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.

A combined ligand and structure-based drug design approach provides a synergistic advantage over either methods performed individually. Present work bestows a good assembly of ligand and structure-based pharmacophore generation concept. Ligand-oriented study was accomplished by employing the HypoGen module of Catalyst in which we have translated the experimental findings into 3-D pharmacophore models by identifying key features (four point pharmacophore) necessary for interaction of the inhibitors with the active site of HIV-1 protease enzyme using a training set of 33 compounds belonging to the cyclic cyanoguanidines and cyclic urea derivatives. The most predictive pharmacophore model (hypothesis 1), consisting of four features, namely, two hydrogen bond acceptors and two hydrophobic, showed a correlation (r) of 0.90 and a root mean square of 0.71 and cost difference of 56.59 bits between null cost and fixed cost. The model was validated using CatScramble technique, internal and external test set prediction. In the second phase of our study, a structure-based five feature pharmacophore hypothesis was generated which signifies the importance of hydrogen bond donor, hydrogen bond acceptors and hydrophobic interaction between the HIV-1 protease enzyme and its inhibitors. This work has taken a significant step towards the full integration of ligand and structure-based drug design methodologies as pharmacophoric features retrieved from structure-based strategy complemented the features from ligand-based study hence proving the accuracy of the developed models. The ligand-based pharmacophore model was used in virtual screening of Maybridge and NCI compound database resulting in the identification of four structurally diverse druggable compounds with nM activities.

The quantitative structure activity relationship (QSAR) models were developed using multiple linear regression (MLR) and partial least square (PLS) for a set of 85 AT 1 receptor antagonists of hydantoin series. The MLR and PLS generated comparable models with good predictive ability and all the other statistical values, such as r, r 2 , r 2 ðcvÞ ; and F and s values, were satisfactory. The results obtained from this study indicate the importance of steric (K-alpha3), hydrophobic (log P, and total lipole), and total energy (Cosmic total energy) in determining the activity of AT 1 receptor antagonists. The results clearly explained that optimum hydrophobicity of substituent at R 2 position is favorable for the activity and presence of a substituent of particular size and shape on phenyl ring at R 3 position is essential for the activity. This information is pertinent to the further design of new AT 1 receptor antagonist containing the hydantoin nucleus.

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The study indicates that antihistaminic activity is largely explained by steric and electronic parameters. In line with parameters entered in the model some indolylpiperidines derivatives were designed with good antihistaminic properties and pharmacokinetic profiles.