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QSAR study for carcinogenicity in a large set of organic compounds.

机译:QSAR研究大量有机化合物的致癌性。

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摘要

In our continuing efforts to find out acceptable Absorption, Distribution, Metabolization, Elimination and Toxicity (ADMET) properties of organic compounds, we establish linear QSAR models for the carcinogenic potential prediction of 1464 compounds taken from the "Galvez data set", that include many marketed drugs. More than a thousand of geometry-independent molecular descriptors are simultaneously analyzed, obtained with the softwares E-Dragon and Recon. The variable subset selection method employed is the Replacement Method, and also the improved version Enhanced Replacement Method. The established models are properly validated through an external test set of compounds, and by means of the Leave-Group-Out Cross Validation method. In addition, we apply the Y-Randomization strategy and analyze the Applicability Domain of the developed model. Finally, we compare the results obtained in present study with the previous ones from the literature. The novelty of present work relies on the development of an alternative predictive structure-carcinogenicity relationship in a large heterogeneous set of organic compounds, by only using a reduced number of geometry independent molecular descriptors.
机译:在我们不断努力寻找有机化合物的可接受的吸收,分布,代谢,消除和毒性(ADMET)特性的过程中,我们建立了线性QSAR模型,用于根据“ Galvez数据集”对1464种化合物的致癌潜力进行预测。上市药品。使用软件E-Dragon和Recon可以同时分析上千种与几何无关的分子描述符。所采用的可变子集选择方法是替换方法,以及改进版本的增强替换方法。已建立的模型通过化合物的外部测试集以及“离开-分组-交叉验证”方法进行了正确验证。此外,我们应用Y随机化策略并分析了所开发模型的适用范围。最后,我们将本研究中获得的结果与文献中先前的结果进行比较。本研究的新颖性取决于仅通过使用数量减少的几何独立分子描述符,即可在一大批异质有机化合物中开发出一种替代的预测结构-致癌关系。

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