图书馆订阅: Guest
Begell Digital Portal Begell 数字图书馆 电子图书 期刊 参考文献及会议录 研究收集
影响因子: 2.156 5年影响因子: 2.255 SJR: 0.649 SNIP: 0.599 CiteScore™: 3

ISSN 打印: 1045-4403
ISSN 在线: 2162-6502


DOI: 10.1615/CritRevEukaryotGeneExpr.2019026432
pages 177-187

Molecular Basis of Bicalutamide Response Alteration of Androgen Receptor Caused by Single Nucleotide Polymorphisms: An In Silico Investigation

Noushin Hadian
Department of Biology, Faculty of Sciences, Shahrekord branch, Islamic Azad University, Shahrekord, Iran
Farzaneh Mohamadi Farsani
Department of Biology, Faculty of Sciences, University of Isfahan, Isfahan, Iran
Mohamad Reza Ganjalikhany
Department of Biology, Faculty of Sciences, University of Isfahan, Isfahan, Iran
Hossein Sazegar
Department of Biology, Faculty of Sciences, Shahrekord branch, Islamic Azad University, Shahrekord, Iran
Mehdi Sadeghi
Department of Cell and Molecular Biology, Faculty of Science, Semnan University, Semnan, Iran


The vast majority of drugs act through binding to their protein targets. Prediction of the interaction between small molecules and these receptors is a key element in the process of drug discovery. Advances in structural biology have enabled us to resolve the three-dimensional structure of proteins, which are the targets of the drugs. Pharmacogenetics also helped researchers to study the structural variations arise from the single nucleotide polymorphisms (SNPs) and to survey the effects these variations in drug design and development. These improvements led to the identification of structural changes caused by SNPs, which affect the drug interaction with their receptors, called drug response. In this study, the interaction between androgen receptor and bicalutamide was investigated using a computational analysis. The results of these analyses were then used for identification of nonsynonymous SNPs that are potentially involved in drug response alterations. The data show that amino acids Met895, Trp741, Arg752, Ile899, Leu707, Gly708, Gln711, Met745, Met749, Thr877, Phe764, Met742, Asn705 and Leu704 are the main residues involved in the interaction between androgen receptor and bicalutamide. The occurrence of nonsynonymous polymorphisms I843T, L708R, H690P, I870M, N757S, L713F, G744E, L678P, M788V, M781I, A722T, H875Y, I842V, and F827L in this receptor greatly affected its interaction with bicalutamide, and they were able to cause drug resistance. The results of this study could be useful in predicting the response to treatment in patients receiving bicalutamide.


  1. Lahti JL, Tang GW, Capriotti E, Liu T, Altman RB. , Bioinformatics and variability in drug response: a protein structural perspective. J Royal Soc Interf. 2012;9(72):1409–37.

  2. Obata H, Yahata T, Quan J, Sekine M, Tanaka K. , Association between single nucleotide polymorphisms of drug resistance-associated genes and response to chemotherapy in advanced ovarian cancer. J Anticancer Res. 2006;26(3B):2227–32.

  3. Van den Broeck T, Joniau S, Clinckemalie L, Helsen C, Prekovic S, Spans L, Tosco L, Van Poppel H, Claessens F. , The role of single nucleotide polymorphisms in predicting prostate cancer risk and therapeutic decision making. J BioMed Res Int. 2014;2014:627510.

  4. Nelson PS, Clegg N, Arnold H, Ferguson C, Bonham M, White J, Hood L, Lin B, The program of androgen-responsive genes in neoplastic prostate epithelium. J Proc Natl Acad Sci. 2002;99(18):11890–95.

  5. Lavery DN, Bevan CL. , Androgen receptor signalling in prostate cancer: the functional consequences of acetylation. J BioMed Res Int. 2011;2011:862125.

  6. Ahmad N, Kumar R. , Steroid hormone receptors in cancer development: a target for cancer therapeutics. J Cancer Lett. 2011;300(1):1–9.

  7. Lu Y, Sun J, Kader AK, Kim ST, Kim JW, Liu W, Sun J, Lu D, Feng J, Zhu Y, Jin T. , Association of prostate cancer risk with snps in regions containing androgen receptor binding sites captured by ChIP‐On‐chip analyses. J Prostate. 2012;72(4):376–85.

  8. Tan ME, Li J, Xu HE, Melcher K, Yong EL. , Androgen receptor: structure, role in prostate cancer and drug discovery. J Acta Pharmacol Sinica. 2015;36(1):3.

  9. Li C, Li C, Le Y, Chen JF. , Formation of bicalutamide nanodispersion for dissolution rate enhancement. Int J Pharm. 2011;404(12):257–63.

  10. Bohl CE, Gao W, Miller DD, Bell CE, Dalton JT. , Structural basis for antagonism and resistance of bicalutamide in prostate cancer. J Proc Natl Acad Sci. 2005;102(17):6201–6.

  11. Masiello D, Cheng S, Bubley GJ, Lu ML, Balk SP. , Bicalutamide functions as an androgen receptor antagonist by assembly of a transcriptionally inactive receptor. J Biol Chem. 2002;277(29):26321–26.

  12. Tian X, He Y, Zhou J. , Progress in antiandrogen design targeting hormone binding pocket to circumvent mutation based resistance. J Front Pharmacol. 2015;6:57.

  13. Osguthorpe DJ, Hagler AT. , Mechanism of androgen receptor antagonism by bicalutamide in the treatment of prostate cancer. J Biochem. 2011;50(19):4105–13.

  14. Helsen C, Van den Broeck T, Voet A, Prekovic S, Van Poppel H, Joniau S, Claessens F. , Androgen receptor antagonists for prostate cancer therapy. J Endocrine-Related Cancer. 2014;21(4):T105–18.

  15. Farsani FM, Ganjalikhany MR, Dehbashi M, Naeini MM, Vallian S. , Structural basis of DNA topoisomerase II-α (Top2-α) inhibition: a computational analysis of interactions between Top2-α and its inhibitors. J Med Chem Res. 2016;25(6):1250–59.

  16. Yari H, Ganjalikhany MR, Sadegh H. , In silico investigation of new binding pocket for mitogen activated kinase kinase (MEK): Development of new promising inhibitors. J Comput Bio Chem. 2015;59:185–98.

  17. Mirza Z, Schulten HJ, Farsi HM, Al-Maghrabi JA, Gari MA, Chaudhary AG, Abuzenadah AM, Al-Qahtani MH, Karim S., Molecular interaction of a kinase inhibitor midostaurin with anticancer drug targets, S100A8 and EGFR: transcriptional profiling and molecular docking study for kidney cancer therapeutics. J PLoS One. 2015;10(3):e0119765.

  18. Kabir MZ, Tee WV, Mohamad SB, Alias Z, Tayyab S. , Interaction of an anticancer drug, gefitinib with human serum albumin: insights from fluorescence spectroscopy and computational modeling analysis. J. RSC Adv. 2016;6(94):91756–67.

  19. Sliwoski G, Kothiwale S, Meiler J, Lowe E.W. , Computational methods in drug discovery. J Pharmacol Rev. 2014;66(1):334–95.

  20. Farsani FM, Ganjalikhany MR, Vallian S. , Studies on non-synonymous polymorphisms altering human DNA topoisomerase II-Alpha interaction with amsacrine and mitoxantrone: an in silico approach. J Curr Cancer Drug Targets. 2017;17(7):657668.

  21. Kahrani ZF, Ganjalikhany MR, Rasa SMM, Emamzadeh R. , New insights into the molecular characteristics behind the function of Renilla luciferase. J Cell Biochem. 2018;119(2):1780–90.

  22. Sherry ST, Ward MH, Kholodov M, Baker J, Phan L, Smigielski EM, Sirotkin K. , dbSNP: the NCBI database of genetic variation. J Nucleic Acids Res. 2001;29(1):308–11.

  23. Lauck F, Smith CA, Friedland GF, Humphris EL, Kortemme T. , RosettaBackrub—a web server for flexible backbone protein structure modeling and design. J Nucleic Acids Res. 2010;38(suppl_2):W569–W575.

  24. Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. , AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009;30(16):2785–91.

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

  26. Laskowski RA, Swindells MB. , LigPlot+: multiple ligand–protein interaction diagrams for drug discovery. J Chem Inform Model. 2011;51(10):2778–86.

  27. Bisson WH, Abagyan R, Cavasotto, CN. , Molecular basis of agonicity and antagonicity in the androgen receptor studied by molecular dynamics simulations. J Mol Graph Model. 2008;27(4):452–58.

  28. Liu H, An X, Li S, Wang Y, Li J, Liu H. , Interaction mechanism exploration of R-bicalutamide/S-1 with WT/W741L AR using molecular dynamics simulations. J Mol BioSystems. 2015; 11(12):3347–54.

  29. Farsani FM, Vallian S. , Variations Related to resistance of cancer cells to topoisomerase II alpha inhibitory drugs. J Bioinform Proteom Open Access J. 2018; 2(1):000123.

Articles with similar content:

Interactions of RKIP with Inflammatory Signaling Pathways
Critical Reviews™ in Oncogenesis, Vol.19, 2014, issue 6
Sally Wenzel, Jinming Zhao
Identification of Potential Core Genes in Immunoglobulin-Resistant Kawasaki Disease Using Bioinformatics Analysis
Critical Reviews™ in Eukaryotic Gene Expression, Vol.30, 2020, issue 1
Qihong Fan , Yan Pan
Epigenetic Modification Related to Acetylation of Histone and Methylation of DNA as a Key Player in Immunological Disorders
Critical Reviews™ in Eukaryotic Gene Expression, Vol.29, 2019, issue 1
Muhammad Imran Qadir, Farha Anwer
Gene Prioritization and Network Topology Analysis of Targeted Genes for Acquired Taxane Resistance by Meta-Analysis
Critical Reviews™ in Eukaryotic Gene Expression, Vol.29, 2019, issue 6
Jin Ki Kim, Young Seok Lee, Dongha Kim, Sung Young Kim
Targeting the Regulatory Machinery of BIM for Cancer Therapy
Critical Reviews™ in Eukaryotic Gene Expression, Vol.22, 2012, issue 2
Steven Grant, Hisashi Harada