Drug Discov Ther. 2012;6(2):69-77. (DOI: 10.5582/ddt.2012.v6.2.69)

In silico ligand based design of indolylpiperidinyl derivatives as novel histamine H1 receptor antagonists.

Paliwal S, Singh S, Pal M


Histamine H1 receptor antagonists play a vital role in the first line treatment of a broad range of allergic diseases. Frequent dosing of the antagonist results in side effects like sedation and cardiovascular toxicity. The present study highlights the important structural requirement and mechanistic interpretation of novel indolylpiperidinyl derivatives as H1 receptor antagonists so as to facilitate the design of newer antihistaminics with increased duration of action and comparatively reduced side effects. The significance of the developed quantitative structure-activity relationship (QSAR) models were evaluated on the basis of statistical values of square of correlation coefficient (r2); (multiple linear regression (MLR), 0.86; and partial least squares (PLS), 0.85). The predictive ability of the resulting QSAR models was evaluated with cross-validated correlation coefficient (r2cv) values (MLR, 0.82; PLS, 0.82) generated for the training set and r2 values (MLR, 0.763; PLS, 0.855) derived for test set. The final models comprised of multidimensional steric (verloop length, verloop B3), electronic (total dipole moment) and steric (KAlpha1 index) descriptors. 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.

KEYWORDS: Quantitative structure-activity relationship (QSAR), tools for structure activity relationship (TSAR), multiple linear regression (MLR), partial least square (PLS)

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