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5-芳基-2,2-二烷基-4-苯基-3(2H)-呋喃酮衍生物作为选择性COX-2抑制剂的3D-QSAR CoMFA/CoMSIA研究

3D-QSAR CoMFA/CoMSIA studies on 5-aryl-2,2-dialkyl-4-phenyl-3(2H)-furanone derivatives, as selective COX-2 inhibitors.

作者信息

Puntambekar Devendra Sharad, Giridhar Rajani, Yadav Mange Ram

机构信息

Pharmacy Department, Faculty of Technology and Engineering, Kalabavan, India.

出版信息

Acta Pharm. 2006 Jun;56(2):157-74.

Abstract

Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were performed on a series of 5-aryl-2,2-dialkyl-4-phenyl-3(2H)-furanone derivatives, as selective cyclooxygenase-2 (COX-2) inhibitors. Ligand molecular superimposition on the template structure was performed by the atom/shape based root mean square fit and database alignment methods. Removal of three outliers from the initial training set of 49 molecules improved the predictivity of the model. The statistically significant model was established of 36 molecules, which were validated by a test set of ten compounds. The atom and shape based root mean square alignment (IV) yielded the best predictive CoMFA model [R2(cv) = 0.664, R2 (non-cross-validated square of correlation coefficient) = 0.916, F value = 47.341, R2(bs) = 0.947 with six components, standard error of prediction36 = 0.360 and standard error of estimate36 = 0.180] while the CoMSIA model yielded [R2(cv) = 0.777, R2 (non-cross-validated square of correlation coefficient) = 0.905, F value = 66.322, R2(bs) = 0.933 with four components, standard error of prediction36 = 0.282 and standard error of estimate36 = 0.185]. The contour maps obtained from 3D-QSAR studies were appraised for activity trends for the molecules analyzed. Results indicate that steric, electrostatic, hydrophobic (lipophilic) and hydrogen bond donor substituents play a significant role in COX-2 inhibitory activity and selectivity of the compounds. The data generated from the present study will further help design novel, potent and selective COX-2 inhibitors.

摘要

对一系列5-芳基-2,2-二烷基-4-苯基-3(2H)-呋喃酮衍生物进行了比较分子场分析(CoMFA)和比较分子相似性指数分析(CoMSIA),这些衍生物为选择性环氧化酶-2(COX-2)抑制剂。通过基于原子/形状的均方根拟合和数据库比对方法,将配体分子叠加到模板结构上。从最初的49个分子训练集中去除3个异常值,提高了模型的预测能力。建立了一个具有统计学意义的包含36个分子的模型,并用一个包含10种化合物的测试集进行了验证。基于原子和形状的均方根比对(IV)产生了最佳预测CoMFA模型[交叉验证相关系数的平方R2(cv)=0.664,非交叉验证相关系数的平方R2=0.916,F值=47.341,具有六个成分时的自举法R2(bs)=0.947,预测标准误差36=0.360,估计标准误差36=0.180],而CoMSIA模型产生[交叉验证相关系数的平方R2(cv)=0.777,非交叉验证相关系数的平方R2=0.905,F值=66.322,具有四个成分时的自举法R2(bs)=0.933,预测标准误差36=0.282,估计标准误差36=0.185]。对从3D-QSAR研究中获得的等高线图进行了分析,以评估所分析分子的活性趋势。结果表明,空间、静电、疏水(亲脂)和氢键供体取代基在化合物的COX-2抑制活性和选择性中起重要作用。本研究产生的数据将进一步有助于设计新型、高效和选择性的COX-2抑制剂。

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