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预测6-芳基苯甲腈的抗HIV-1活性:使用超增强偏心连接拓扑化学指数的计算方法。

Predicting anti-HIV-1 activity of 6-arylbenzonitriles: computational approach using superaugmented eccentric connectivity topochemical indices.

作者信息

Dureja Harish, Gupta Sunil, Madan A K

机构信息

Faculty of Pharmaceutical Sciences, MD University, Rohtak 124 001, India.

出版信息

J Mol Graph Model. 2008 Feb;26(6):1020-9. doi: 10.1016/j.jmgm.2007.08.008. Epub 2007 Aug 31.

Abstract

Highly discriminating adjacency-cum-distance based topochemical indices termed as superaugmented eccentric connectivity topochemical indices for quantitative structure-activity and structure-property relationships (QSAR/QSPR) have been conceptualized in the present study. These indices were found to exhibit high sensitivity towards the presence and relative position of heteroatom(s), exceptionally high discriminating power and negligible degeneracy for all possible structures of five vertices containing one heteroatom. Utility of these indices was investigated for development of models for prediction of anti-human immunodeficiency virus (HIV)-1 activity using a data set comprising 81 differently substituted 6-arylbenzonitriles. The values of the superaugmented eccentric connectivity topochemical indices of all the analogues comprising the data set were computed using an in-house computer program. The resultant data was analyzed and suitable models were developed after identification of the active ranges. Subsequently, a biological activity was assigned to each analogue using these models which was then compared with the reported anti-HIV-1 activity. The accuracy of prediction was found to be approximately 81% for all the three topochemical models. High sensitivity towards presence and relative position of heteroatom(s), exceptionally high discriminating power amalgamated with low degeneracy offer proposed topochemical indices vast potential for isomer discrimination, similarity/dissimilarity, drug design, quantitative structure-activity/structure-property relationships, lead optimization and combinatorial library design.

摘要

本研究提出了一种基于邻接和距离的高分辨拓扑化学指数,称为超增强偏心连接拓扑化学指数,用于定量构效关系和构性关系(QSAR/QSPR)。对于含一个杂原子的所有可能的五元结构,这些指数对杂原子的存在和相对位置表现出高灵敏度、极高的分辨能力和可忽略的简并性。利用包含81种不同取代的6-芳基苯腈的数据集,研究了这些指数在建立抗人类免疫缺陷病毒(HIV)-1活性预测模型中的应用。使用内部计算机程序计算了数据集中所有类似物的超增强偏心连接拓扑化学指数值。对所得数据进行分析,并在确定活性范围后建立合适的模型。随后,使用这些模型为每个类似物指定生物活性,然后将其与报道的抗HIV-1活性进行比较。发现所有三种拓扑化学模型的预测准确率约为81%。对杂原子的存在和相对位置的高灵敏度、极高的分辨能力以及低简并性相结合,为所提出的拓扑化学指数在异构体鉴别、相似性/不相似性、药物设计、定量构效/构性关系、先导优化和组合库设计方面提供了巨大潜力。

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