Bhongade Bhoomendra A, Gouripur Veerappa V, Gadad Andanappa K
Department of Medicinal Chemistry, College of Pharmacy, J. N. Medical College, Belgaum 590 010, Karnataka, India.
Bioorg Med Chem. 2005 Apr 15;13(8):2773-82. doi: 10.1016/j.bmc.2005.02.027.
A series of indole/benzoimidazole-5-carboxamidines have been reported to inhibit various trypsin-like serine proteases viz. uPA, tPA, factor Xa, thrombin, plasmin, and trypsin, which are involved in various types of pathophysiological conditions such as cancer progression, thrombosis etc. Inhibition of these protease enzymes may serve as therapeutic agents in various types of cancer as well serve as anticoagulant or antithrombotic agents. The dual inhibitory action may result in poor clinical candidates. 3D-QSAR models were generated for indole/benzoimidazole-5-carboxamidines using the CoMFA technique to study their selectivity trends toward various trypsin-like serine proteases. Molecular superimposition was carried out on the template structure using atom-based RMS fit method. The CoMFA models were established from the training set of 25-29 molecules and validated by predicting the activities of seven-eight test set molecules. The CoMFA models generated using steric and electrostatic fields for tPA, fXa, thrombin, plasmin, and trypsin inhibition exhibited better statistical significance than the CoMFA models generated using ClogP as an additional descriptor. Thus, the validated CoMFA models with steric and electrostatic fields were used to generate 3D contour maps, which may provide possible modification of molecules for better selectivity/activity. The present 3D-QSAR studies emphasize the selectivity trends of indole/benzoimidazole-5-carboxamidines, which may be obliging in designing novel selective serine protease inhibitors of therapeutic interest.
据报道,一系列吲哚/苯并咪唑-5-甲脒可抑制多种类胰蛋白酶丝氨酸蛋白酶,即尿激酶型纤溶酶原激活剂(uPA)、组织型纤溶酶原激活剂(tPA)、凝血因子Xa、凝血酶、纤溶酶和胰蛋白酶,这些酶参与多种病理生理状况,如癌症进展、血栓形成等。抑制这些蛋白酶可作为多种癌症的治疗药物,也可作为抗凝剂或抗血栓剂。这种双重抑制作用可能导致临床候选药物不佳。使用比较分子场分析法(CoMFA)技术生成了吲哚/苯并咪唑-5-甲脒的3D-QSAR模型,以研究它们对各种类胰蛋白酶丝氨酸蛋白酶的选择性趋势。使用基于原子的均方根拟合方法对模板结构进行分子叠加。CoMFA模型由25 - 29个分子的训练集建立,并通过预测七八个测试集分子的活性进行验证。使用空间场和静电场生成的针对tPA、fXa、凝血酶、纤溶酶和胰蛋白酶抑制的CoMFA模型,比使用ClogP作为附加描述符生成的CoMFA模型具有更好的统计学意义。因此,使用经过验证的具有空间场和静电场的CoMFA模型生成3D等高线图,这可能为分子的可能修饰提供依据,以实现更好的选择性/活性。目前的3D-QSAR研究强调了吲哚/苯并咪唑-5-甲脒的选择性趋势,这可能有助于设计具有治疗意义的新型选择性丝氨酸蛋白酶抑制剂。