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Mechanism-based quantitative structure-activity relationships for the inhibition of substituted phenols on germination rate of Cucumis sativus

机译:基于机理的定量构效关系研究取代酚对黄瓜黄瓜萌发率的抑制

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Comparative inhibition activity (GC_(50)) of 42 structurally diverse substituted phenols on seed germination rate of Cucumis sativus was investigated. Quantitative structure-activity relationships (QSARs) were developed by using hy-drophobicity (1-octanol/water partition coefficient, log K_(ow)) and electrophilicity (the energy of the lowest unoccupied molecule orbital, E_(lumo)) for the toxicity of phenols according to their modes of toxic action. Most phenols elicited their response via a polar narcotic mechanism and a highly significant log K_(ow)-based model was obtained (GC_(50) = 0.92 log K_(ow) + 1.99, r~2 = 0.84, n = 29). The inclusion of E_(lumo) greatly improved the predictive power of the polar narcotic QSAR (GC_(50)= 0.88 log K_(ow) - 0.30E_(lumo) + 1.99, r~2 = 0.93, n = 29). pK_a proved to be an insignificant influencing factor in this study. Poor correlation with hydrophobicity and strong correlation with electrophilicity were observed for the nine bio-reactive chemicals. Their elevated toxicity was considerably underestimated by the polar narcotic log K_(ow)-dependent QSAR. The nine chemicals consist of selected nitro-substituted phenols, hydroquinone, catechol and 2-aminophenol. Their excess toxic potency could be explained by their molecular structure involving in vivo reaction with bio-macromolecules. Strong dissociation of carboxyl group of the four benzoic acid derivatives greatly decreased their observed toxicity. In an effort to model all chemicals including polar narcotics and bio-reactive chemicals, a response-surface analysis with the toxicity, logK_(ow) and E_(lumo) was performed. This resulted in a highly predictive two-parameter QSAR for most of the chemicals (GC_(50) = 0.70 logK_(ow) - 0.66E_(lumo) + 2.17, r~2 = 0.89, n = 36). Catechol and 2,4-dinitrophenol proved to be outliers of this model and their much high toxicity was explained.
机译:研究了42种结构多样的取代酚对黄瓜(Cucumis sativus)种子萌发率的比较抑制活性(GC_(50))。通过使用疏水性(1-辛醇/水分配系数,log K_(ow))和亲电性(最低未占据分子轨道的能量,E_(lumo))来建立定量构效关系(QSAR)根据它们的毒性作用方式大多数酚通过极性麻醉机制引起其反应,并获得了基于log K_(ow)的高度显着模型(GC_(50)= 0.92 log K_(ow)+ 1.99,r〜2 = 0.84,n = 29)。包含E_(lumo)极大地改善了极地麻醉QSAR的预测能力(GC_(50)= 0.88 log K_(ow)-0.30E_(lumo)+ 1.99,r〜2 = 0.93,n = 29)。在本研究中,pK_a被证明是无关紧要的影响因素。观察到九种生物活性化学物质与疏水性的相关性较差,而与亲电性的相关性强。极性麻醉药log K_(ow)依赖性QSAR大大低估了它们的毒性。九种化学物质由选定的硝基取代酚,对苯二酚,邻苯二酚和2-氨基酚组成。它们的过量毒性潜力可以通过涉及与生物大分子的体内反应的分子结构来解释。四种苯甲酸衍生物的羧基强烈解离,大大降低了它们的毒性。为了模拟所有化学药品,包括极性麻醉药和生物活性化学药品,进行了毒性,logK_(ow)和E_(lumo)响应面分析。这对大多数化学品产生了高度预测性的两参数QSAR(GC_(50)= 0.70 logK_(ow)-0.66E_(lumo)+ 2.17,r〜2 = 0.89,n = 36)。儿茶酚和2,4-二硝基苯酚被证明是该模型的异常值,并解释了它们的高毒性。

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