Volume 3, Issue 4 (3-2017)                   jhbmi 2017, 3(4): 310-318 | Back to browse issues page

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Hadian N, Sazegar H, Mohamadi Farsani F, Zia N. Computational Analysis of Interactions between Androgen Receptor and Bicalutamide. jhbmi 2017; 3 (4) :310-318
URL: http://jhbmi.ir/article-1-170-en.html
. Ph.D in Physiology, Assistant Professor, Biology Dept., Faculty of Sciences, Islamic Azad University of Shahrekord, Shahrekord, Iran.
Abstract:   (5970 Views)
Introduction: The majority of drugs act through binding with target proteins. Prediction of the interaction between small molecules and proteins is a key element in the process of drug discovery. Advances in Structural Genomics have provided this possibility to access three-dimensional structures of the proteins which are targeted by drugs. Since laboratory processes through which drug-target protein interactions are investigated require high cost and energy, in silico methods can be used as effective strategies for providing useful information in support of experimental methods.
Methods: In this study, the interaction between androgen receptor and Bicalutamide, a widely used drug in the treatment of prostate cancer, was investigated via computational analyses. The docking analysis of this receptor with Bicalutamide was done using Autodock4.2.6 and analysis of complexes was done through LigPlot4.5.3 and Chimera1.5.3.
Results: The obtained results showed that amino acid residues Met-895, Trp-741, Arg-752, Ile-899, Leu-707, Gly-708, Gln-711, Met-745, Met-749, Thr-87, Phe-764, and Met-749 (through forming hydrophobic bonds with the drug) and amino acid residues Asn-705 and Leu-704 (through forming hydrogen bonds with the drug) play a significant role in the protein-drug interaction and cause proper positioning of the drug in protein and consequently its efficacy.
Conclusion: These results could be used in the future studies for investigation of drug resistance to Bicalutamide and to develop more efficient medicines.
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Type of Study: Original Article | Subject: Special
Received: 2016/12/1 | Accepted: 2017/02/23

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