Quantitative structure - activity study on the reductivedehalogenation potency of the halogenated aromatics

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环境化学中有机化合物毒性的QSAR研究方法

定量结构—活性相关 (QSAR)研究具有重要的理论和实际意义。在前人大量相关研究的基础上分析了目前国内外普遍实用的七种QSAR研究方法 ,并讨论了各方法的优缺点及适用范围 ,以利于各方法的进一步推广。同时简要介绍了QSAR的发展趋势。     

Quantitative structure activity relationships for carp kidney ATPase endpoint

ＩｎｔｒｏｄｕｃｔｉｏｎＭｏｓｔｏｆｎｉｔｒｏａｒｏｍａｔｉｃｓａｒｅｉｍｐｏｒｔａｎｔｅｎｖｉｒｏｎｍｅｎｔａｌｐｏｌｌｕｔａｎｔｓ.ＴｈｅｃａｒｐｉｓｔｈｅｍａｊｏｒｅｃｏｎｏｍｉｃｆｉｓｈｉｎＣｈｉｎａａｎｄｉｓｏｎｅｏｆｔｈｅｆｉｖｅｓｔａｎ?..     

苯胺类化合物在不同pH值下对大型蚤的急性毒性及QSAR研究

测定了13种苯胺类化合物在不同pH下（6．0，7．8，9．0）对大型蚤（Daphnia magna)的24h半数活动抑制浓度24h-1C50，应用三种理化参数logP,TSA和pKa，对毒性数据进行了定量构效关系（QSARs)研究，并在此基础上初步探讨了苯胺类化合物的毒性机制。     

环境化学中的QSAR研究方法

环境化学中的定量结构-活性相关（QSAR）研究具有重要的理论和实际意义，介绍了QSAR方法的历史和发展过程，及QSAR方法的研究体系，同时对QSAR发展趋势进行了展望。     

预测有机化合物对水蚤EC50值的片段常数法

根据217种化合物建立了估算有机化合物对水蚤EC50值（48h半数影响浓度）的片段常数模型,分析了模型的误差及稳健性。研究结果表明,有机化合物的片段常数和结构因子与水蚤的EC50值倒数的对数（lg1/EC50)显著相关,可以根据片段常数法估算有机化合物对水蚤的EC50。模型的可决系数为0.9687,平均绝对误差0.40个对数单位,其中68.7%化合物的误差小于0.5个对数单位。     

Novel application of the CORAL software to model cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli

Convenient to apply and available on the Internet software CORAL (http://www.insilico.eu/CORAL) has been used to build up quantitative structure-activity relationships (QSAR) for prediction of cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli (minus logarithm of concentration for 50% effect pEC50). In this study six random splits of the data into the training and test set were examined. It has been shown that the CORAL provides a reliable tool that could be used to build up a QSAR of the pEC50.     

Peroxidase-mediated removal of endocrine disrupting compound mixtures from water

Several classes of oxidative enzymes have shown promise for efficient removal of endocrine disrupting compounds (EDCs) that are resistant to conventional wastewater treatments. Although the kinetics of reactions between individual EDCs and selected oxidative enzymes are well documented in the literature, there has been little investigation of reactions with EDC mixtures. This makes it impossible to predict how enzyme-mediated treatment systems will perform since wastewater effluents generally contain multiple EDCs. This paper reports pseudo-first order rate constants for a model oxidative enzyme, horseradish peroxidase (HRP), during single-substrate (k₁) and mixed-substrate (k_1-MIX) reactions. Measured values are compared with literature values of three Michaelis-Menten parameters: half-saturation constant (K_M), enzyme turnover number (k_CAT), and the ratio k_CAT/K_M. Published reports had suggested that each of these could be correlated with HRP reactivity towards EDCs in mixtures, and empirical results from this study show that K_M can be used to predict the sequence of EDC removal reactions within a particular mixture. We also observed that k_1-MIX values were generally greater than k₁ values and that compounds exhibiting greatest estrogenic toxicities reacted most rapidly in a given mixture. Finally, because K_M may be tedious to measure for every EDC of interest, we have constructed a quantitative structure-activity relationship (QSAR) model to predict these values. This model predicts K_M quite accurately (R² = 89%) based on two molecular characteristics: molecular volume and hydration energy. Its accuracy makes this QSAR a useful tool for predicting which EDCs will be removed most efficiently during enzyme treatment of EDC mixtures.