Comparative Molecular Field Analysis of Selective Cyclooxygenase‐2 (COX‐2) Inhibitors

C. Marot, P. Chavatte, D. Lesieur
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引用次数: 26

Abstract

The 3D-QSAR approach has been used to obtain informations about the active conformation of selective cyclo-oxygenase-2 (COX-2) inhibitors. In this paper, we have compared different combinations of two fields (steric and electrostatic) in order to optimize the 3D-QSAR models of selective COX-2 inhibitors. Assuming that all the compounds interact at the same binding site at the enzyme level, DuP697 pharmacophoric conformation served as a template for the superimposition of 54 structurally heterogeneous COX-2 inhibitors constituting both the training and test sets used to perform a 3D-QSAR study via the CoMFA method. A statistically significant model was obtained with 38 compounds of the training set (n=38, q2=0,70, N=3, r2=0,93, s=0,38, F=156) with steric and electrostatic relative contributions of 40% and 60%, respectively. The predictive power of the proposed model was discerned by successfully testing the 16 compounds constituting the test set. The so obtained and validated model brings important structural insights to aid the design of novel anti-inflammatory drugs prior to their synthesis.
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选择性环氧合酶2 (COX‐2)抑制剂的比较分子场分析
3D-QSAR方法已被用于获得选择性环氧化酶-2 (COX-2)抑制剂活性构象的信息。在本文中,我们比较了两种场(空间和静电)的不同组合,以优化选择性COX-2抑制剂的3D-QSAR模型。假设所有化合物在酶水平上在相同的结合位点相互作用,DuP697的药效构象作为54个结构异质COX-2抑制剂的叠加模板,构成了通过CoMFA方法进行3D-QSAR研究的训练集和测试集。训练集的38个化合物(n=38, q2=0,70, n=3, r2=0,93, s=0,38, F=156)的空间和静电相对贡献分别为40%和60%,得到了具有统计学意义的模型。通过成功测试构成测试集的16种化合物来识别所提出模型的预测能力。因此获得和验证的模型带来了重要的结构见解,以帮助在合成之前设计新的抗炎药物。
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