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合成大麻素:通过定量构效关系模型对大麻素受体1亲和力的计算机模拟预测

Synthetic cannabinoids: In silico prediction of the cannabinoid receptor 1 affinity by a quantitative structure-activity relationship model.

作者信息

Paulke Alexander, Proschak Ewgenij, Sommer Kai, Achenbach Janosch, Wunder Cora, Toennes Stefan W

机构信息

Institute of Legal Medicine, University of Frankfurt/Main, Kennedyallee 104, D-60596 Frankfurt/Main, Germany.

Institute of Pharmaceutical Chemistry, University of Frankfurt/Main, Max-von-Laue Straße 9, D-60438 Frankfurt/Main, Germany.

出版信息

Toxicol Lett. 2016 Mar 14;245:1-6. doi: 10.1016/j.toxlet.2016.01.001. Epub 2016 Jan 12.

DOI:10.1016/j.toxlet.2016.01.001
PMID:26795018
Abstract

The number of new synthetic psychoactive compounds increase steadily. Among the group of these psychoactive compounds, the synthetic cannabinoids (SCBs) are most popular and serve as a substitute of herbal cannabis. More than 600 of these substances already exist. For some SCBs the in vitro cannabinoid receptor 1 (CB1) affinity is known, but for the majority it is unknown. A quantitative structure-activity relationship (QSAR) model was developed, which allows the determination of the SCBs affinity to CB1 (expressed as binding constant (Ki)) without reference substances. The chemically advance template search descriptor was used for vector representation of the compound structures. The similarity between two molecules was calculated using the Feature-Pair Distribution Similarity. The Ki values were calculated using the Inverse Distance Weighting method. The prediction model was validated using a cross validation procedure. The predicted Ki values of some new SCBs were in a range between 20 (considerably higher affinity to CB1 than THC) to 468 (considerably lower affinity to CB1 than THC). The present QSAR model can serve as a simple, fast and cheap tool to get a first hint of the biological activity of new synthetic cannabinoids or of other new psychoactive compounds.

摘要

新型合成精神活性化合物的数量稳步增加。在这类精神活性化合物中,合成大麻素(SCBs)最为流行,并可作为草药大麻的替代品。目前已存在600多种此类物质。对于一些SCBs,其体外大麻素受体1(CB1)亲和力是已知的,但大多数情况下是未知的。我们开发了一种定量构效关系(QSAR)模型,该模型无需参考物质即可确定SCBs对CB1的亲和力(以结合常数(Ki)表示)。化学先进模板搜索描述符用于化合物结构的向量表示。使用特征对分布相似度计算两个分子之间的相似度。使用反距离加权法计算Ki值。通过交叉验证程序对预测模型进行验证。一些新型SCBs的预测Ki值在20(对CB1的亲和力远高于四氢大麻酚(THC))至468(对CB1的亲和力远低于THC)之间。当前的QSAR模型可作为一种简单、快速且廉价的工具,用于初步了解新型合成大麻素或其他新型精神活性化合物的生物活性。

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