首页> 外文期刊>Journal of Mathematical Chemistry >QSAR analysis of 1,4-dihydro-4-oxo-1-(2-thiazolyl)-1,8-naphthyridines exhibiting anticancer activity by optimal SMILES-based descriptors
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QSAR analysis of 1,4-dihydro-4-oxo-1-(2-thiazolyl)-1,8-naphthyridines exhibiting anticancer activity by optimal SMILES-based descriptors

机译:基于最佳SMILES的描述符对具有抗癌活性的1,4-二氢-4-氧-1-(2-噻唑基)-1,8-萘啶进行QSAR分析

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摘要

A predictive model of the anticarcinogenic activity of a 1,4-dihydro-4-oxo-1-(2-thiazolyl)-1,8-naphthyridines series has been built, with statistical quality: n = 75, r 2 = 0.7688, s = 0.48, F = 243 (training set); n = 25, r 2 = 0.8025, s = 0,49, F = 93 (test set). The robustness of this model has been tested in three random splits into training set and test set. Correlation weights (the analogue of the contributions of substituents) of molecular attributes expressed by symbols in the simplified molecular input line entry system (SMILES) notation are able to serve as informative indicators in the search for new anticancer agents. Keywords SMILES - QSAR - Optimal descriptor - Anticancer activity
机译:建立了1,4-二氢-4-氧代-1-(2-噻唑基)-1,8-萘啶系列抗癌活性的预测模型,其统计质量为:n = 75,r 2 = 0.7688,s = 0.48,F = 243(训练组); n = 25,r 2 = 0.8025,s = 0.49,F = 93(测试集)。该模型的鲁棒性已经在训练集和测试集的三个随机分割中进行了测试。用简化的分子输入线输入系统(SMILES)表示法中的符号表示的分子属性的相关权重(取代基的类似物)可以用作寻找新的抗癌药的信息性指标。关键词SMILES-QSAR-最佳描述词-抗癌活性

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