Investigation of fragment based quantitative regression on a series of substituted chromen-2-one derivatives as FXa inhibitors

Santosh S. Kumbhar, P. Choudhari, M. Bhatia
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Abstract

ABSTRACT Factor Xa (FXa), a trypsin-like serine protease, is well-established target for the development of the anticoagulants. Number of molecules were reported as Factor Xa inhibitors but most of them have pharmacokinetic issues. In this present communication, we report development and validation of the group based quantitative structure activity relationship (GQSAR) studies on 48 chromen-2-one derivatives as effective inhibitors of FXa. All the molecules were fragmented into eleven functional fragments (R1, R2, R3, R4, R5, R6, R7, R8, R9, R10 and R11).  All the developed GQSAR models were generated using multiple linear regressions analysis (MLR). The generated GQSAR models were selected on the basis of statistical data that models having r 2 should be above 0.6 were used to check the external predictivity while the significance of the model was decided on the basis of F value. Developed GQSAR models reveled presence of lipophilic groups on fragment R6 will diminish the bio-activity while at R2 it will lead to increase in bioactivity of molecules. Additionally, minimum number of rotatable bonds at fragments R1 was fruitful for better FXa inhibition activity. The results of GQSAR models may lead to better understanding of design and development of novel FXa inhibitors.
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基于片段的定量回归研究一系列取代的2- 1 -染色质衍生物作为FXa抑制剂
Xa因子(FXa)是一种胰蛋白酶样丝氨酸蛋白酶,是开发抗凝血药物的公认靶点。许多分子被报道为Xa因子抑制剂,但大多数具有药代动力学问题。在本文中,我们报告了基于基团的定量结构活性关系(GQSAR)研究的发展和验证,这些研究表明48种染色质-2- 1衍生物是FXa的有效抑制剂。所有分子被分割成11个功能片段(R1、R2、R3、R4、R5、R6、R7、R8、R9、R10和R11)。所有建立的GQSAR模型均采用多元线性回归分析(MLR)生成。根据统计数据选择生成的GQSAR模型,使用r 2大于0.6的模型检查外部预测性,根据F值确定模型的显著性。建立的GQSAR模型显示,在R6片段上存在亲脂基团会降低分子的生物活性,而在R2片段上存在亲脂基团会导致分子的生物活性增加。此外,片段R1上的最小可旋转键数有助于提高FXa抑制活性。GQSAR模型的结果可能有助于更好地理解新型FXa抑制剂的设计和开发。
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