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Structure-activity Relationship Analysis of N-Benzoylpyrazoles for Elastase Inhibitory Activity: A Simplified Approach Using Atom Pair Descriptors

机译:N-苯并吡唑类化合物对弹性蛋白酶抑制活性的构效关系分析:使用原子对描述符的简化方法

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摘要

Previously, we utilized high throughput screening of a chemical diversity library to identify potent inhibitors of human neutrophil elastase and found that many of these compounds had N-benzoylpyrazole core structures. We also found individual ring substituents had significant impact on elastase inhibitory activity and compound stability. In the present study, we utilized computational structure–activity relationship (SAR) analysis of a series of 53 N-benzoylpyrazole derivatives to further optimize these lead molecules. We present an improved approach to SAR methodology based on atom pair descriptors in combination with 2-dimentional (2D) molecular descriptors. This approach utilizes the rich representation of chemical structure and leads to SAR analysis that is both accurate and intuitively easy to understand. A sequence of ANOVA, linear discriminant, and binary classification tree analyses of the molecular descriptors led to the derivation of SAR rule-based algorithms. These rules revealed that the main factors influencing elastase inhibitory activity of N-benzoylpyrazole molecules were the presence of methyl groups in the pyrazole moiety and ortho-substituents in the benzoyl radical. Furthermore, our data showed that physicochemical characteristics (energy of frontier molecular orbitals, molar refraction, lipophilicity) were not necessary for achieving good SAR, as comparable quality of SAR classification was obtained with atom pairs and 2D descriptors only. This simplified SAR approach may be useful to qualitative SAR recognition problems in a variety of data sets.
机译:以前,我们利用化学多样性文库的高通量筛选来鉴定人嗜中性粒细胞弹性蛋白酶的有效抑制剂,发现其中许多化合物具有N-苯甲酰基吡唑核心结构。我们还发现单个环取代基对弹性蛋白酶的抑制活性和化合物稳定性具有重要影响。在本研究中,我们利用了一系列53种N-苯甲酰基吡唑衍生物的计算结构-活性关系(SAR)分析来进一步优化这些铅分子。我们提出了一种基于原子对描述符与二维(2D)分子描述符相结合的SAR方法的改进方法。这种方法利用了化学结构的丰富表示,并导致SAR分析既准确又直观易懂。分子描述符的一系列方差分析,线性判别和二元分类树分析导致了基于SAR规则的算法的推导。这些规则表明,影响N-苯甲酰基吡唑分子的弹性蛋白酶抑制活性的主要因素是吡唑部分中甲基的存在和苯甲酰基中的邻位取代基的存在。此外,我们的数据表明,获得良好的SAR不需要理化特性(前沿分子轨道的能量,摩尔折射,亲脂性),因为仅通过原子对和2D描述子即可获得可比的SAR分类质量。这种简化的SAR方法对于各种数据集中的定性SAR识别问题可能很有用。

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