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Prediction of No Observed Adverse Effect Concentration for inhalation toxicity using Monte Carlo approach
SAR and QSAR in Environmental Research ( IF 3 ) Pub Date : 2020-11-12 , DOI: 10.1080/1062936x.2020.1841827
A.A. Toropov 1 , A.P. Toropova 1 , G. Selvestrel 1 , D. Baderna 1 , E. Benfenati 1
Affiliation  

ABSTRACT

Ideal correlation is one variable model based on so-called optimal descriptors calculated with simplified molecular input-line entry systems (SMILES). The optimal descriptor is calculated according to the index of ideality of correlation, a new criterion of predictive potential of quantitative structure–property/activity relationships (QSPRs/QSARs). The aim of the present study was the building and estimation of models for inhalation toxicity as No Observed Adverse Effect Concentration (NOAEC) based on the OECD guidelines 413. Three random distributions into the training set and validation set were examined. In practice, a structured training set that contains active training set, passive training set and calibration set is used as the training set. The statistical characteristics of the best model for negative logarithm of NOAEC (pNOAEC) are for training set n = 108, average r 2 = 0.52 + 0.62 + 0.76/3 = 0.63 and for validation set n = 35, r 2 = 0.73.



中文翻译:

使用蒙特卡洛方法预测吸入毒性的未观察到的有害作用浓度

摘要

理想相关是一种基于变量的模型,该变量基于使用简化的分子输入线输入系统(SMILES)计算的所谓最佳描述符。最佳描述符是根据相关性的理想性指标计算的,该指标是定量结构的预测潜力的新标准—物性/活性关系(QSPRs / QSARs)。本研究的目的是建立和评估基于OECD指南413的吸入毒性模型,即未观察到不利影响浓度(NOAEC)。检查了训练集中和验证集中的三个随机分布。实际上,包含主动训练集,被动训练集和校准集的结构化训练集被用作训练集。n = 108,平均值r 2  = 0.52 + 0.62 + 0.76 / 3 = 0.63,对于验证集n = 35,r 2  = 0.73。

更新日期:2020-11-25
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