预测酰基辅酶A:胆固醇o -酰基转移酶抑制活性:使用拓扑描述符的计算方法。

Drug design and discovery Pub Date : 2003-01-01
Viney Lather, A K Madan
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引用次数: 0

摘要

研究了氨基磺酰基脲的拓扑指标与酰基辅酶A:胆固醇o -酰基转移酶(ACAT)抑制活性的关系。本研究使用了三个拓扑指数,即Wiener指数(基于距离的拓扑描述符)、分子连通性指数(基于邻接的拓扑描述符)和偏心连通性指数(基于邻接和距离的拓扑描述符)。一个包含41个取代(氨基磺酰基)脲类似物的数据集被选择用于本研究。使用内部计算机程序计算了组成数据集的41种化合物的维纳指数、偏心连通性指数和分子连通性指数。对所得数据进行了分析,并在确定活动范围后建立了合适的模型。随后,利用这些模型为每种化合物分配生物活性,然后将其与体外报道的ACAT抑制活性进行比较。发现使用这些模型的预测精度从最小约83%到最大约91%不等。
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Predicting acyl-coenzyme A: cholesterol O-acyltransferase inhibitory activity: computational approach using topological descriptors.

Relationship between the topological indices and acyl-coenzyme A:cholesterol O-acyltransferase (ACAT) inhibitory activity of (aminosulfonyl)ureas has been investigated. Three topological indices, Wiener's index--a distance-based topological descriptor, molecular connectivity index--an adjacency-based topological index, and eccentric connectivity index--an adjacency-cum-distance-based topological descriptor, were used for the present investigations. A data set comprising 41 analogues of substituted (aminosulfonyl)ureas was selected for the present studies. The values of wiener's index, eccentric connectivity index, and molecular connectivity index for each of the 41 compounds comprising the data set were computed using an in-house computer program. Resultant data were analyzed and suitable models were developed after identification of active ranges. Subsequently, a biological activity was assigned to each compound using these models, which was then compared with the reported in vitro ACAT inhibitory activity. Accuracy of prediction using these models was found to vary from a minimum of approximately 83% to a maximum of approximately 91%.

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