Paliwal S, Singh S, Pal M
Department of Pharmacy, Banasthali University, Banasthali, Rajasthan, India.
Drug Discov Ther. 2012 Apr;6(2):69-77.
Histamine H(1) 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 H(1) 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 (r(2)); (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 (r(2)cv) values (MLR, 0.82; PLS, 0.82) generated for the training set and r(2) values (MLR, 0.763; PLS, 0.855) derived for test set. The final models comprised of multidimensional steric (verloop length, verloop B(3)), 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.
组胺H(1)受体拮抗剂在多种过敏性疾病的一线治疗中发挥着至关重要的作用。频繁给药拮抗剂会导致诸如镇静和心血管毒性等副作用。本研究强调了新型吲哚基哌啶基衍生物作为H(1)受体拮抗剂的重要结构要求和机理解释，以便于设计出作用时间延长且副作用相对减少的新型抗组胺药。基于相关系数平方（r(2)）的统计值评估了所建立的定量构效关系（QSAR）模型的意义；（多元线性回归（MLR），0.86；偏最小二乘法（PLS），0.85）。用为训练集生成的交叉验证相关系数（r(2)cv）值（MLR，0.82；PLS，0.82）和为测试集得出的r(2)值（MLR，0.763；PLS，0.855）评估所得QSAR模型的预测能力。最终模型由多维空间（Verloop长度、Verloop B(3)）、电子（总偶极矩）和空间（KAlpha1指数）描述符组成。该研究表明，抗组胺活性在很大程度上由空间和电子参数解释。根据模型中输入的参数，设计了一些具有良好抗组胺特性和药代动力学特征的吲哚基哌啶衍生物。
