Department of Civil and Environmental Engineering, University of Virginia, P.O. Box 400742, Charlottesville, VA 22904-4742, USA.
Chemosphere. 2011 Oct;85(4):553-7. doi: 10.1016/j.chemosphere.2011.06.064. Epub 2011 Jul 8.
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 (k1-MIX) reactions. Measured values are compared with literature values of three Michaelis-Menten parameters: half-saturation constant (KM), enzyme turnover number (kCAT), and the ratio kCAT/KM. 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 KM can be used to predict the sequence of EDC removal reactions within a particular mixture. We also observed that k1-MIX values were generally greater than k1 values and that compounds exhibiting greatest estrogenic toxicities reacted most rapidly in a given mixture. Finally, because KM 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 KM 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.
几类氧化酶已显示出高效去除内分泌干扰化合物(EDCs)的潜力,这些化合物对传统废水处理具有抗性。尽管文献中详细记录了个别 EDC 与选定氧化酶之间的反应动力学,但对 EDC 混合物的反应研究甚少。这使得无法预测酶介导的处理系统将如何表现,因为废水排放通常含有多种 EDC。本文报告了模型氧化酶辣根过氧化物酶(HRP)在单底物(k1)和混合底物(k1-MIX)反应中的拟一级速率常数。测量值与文献中三种米氏常数参数的值进行了比较:半饱和常数(KM)、酶转换数(kCAT)和 kCAT/KM 的比值。已发表的报告表明,这些参数中的每一个都可以与混合物中 HRP 对 EDC 的反应性相关联,本研究的经验结果表明,KM 可用于预测特定混合物中 EDC 去除反应的顺序。我们还观察到,k1-MIX 值通常大于 k1 值,并且表现出最大雌激素毒性的化合物在给定混合物中反应最快。最后,由于 KM 对于每个感兴趣的 EDC 可能都很繁琐,因此我们构建了一个定量结构-活性关系(QSAR)模型来预测这些值。该模型基于两个分子特征(分子体积和水合能)非常准确地预测 KM(R2=89%)。其准确性使这种 QSAR 成为预测在酶处理 EDC 混合物过程中哪些 EDC 将被最有效地去除的有用工具。