Lessigiarska I, Cronin M T D, Worth A P, Dearden J C, Netzeva T I
ECVAM, Institute for Health and Consumer Protection, European Commission Joint Research Centre, TP 582, Via Enrico Fermi 1, 21020 Ispra, Italy.
SAR QSAR Environ Res. 2004 Jun;15(3):169-90. doi: 10.1080/10629360410001697771.
In the present study, structure-activity relationship (QSAR) models for the prediction of the toxicity to the bacterium Sinorhizobium meliloti have been developed, based on a data set of 140 compounds. The data set is highly heterogeneous both in terms of chemistry and mechanisms of toxic action. For deriving QSARs, chemicals were divided into groups according to mechanism of action and chemical structure. The QSARs derived are considered to be of moderate statistical quality. A baseline effect (relationship between the toxicity and logP), which can be related to non-polar narcosis, was observed. To explain toxicity greater than the baseline toxicity, other structural descriptors were used. The development of models for non-polar and polar narcosis had some success. It appeared that the toxicity of compounds acting by more specific mechanisms of toxic action is difficult to predict. A global QSAR was also developed, which had square of the correlation coefficient r2 = 0.53. A QSAR with reasonable statistical parameters was developed for the aliphatic compounds in the data set (r2 = 0.83). QSARs could not be obtained for the aromatic compounds as a group.
在本研究中，基于140种化合物的数据集，开发了用于预测对苜蓿中华根瘤菌毒性的构效关系（QSAR）模型。该数据集在化学性质和毒性作用机制方面具有高度的异质性。为了推导QSAR，根据作用机制和化学结构将化学品分为不同组。所推导的QSAR被认为具有中等统计质量。观察到一种可与非极性麻醉相关的基线效应（毒性与logP之间的关系）。为了解释大于基线毒性的毒性，使用了其他结构描述符。非极性和极性麻醉模型的开发取得了一些成功。似乎通过更特定毒性作用机制起作用的化合物的毒性难以预测。还开发了一个全局QSAR，其相关系数r2的平方 = 0.53。为数据集中的脂肪族化合物开发了具有合理统计参数的QSAR（r2 = 0.83）。作为一个整体，无法获得芳香族化合物的QSAR。
