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Medicinal Chemistry Research

, Volume 26, Issue 10, pp 2322–2335 | Cite as

Molecular docking simulations and GRID-independent molecular descriptor (GRIND) analysis to probe stereoselective interactions of CYP3A4 inhibitors

Original Research
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Abstract

CYP3A4 has been identified as a major enzyme involved in the metabolism of drugs and xenobiotics in the human body. It is mainly expressed in the liver and has a wide capacity to oxidize structurally and functionally diverse compounds due to its large promiscuous catalytic binding site. Inhibition of CYP3A4 often leads to undesired drug–drug interactions and toxic side effects. Previous studies have demonstrated that enantiomers of the same chiral drug might inhibit CYP3A4 with different potencies and thus, one enantiomer might have different pharmacokinetics, and metabolism as compared to its counterpart. Therefore, the use of enantiopure therapeutic agents has been advocated as a promising concept to evade drug toxicity. This emphasizes the need to investigate the molecular basis of interaction and stereoselectivity of CYP3A4. Towards this goal, various in silico models have been developed that correlate the differences in the inhibitory potencies of enantiomeric pairs with difference in their interaction pattern within the binding cavity of CYP3A4. The 3D interaction based differentiating features include two hydrogen bond acceptors at a certain distance from each other, as well as from molecular boundaries of different enantiomeric pairs. Additionally, our results demonstrated the role of a hydrogen bond donor and a hydrogen bond acceptor in stereoselective inhibition of CYP3A4.

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Keywords

Cytochrome P450 (CYP-P450) Drug metabolism CYP3A4 inhibitors Stereoselectivity GRIND Molecular docking 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no competing interests.

Supplementary material

44_2017_1933_MOESM1_ESM.docx (699 kb)
Supplementary Item I
44_2017_1933_MOESM2_ESM.xlsx (29 kb)
Supplementary Item II

References

  1. Baroni M et al. (1993) Generating optimal linear PLS estimations (GOLPE): an advanced chemometric tool for handling 3D-QSAR problems. Quant Struct-Act Rel 12(1):9–20CrossRefGoogle Scholar
  2. Breadmore MC, Thormann W (2003) Capillary electrophoresis evidence for the stereoselective metabolism of itraconazole in man. Electrophoresis 24(15):2588–2597CrossRefPubMedGoogle Scholar
  3. Breuninger LM et al. (1995) Expression of multidrug resistance-associated protein in NIH/3T3 cells confers multidrug resistance associated with increased drug efflux and altered intracellular drug distribution. Cancer Res 55(22):5342–5347PubMedGoogle Scholar
  4. Cheng F et al. (2012) admetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties. J Chem Inf Model 52(11):3099–3105Google Scholar
  5. Choi BH et al. (2001) Effects of norfluoxetine, the major metabolite of fluoxetine, on the cloned neuronal potassium channel Kv3. 1. Neuropharmacology 41(4):443–453CrossRefPubMedGoogle Scholar
  6. Cianchetta G et al. (2006) Molecular interaction fields in ADME and safety. Mol Interact Fields 27:197–218CrossRefGoogle Scholar
  7. de Groot MJ, Ekins S (2002) Pharmacophore modeling of cytochromes P450. Adv Drug Deliv Rev 54(3):367–383CrossRefPubMedGoogle Scholar
  8. Dilmaghanian S et al. (2004) Enantioselectivity of inhibition of cytochrome P450 3A4 (CYP3A4) by ketoconazole: testosterone and methadone as substrates. Chirality 16(2):79–85CrossRefPubMedGoogle Scholar
  9. Dobson PD, Kell DB (2008) Carrier-mediated cellular uptake of pharmaceutical drugs: an exception or the rule? Nat Rev Drug Discov 7(3):205–220CrossRefPubMedGoogle Scholar
  10. Durán A et al. (2008) Development and validation of AMANDA, a new algorithm for selecting highly relevant regions in molecular interaction fields. J Chem Inf Model 48(9):1813–1823CrossRefPubMedGoogle Scholar
  11. Ernest CS et al. (2005) Mechanism-based inactivation of CYP3A by HIV protease inhibitors. J Pharmacol Exp Ther 312(2):583–591CrossRefPubMedGoogle Scholar
  12. Freeman-Cook KD et al. (2013) Lipophilic efficiency: the most important efficiency metric in medicinal chemistry. Future Med Chem 5(2):113–115CrossRefPubMedGoogle Scholar
  13. Hajós M et al. (2004) The selective norepinephrine reuptake inhibitor antidepressant reboxetine: pharmacological and clinical profile. CNS Drug Rev 10(1):23–44CrossRefPubMedGoogle Scholar
  14. Hamdy DA, Brocks DR (2009) Nonlinear stereoselective pharmacokinetics of ketoconazole in rat after administration of racemate. Chirality 21(7):704–712CrossRefPubMedGoogle Scholar
  15. Harlow GR, Halpert JR (1998) Analysis of human cytochrome P450 3A4 cooperativity: construction and characterization of a site-directed mutant that displays hyperbolic steroid hydroxylation kinetics. Proc Natl Acad Sci 95(12):6636–6641CrossRefPubMedPubMedCentralGoogle Scholar
  16. He YA et al. (1997) Identification of three key residues in substrate recognition site 5 of human cytochrome P450 3A4 by cassette and site-directed mutagenesis. Biochemistry 36(29):8831–8839CrossRefPubMedGoogle Scholar
  17. Holladay JW et al. (1998) Pharmacokinetics and antidepressant activity of fluoxetine in transgenic mice with elevated serum alpha-1-acid glycoprotein levels. Drug Metab Dispos 26(1):20–24PubMedGoogle Scholar
  18. Jabeen I et al. (2012) Structure–activity relationships, ligand efficiency, and lipophilic efficiency profiles of benzophenone-type inhibitors of the multidrug transporter P-glycoprotein. J Med Chem 55(7):3261–3273CrossRefPubMedPubMedCentralGoogle Scholar
  19. Jayakanthan M et al. (2010) Analysis of CYP3A4-HIV-1 protease drugs interactions by computational methods for highly active antiretroviral therapy in HIV/AIDS. J Mol Graph Model 28(5):455–463CrossRefPubMedGoogle Scholar
  20. Jones G et al. (1997) Development and validation of a genetic algorithm for flexible docking. J Mol Biol 267(3):727–748CrossRefPubMedGoogle Scholar
  21. Kantola T et al. (1998) Erythromycin and verapamil considerably increase serum simvastatin and simvastatin acid concentrations. Clin Pharmacol Ther 64(2):177–182CrossRefPubMedGoogle Scholar
  22. Kunze KL et al. (2006) Stereochemical aspects of itraconazole metabolism in vitro and in vivo. Drug Metab Dispos 34(4):583–590CrossRefPubMedGoogle Scholar
  23. Kwan HY, Thormann W (2011) Enantioselective capillary electrophoresis for the assessment of CYP3A4 - mediated ketamine demethylation and inhibition in vitro. Electrophoresis 32(19):2738–2745CrossRefPubMedGoogle Scholar
  24. Lamb DC et al. (2000) Differential inhibition of human CYP3A4 and Candida albicans CYP51 with azole antifungal agents. Chem Biol Interact 125(3):165–175CrossRefPubMedGoogle Scholar
  25. Li X (2011) Oral bioavailability: basic principles, advanced concepts, and applications. John Wiley and sons vol. 16Google Scholar
  26. Li Z et al. (2004) Personal experience with four kinds of chemical structure drawing software: review on ChemDraw, ChemWindow, ISIS/Draw, and ChemSketch. J Chem Inf Comput Sci 44(5):1886–1890CrossRefPubMedGoogle Scholar
  27. Lu H (2007) Stereoselectivity in drug metabolism. Expert Opin Drug Metab Toxicol 3(2):149–158Google Scholar
  28. Lutz JD et al. (2013) Stereoselective inhibition of CYP2C19 and CYP3A4 by fluoxetine and its metabolite: implications for risk assessment of multiple time-dependent inhibitor systems. Drug Metab Dispos 41(12):2056–2065CrossRefPubMedPubMedCentralGoogle Scholar
  29. Mannu J et al. (2011) A computational study of CYP3A4 mediated drug interaction profiles for anti-HIV drugs. J Mol Model 17(8):1847–1854CrossRefPubMedGoogle Scholar
  30. Marchese Robinson RL et al. (2011) Development and comparison of hERG Blocker classifiers: assessment on different datasets yields markedly different results. Mol Inform 30(5):443–458CrossRefPubMedGoogle Scholar
  31. Molecular Operating Environment (MOE) 2013.08; Chemical Computing Group Inc., 1010 Sherbooke St. West, Suite #910, Montreal, QC, Canada, H3A 2R7, 2015.49Google Scholar
  32. Niesters M et al. (2014) Ketamine for chronic pain: risks and benefits. Br J Clin Pharmacol 77(2):357–367CrossRefPubMedPubMedCentralGoogle Scholar
  33. Obach RS (2000) Inhibition of human cytochrome P450 enzymes by constituents of St. John’s Wort, an herbal preparation used in the treatment of depression. J Pharmacol Exp Ther 294(1):88–95PubMedGoogle Scholar
  34. Pastor M et al. (2000) GRid-INdependent descriptors (GRIND): a novel class of alignment-independent three-dimensional molecular descriptors. J Med Chem 43(17):3233–3243CrossRefPubMedGoogle Scholar
  35. Peng C-C et al. (2012) Stereospecific metabolism of itraconazole by CYP3A4: dioxolane ring scission of azole antifungals. Drug Metab Dispos 40(3):426–435CrossRefPubMedPubMedCentralGoogle Scholar
  36. Schuster D et al. (2006) Development and validation of an in silico P450 profiler based on pharmacophore models. Curr Drug Discov Technol 3(1):1–48CrossRefPubMedGoogle Scholar
  37. Sevrioukova IF, Poulos TL (2010) Structure and mechanism of the complex between cytochrome P4503A4 and ritonavir. Proc Natl Acad Sci 107(43):18422–18427CrossRefPubMedPubMedCentralGoogle Scholar
  38. Sevrioukova IF, Poulos TL (2013) Dissecting cytochrome P450 3A4-ligand interactions using ritonavir analogues. Biochemistry 52(26):4474–4481CrossRefPubMedGoogle Scholar
  39. Shimada T et al. (2010) Structure− function relationships of inhibition of human cytochromes P450 1A1, 1A2, 1B1, 2C9, and 3A4 by 33 flavonoid derivatives. Chem Res Toxicol 23(12):1921–1935CrossRefPubMedPubMedCentralGoogle Scholar
  40. Shityakov S et al. (2014) Three-dimensional quantitative structure–activity relationship and docking studies in a series of anthocyanin derivatives as cytochrome P450 3A4 inhibitors. Adv Appl Bioinform Chem 7:11PubMedPubMedCentralGoogle Scholar
  41. Shou M et al. (1994) Activation of CYP3A4: evidence for the simultaneous binding of two substrates in a cytochrome P450 active site. Biochemistry 33(21):6450–6455CrossRefPubMedGoogle Scholar
  42. Smith DA et al. (1997) Properties of cytochrome P450 isoenzymes and their substrates part 2: properties of cytochrome P450 substrates. Drug Discov Today 2(11):479–486CrossRefGoogle Scholar
  43. Teixeira VH et al. (2010) Analysis of binding modes of ligands to multiple conformations of CYP3A4. Biochimica et Biophysica Acta-Proteins Proteomics 1804(10):2036–2045CrossRefGoogle Scholar
  44. Wang Y-H et al. (2004) Prediction of cytochrome P450 3A inhibition by verapamil enantiomers and their metabolites. Drug Metab Dispos 32(2):259–266CrossRefPubMedGoogle Scholar
  45. Wang S et al. (2012) ADMET evaluation in drug discovery. 12. Development of binary classification models for prediction of hERG potassium channel blockage. Mol Pharm 9(4):996–1010CrossRefPubMedPubMedCentralGoogle Scholar
  46. Weber J et al. (2012) Impact of X-ray structure on predictivity of scoring functions: PPARγ case study. Mol Inform 31(9):631–633CrossRefPubMedGoogle Scholar
  47. Wienkers LC et al. (1999) Cytochrome P-450-mediated metabolism of the individual enantiomers of the antidepressant agent reboxetine in human liver microsomes. Drug Metab Dispos 27(11):1334–1340PubMedGoogle Scholar
  48. Yano JK et al. (2004) The structure of human microsomal cytochrome P450 3A4 determined by X-ray crystallography to 2.05-Å resolution. J Biol Chem 279(37):38091–38094CrossRefPubMedGoogle Scholar
  49. Zhou S-F (2008) Drugs behave as substrates, inhibitors and inducers of human cytochrome P450 3A4. Curr Drug Metab 9(4):310–322CrossRefPubMedGoogle Scholar
  50. Zhou S et al. (2005) Mechanism-based inhibition of cytochrome P450 3A4 by therapeutic drugs. Clin Pharmacokinet 44(3):279–304CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Sadia Mukhtar
    • 1
  • Yusra Sajid Kiani
    • 1
  • Ishrat Jabeen
    • 1
  1. 1.Research Center for Modeling and Simulation (RCMS)National University of Sciences and Technology (NUST)IslamabadPakistan

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