Skip to main content

Advertisement

Log in

Molecular Docking, Drug Likeness, and ADMET Analyses of Passiflora Compounds as P-Glycoprotein (P-gp) Inhibitor for the Treatment of Cancer

  • Cancer Chemoprevention (R Agarwal, CV Rao and S Yu, Section Editors)
  • Published:
Current Pharmacology Reports Aims and scope Submit manuscript

Abstract

Cancer disease leads to deaths worldwide. Anti-cancer drugs have a high prevalence of side effects and cause multidrug resistance (MDR) that remains a significant barrier to major cancer therapy. To date, chemical and herbal substances have been analyzed for their MDR modulatory activity. However, research on new and safe molecules has been continued to overcome MDR in cancer. The plant compounds can be an effective inhibitor for successful cancer therapy. Recently, computational models have gained importance to discover new inhibitors. In the present study, we aimed to explore the various compounds of Passiflora species as P-gp inhibitor. P-gp protein was docked with the active substrate and inhibitor, respectively, including tamoxifen and verapamil. Besides, 3D structure of P-gp was docked with 11 compounds (luteolin, beta amyrin, beta-sitosterol, chimaphilin, chrysin, edulan I and II, apigenin, oleanolic acid, stigmasterol, hydroxyflavone) of plant origin using AutoDock4.2 program. Furthermore, the compounds were analyzed for ADMET and drug likeness properties of compounds determined as Lipinski, Veber, and Ghose’s rules (http://www.swissadme.ch/). As obtained molecular docking analysis results, luteolin, chrysin, hydroxyflavone, and apigenin may be a candidate for being P-gp inhibitor. Hence, it may be of attention to consider these compounds for further in vitro and in vivo evaluation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Yura Y. Presage of oncolytic virotherapy for oral cancer with herpes simplex virus. Jpn Dent Sci Rev. 2017;53:53–60. https://doi.org/10.1016/j.jdsr.2016.10.001.

    Article  PubMed  Google Scholar 

  2. Pluchino KM, Hall MD, Goldsborough AS, Callaghan R, Gottesman MM. Collateral sensitivity as a strategy against cancer multidrug resistance. Drug Resist Updat. 2012;15:98–105. https://doi.org/10.1016/j.drup.2012.03.002.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Saunders NA, Simpson F, Thompson EW, Hill MM, Endo-Munoz L, Leggatt G, et al. Role of intratumoural heterogeneity in cancer drug resistance: molecular and clinical perspectives. EMBO Mol Med. 2012;4(8):675–84. https://doi.org/10.1002/emmm.201101131.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Gottesman MM, Fojo T, Bates SE. Multidrug resistance in cancer: role of ATP-dependent transporters. Nat Rev Cancer. 2002;2(1):48–58. https://doi.org/10.1038/nrc706.

    Article  CAS  PubMed  Google Scholar 

  5. Chai S, To KK, Lin G. Circumvention of multi-drug resistance of cancer cells by Chinese herbal medicines. Chin Med. 2010;5:26. https://doi.org/10.1186/1749-8546-5-26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Wang J, Seebacher N, Shi H, Kan Q, Duan Z. Novel strategies to prevent the development of multidrug resistance (MDR) in cancer. Oncotarget. 2017;8(48):84559–71. https://doi.org/10.18632/oncotarget.19187.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Iyer AK, Singh A, Ganta S, Amiji MM. Role of integrated cancer nanomedicine in overcoming drug resistance. Adv Drug Deliv Rev. 2013;65(13–14):1784–802. https://doi.org/10.1016/j.addr.2013.07.012.

    Article  CAS  PubMed  Google Scholar 

  8. Moitra K. Overcoming multidrug resistance in cancer stem cells. Biomed Res Int. 2015;2015:635745. https://doi.org/10.1155/2015/635745.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Jabr-Milane LS, van Vlerken LE, Yadav S, Amiji MM. Multi-functional nanocarriers to overcome tumor drug resistance. Cancer Treat Rev. 2008;34(7):592–602. https://doi.org/10.1016/j.ctrv.2008.04.003.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Gillet JP, Efferth T, Remacle J. Chemotherapy-induced resistance by ATP-binding cassette transporter genes. Biochim Biophys Acta. 2007;1775(2):237–62. https://doi.org/10.1016/j.bbcan.2007.05.002.

    Article  CAS  PubMed  Google Scholar 

  11. Allikmets R, Gerrard B, Hutchinson A, Dean M. Characterization of the human ABC superfamily: isolation and mapping of 21 new genes using the expressed sequence tags database. Hum Mol Genet. 1996;5(10):1649–55. https://doi.org/10.1093/hmg/5.10.1649.

    Article  CAS  PubMed  Google Scholar 

  12. Nobili S, Landini I, Giglioni B, Mini E. Pharmacological strategies for overcoming multidrug resistance. Curr Drug Targets. 2006;7(7):861–79. https://doi.org/10.2174/138945006777709593.

    Article  CAS  PubMed  Google Scholar 

  13. Yuan H, Ma Q, Ye L, Piao G. The traditional medicine and modern medicine from natural products. Molecules. 2016;21(5):559. https://doi.org/10.3390/molecules21050559.

    Article  CAS  PubMed Central  Google Scholar 

  14. Lourith N, Kanlayavattanakul M. Antioxidant activities and phenolics of Passiflora edulis seed recovered from juice production residue. J Oleo Sci. 2013;62(4):235–40. https://doi.org/10.5650/jos.62.235.

    Article  CAS  PubMed  Google Scholar 

  15. Silva DC, Freitas ALP, Barros FCN, Lins KO, Alves APN, Alencar NM, et al. Polysaccharide isolated from Passiflora edulis: characterization and antitumor properties. Carbohydr Polym. 2012;87(1):139–45. https://doi.org/10.1016/j.carbpol.2011.07.029.

    Article  CAS  PubMed  Google Scholar 

  16. Brewer FK, Follit CA, Vogel PD, Wise JG. In silico screening for inhibitors of p-glycoprotein that target the nucleotide binding domains. Mol Pharmacol. 2014;86(6):716–26. https://doi.org/10.1124/mol.114.095414.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. McCormick JW, Vogel PD, Wise JG. Multiple drug transport pathways through human P-glycoprotein. Biochemistry. 2015;54(28):4374–90. https://doi.org/10.1021/acs.biochem.5b00018.

    Article  CAS  PubMed  Google Scholar 

  18. Prajapati R, Singh U, Patil A, Khomane KS, Bagul P, Bansal AK, et al. In silico model for P-glycoprotein substrate prediction: insights from molecular dynamics and in vitro studies. J Comput Aided Mol Des. 2013;27(4):347–63. https://doi.org/10.1007/s10822-013-9650-x.

    Article  CAS  PubMed  Google Scholar 

  19. Shahraki O, Zargari F, Edraki N, Khoshneviszadeh M, Firuzi O, Miri R. Molecular dynamics simulation and molecular docking studies of 1,4-dihydropyridines as P-glycoprotein's allosteric inhibitors. J Biomol Struct Dyn. 2018;36(1):112–25. https://doi.org/10.1080/07391102.2016.1268976.

    Article  CAS  PubMed  Google Scholar 

  20. Pajeva IK, Globisch C, Wiese M. Combined pharmacophore modeling, docking, and 3D QSAR studies of ABCB1 and ABCC1 transporter inhibitors. Chem Med Chem. 2009;4(11):1883–96. https://doi.org/10.1002/cmdc.200900282.

    Article  CAS  PubMed  Google Scholar 

  21. Zhou S, Lim LY, Chowbay B. Herbal modulation of P-glycoprotein. Drug Metab Rev. 2004;36(1):57–104. https://doi.org/10.1081/dmr-120028427.

    Article  CAS  PubMed  Google Scholar 

  22. Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE, Belew RK, et al. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J Comput Chem. 1998;19(14):1639–62. https://doi.org/10.1002/(SICI)1096-987X(19981115)19:14<1639::AID-JCC10>3.0.CO;2-B.

    Article  CAS  Google Scholar 

  23. Trott O, Olson AJ. Auto Dock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. 2010;31(2):455–61. https://doi.org/10.1002/jcc.21334.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Humphrey W, Dalke A, Schulten K. VMD: visual molecular dynamics. J Mol Graph. 1996;14(1):33–8, 27-8. https://doi.org/10.1016/0263-7855(96)00018-5.

    Article  CAS  PubMed  Google Scholar 

  25. Thomsen R, Christensen MH. MolDock: a new technique for high-accuracy molecular docking. J Med Chem. 2006;49(11):3315–21. https://doi.org/10.1021/jm051197e.

    Article  CAS  PubMed  Google Scholar 

  26. Ntie-Kang F, Lifongo LL, Mbah JA, Owono Owono LC, Megnassan E, Mbaze LM, et al. In silico drug metabolism and pharmacokinetic profiles of natural products from medicinal plants in the Congo basin. In Silico Pharmacol. 2013;1:12. https://doi.org/10.1186/2193-9616-1-12.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Zoete V, Daina A, Bovigny C, Michielin O. SwissSimilarity: a web tool for low to ultra high throughput ligand-based virtual screening. J Chem Inf Model. 2016;56:1399–404. https://doi.org/10.1021/acs.jcim.6b00174.

    Article  CAS  PubMed  Google Scholar 

  28. 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;7:427–517. https://doi.org/10.1038/srep42717.

    Article  Google Scholar 

  29. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev. 2001;46(1–3):3–26. https://doi.org/10.1016/s0169-409x(00)00129-0.

    Article  CAS  PubMed  Google Scholar 

  30. Veber DF, Johnson SR, Cheng HY, Smith BR, Ward KW, Kopple KD. Molecular properties that influence the oral bioavailability of drug candidates. J Med Chem. 2002;45(12):2615–23. https://doi.org/10.1021/jm020017n.

    Article  CAS  PubMed  Google Scholar 

  31. Ghose AK, Viswanadhan VN, Wendoloski JJ. A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases. J Comb Chem. 1999;1(1):55–68. https://doi.org/10.1021/cc9800071.

    Article  CAS  PubMed  Google Scholar 

  32. Kim Y, Chen J. Molecular structure of human P-glycoprotein in the ATP-bound, outward-facing conformation. Science. 2018;359(6378):915–919. https://doi.org/10.1126/science.aar7389.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Serap Yalcin.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection on Cancer Chemoprevention

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yalcin, S. Molecular Docking, Drug Likeness, and ADMET Analyses of Passiflora Compounds as P-Glycoprotein (P-gp) Inhibitor for the Treatment of Cancer. Curr Pharmacol Rep 6, 429–440 (2020). https://doi.org/10.1007/s40495-020-00241-6

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40495-020-00241-6

Keywords

Navigation