查看更多>>摘要：Phenolic contaminants pose a significant threat to both environmental and human health due to their hazardous nature and resistance to degradation. These contaminants are commonly found in industrial waste streams, and if released into the environment without proper treatment, they can cause grave harm to both human and aquatic life. Several methods are reported regarding treatment of phenolic contaminants found in industrial effluent each having their own advantages and disadvantages, e.g., biological treatment, which employs microorganisms, is an eco-friendly and cost-effective approach; although it necessitates precise regulation of environmental parameters, chemical oxidation method involves the use of oxidizing agents such as hydrogen peroxide or ozone to degrade the contaminants, but it can be expensive procedure. Physical adsorption method involves the use of activated carbon or other adsorbents to adsorb the contaminants from the effluent have to be regenerated and reused, making this method cost-effective in the long run. The treatment of phenolic contaminants from industrial effluent is a complex and challenging task. Protox-Ⅱ is a software program that was used to predict the toxicity of phenol and natural phenols based on their chemical structure. Software program uses a range of algorithms to estimate the toxicity of a substance, including its LD50 value and toxic classes. In this study, we have predicted the binding affinities (in kcal/mol) and the binding mode (orientation and conformation) of the ligand in the binding site of the protein of different phenolic substrates to polyphenol oxidase enzyme using in silico studies by using AutoDock Vina. For validation, in vitro degradation studies of phenol were performed where artificial industrial effluent comprising of different phenolic substrates was incubated with polyphenol oxidase enzymes of select underground vegetables. The rate of phenol degradation was measured using spectrophotometry. Natural polyphenols Mangiferin and Juglone appear to be highly toxic (Class I) with predicted LD50 dose 2 mg/per kg of body weight and 3 mg/per kg of body weight, respectively. Binding affinity of various substrates with polyphenol oxidase enzyme is in the following order: Amentoflavone ＞ Mangiferin ＞ Piceatannol ＞ Resveratrol ＞ Caffeic acid ＞ Napthol ＞ Umbelliferone ＞ Gallic acid ＞ Coumarin ＞ Pyrogallol ＞ Catechol ＞ Phenol. A comparison study was done to check for polyphenol oxidase enzyme activity in the peels of (Lagenaria siceraria, Solanum tuberosum, Musa paradisiaca, Colocasia esculenta, Amorphophallus paeoniifolius, Raphanus Sativus, Lufa acutangular) was studied for presence of polyphenol oxidase enzyme activity. Amorphophallus paeoniifolius showed the highest enzyme activity of 1790 U/ml/min followed by Colocasia esculenta, Lufa acutangular, Musa paradisiaca with enzyme activity 1290 U/ml/min, 1084.7 U/ml/ min, 740 U/ml/min, respectively. Lagenaria siceraria (Bottle gourd) showed the highest phenol concentration degradation from 20.7 to 0.56 ug. Polyphenol oxidase enzyme from agro-waste can serve as an effective bioremediation agent for the treatment of phenolic wastewater generated by various industries. Fusion of bioinformatics and biochemical techniques will help in better understanding of the rate of enzyme substrate reaction, which compound is more likely to get degraded first. The strength of the binding affinity between molecules can also affect the stability of the immobilization. Our findings highlighted the importance of Bioinformatics tool on remediation rate, providing new insights into designing strategies of immobilization while carefully considering binding affinity between two molecules. Lastly, we present our viewpoint on the obstacles and potential avenues for future investigation in the enzymatic breakdown of phenol.
NETL
NSTL
Springer Nature