Abstract
BackgroundAT1 receptor antagonists are clinically effective drugs for the treatment of hypertension, cardiovascular, and related disorders. In an attempt to identify new AT1 receptor antagonists, a pharmacophore-based virtual screening protocol was applied. The pharmacophore models were generated from 30 training set compounds. The best model was chosen on the basis of squared correlation coefficient of training set and internal test set. The validity of the developed model was also ensured using catScramble validation method and external test set prediction.ResultsThe final model highlighted the importance of hydrogen bond acceptor, hydrophobic aliphatic, hydrophobic, and ring aromatic features. The model satisfied all the statistical criteria such as cost function analysis and correlation coefficient. The result of estimated activity for internal and external test set compounds reveals that the generated model has high prediction capability. The validated pharmacophore model was further used for mining of 56000 compound database (MiniMaybridge). Total 141 hits were obtained and all the hits were checked for druggability, this led to the identification of two active druggable AT1 receptor antagonists with diverse structure.ConclusionA highly validated pharmacophore model generated in this study identified two novel druggable AT1 receptor antagonists. The developed model can also be further used for mining of other virtual database.
Highlights
Angiotensin II (AII) receptors [type 1 (AT1) receptor antagonists are clinically effective drugs for the treatment of hypertension, cardiovascular, and related disorders
Hypothesis1 was identified as best pharmacophore model, since this hypothesis showed a cost difference of 20.17 between null cost 148.75 and total cost 128.58 satisfying the range recommended in the cost analysis of the catalyst procedure
The moderately active compounds 35e and 36e missed the HY feature while the lesser active compound 38e (Figure 7) missed the ring aromatic feature. These results revealed the importance of HY functionalities and ring aromatic feature in imparting good AT1 receptor antagonist activity
Summary
AT1 receptor antagonists are clinically effective drugs for the treatment of hypertension, cardiovascular, and related disorders. In an attempt to identify new AT1 receptor antagonists, a pharmacophorebased virtual screening protocol was applied. The pharmacophore models were generated from 30 training set compounds. In the absence of three-dimensional (3D) structure for AT1 receptor, a rational design of antagonists using a structure-based approach is not feasible [1]. For this reason, 3D pharmacophore models from the ligand-based approach are very useful for analyzing the ligand-receptor interactions. The development of a 3D-pharmacophore and its use in the virtual screening of the chemical databases appear to be a more relevant and time-saving approach. The construction of an accurate pharmacophore is a key objective in many drug discovery efforts
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