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首页> 外文期刊>Journal of Hazardous Materials >Biodegradation of malachite green by a novel laccase-mimicking multicopper BSA-Cu complex: Performance optimization, intermediates identification and artificial neural network modeling
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Biodegradation of malachite green by a novel laccase-mimicking multicopper BSA-Cu complex: Performance optimization, intermediates identification and artificial neural network modeling

机译:新型漆壳模仿多电囊BSA-Cu复合物的孔雀石绿色生物降解:性能优化,中间体识别和人工神经网络建模

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摘要

In this work, a soluble biopolymer was prepared by conjugating the bovine serum albumin (BSA) with transition metal ion (Cu2+). BSA-Cu complex was synthesized and characterized using UV-vis absorption, fluorescence and ATR-FTIR spectroscopies. A colorimetric guaiacol oxidation based method, was used to study the catalytic activity of complex and the results indicated its laccase-like activity. Compared with laccase, BSA-Cu complex showed a higher K-m value and a similar V-max value at the same mass concentration. Also, the ability of the BSA Cu complex to decolorize malachite green (MG) was tested and the results showed that the complex was able to complete the decolorization process of MG within 30 min. Using gas chromatography/mass spectrometry (GC-MS) the resultant metabolites of MG degradation were analyzed and the toxicity of degradation products was assessed against Escherichia coli and Bacillus subtilis. The results confirmed the formation of less toxic products after degradation of MG by BSA-Cu complex. To predict the decolorization efficiency (DE%) of MG, an artificial neural network (ANN) was designed with five, five and one neurons in the input, hidden and output layers, respectively. The obtained results showed the ability of the designed ANN to predict MG removal successfully.
机译:在这项工作中,通过用过渡金属离子(Cu2 +)将牛血清白蛋白(BSA)缀合来制备可溶性生物聚合物。合成BSA-Cu复合物,使用UV-Vis吸收,荧光和ATR-FTIR光谱表征。基于比色愈缩玉米氧化方法,用于研究复合物的催化活性,结果表明其漆酶状活性表示。与漆酶相比,BSA-Cu络合物显示出较高的K-M值和相同质量浓度的类似V-MAX值。此外,测试了BSA Cu复合物以脱色孔雀石绿(Mg)的能力,结果表明该复合物能够在30分钟内完成Mg的脱色过程。使用气相色谱/质谱/质谱(GC-MS)分析了Mg降解的所得代谢物,并评估了对大肠杆菌和枯草芽孢杆菌的降解产物的毒性。结果证实了BSA-Cu复合物降解Mg后形成较小的毒性产物。为了预测MG的脱色效率(DE%),分别设计了一种人工神经网络(ANN),分别设计了输入,隐藏和输出层中的五个,五个和一个神经元。所获得的结果表明,设计的ANN预测成功去除Mg的能力。

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