关键词: BADGE Biotransformation Box Behnken Design Endocrine disruptor Machine learning model Molecular docking Thermophilic laccases

Mesh : Biodegradation, Environmental Laccase / metabolism Geobacillus stearothermophilus / enzymology Geobacillus / enzymology Benzhydryl Compounds / metabolism Phenols / metabolism Epoxy Compounds / metabolism

来  源:   DOI:10.1007/s11356-024-34095-y

Abstract:
Bisphenol A diglycidyl ether (BADGE), a derivative of the well-known endocrine disruptor Bisphenol A (BPA), is a potential threat to long-term environmental health due to its prevalence as a micropollutant. This study addresses the previously unexplored area of BADGE toxicity and removal. We investigated, for the first time, the biodegradation potential of laccase isolated from Geobacillus thermophilic bacteria against BADGE. The laccase-mediated degradation process was optimized using a combination of response surface methodology (RSM) and machine learning models. Degradation of BADGE was analyzed by various techniques, including UV-Vis spectrophotometry, high-performance liquid chromatography (HPLC), Fourier transform infrared (FTIR) spectroscopy, and gas chromatography-mass spectrometry (GC-MS). Laccase from Geobacillus stearothermophilus strain MB600 achieved a degradation rate of 93.28% within 30 min, while laccase from Geobacillus thermoparafinivorans strain MB606 reached 94% degradation within 90 min. RSM analysis predicted the optimal degradation conditions to be 60 min reaction time, 80°C temperature, and pH 4.5. Furthermore, CB-Dock simulations revealed good binding interactions between laccase enzymes and BADGE, with an initial binding mode selected for a cavity size of 263 and a Vina score of -5.5, which confirmed the observed biodegradation potential of laccase. These findings highlight the biocatalytic potential of laccases derived from thermophilic Geobacillus strains, notably MB600, for enzymatic decontamination of BADGE-contaminated environments.
摘要:
双酚A二缩水甘油醚(BADGE),众所周知的内分泌干扰物双酚A(BPA)的衍生物,由于其作为微污染物的普遍存在,因此对长期环境健康构成潜在威胁。这项研究解决了以前未开发的BADGE毒性和去除领域。我们调查了,第一次,从嗜热地芽孢杆菌中分离的漆酶对BADGE的生物降解潜力。使用响应面方法(RSM)和机器学习模型的组合来优化漆酶介导的降解过程。通过各种技术分析了BADGE的降解,包括紫外-可见分光光度法,高效液相色谱(HPLC),傅里叶变换红外(FTIR)光谱,和气相色谱-质谱(GC-MS)。嗜热脂肪土芽孢杆菌MB600的漆酶在30min内降解率为93.28%,而来自热parafinivorans地芽孢杆菌菌株MB606的漆酶在90分钟内降解达到94%。RSM分析预测最佳降解条件为60min反应时间,温度80°C,和pH4.5。此外,CB-Dock模拟揭示了漆酶和BADGE之间良好的结合相互作用,对于263的腔大小和-5.5的Vina评分选择初始结合模式,这证实了所观察到的漆酶的生物降解潜力。这些发现突出了来自嗜热地芽孢杆菌菌株的漆酶的生物催化潜力,特别是MB600,用于对BADGE污染的环境进行酶净化。
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