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Qsar and Docking Analysis of A2b Adenosine Receptor Antagonists Based on Non-Xanthine Scaffold Publisher



Mansourian M1, 2 ; Fassihi A1, 3 ; Saghaie L1, 3 ; Madadkarsobhani A4, 5 ; Mahnam K6 ; Abbasi M1
Authors
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Authors Affiliations
  1. 1. Department of Medicinal Chemistry, School of Pharmacy, Isfahan University of Medical Sciences, Isfahan, 81746-73461, Iran
  2. 2. Medicinal Plants Research Center, Yasuj University of Medical Sciences, Yasuj, Iran
  3. 3. Bioinformatics Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
  4. 4. Life Sciences Department, Barcelona Supercomputing Center (BSC), Barcelona, 08034, Spain
  5. 5. Department of Bioinformatics, Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran
  6. 6. Biology Department, Faculty of Science, Shahrekord University, Shahrekord, Iran

Source: Medicinal Chemistry Research Published:2015


Abstract

Partial least squares (PLS) method as ligand-based method was applied for building quantitative structure-activity relationships (QSAR) regression model to predict the inhibitory activity of some A2B antagonists. The accuracy and predictability of the developed model were evaluated by several validation methods using external and internal test sets and also the criteria recommended by Tropsha and Roy were met. The result of the PLS model had a high statistical quality (R 2 = 0.936 and Q 2 = 0.867) for predicting the activity of the compounds. Evaluation of a test set of seven compounds with the developed PLS model revealed that this model is reliable and has a good predictability. Because of high correlation between the predicted and experimental values of activity, PLS model proved to be a highly predictive QSAR approach. Also, the reliability of the model was assessed through docking for the selected antagonists as structure-based method. A potential binding site of A2BAR was verified according to the previous studies of site-directed mutagenesis. Phe173, Glu174, His251, Asn254, Lys269, Ile276, and His 280 were determined to be involved in ligand-receptor interactions. © 2014 Springer Science+Business Media New York.
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