Ostafe & Adriana Isvoran

  2. Department of Physical Education and Sport, Politehnica University of Timisoara, Timisoara, Romania

    Alecu Ciorsac

Authors
  1. Marin Roman
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  2. Diana Larisa Roman
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  3. Vasile Ostafe
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  4. Alecu Ciorsac
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  5. Adriana Isvoran
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Corresponding author

Correspondence to Adriana Isvoran.

Additional information

Responsible editor: Kin Yip Tam, Zoran Mandic, and Tonglei Li

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Roman, M., Roman, D.L., Ostafe, V. et al. Computational Assessment of Pharmacokinetics and Biological Effects of Some Anabolic and Androgen Steroids. Pharm Res 35, 41 (2018). https://doi.org/10.1007/s11095-018-2353-1

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  • DOI: https://doi.org/10.1007/s11095-018-2353-1

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