Abstract
Insecticides are the toxic substances that are used to kill insects. The use of insecticides is believed to be one of the major factors behind the increase in agricultural productivity in the 20th century. The organophosphates are now the largest and most versatile class of insecticide used and Malathion is the predominant type utilized. The accumulation of Malathion in environment is the biggest threat to the environment because of its toxicity. Malathion is lethal to beneficial insects, snails, micro crustaceans, fish, birds, amphibians, and soil microorganisms. Chronic exposure of non-diabetic farmers to organophosphorus Malathion pesticides may induce insulin resistance, which might ultimately results in diabetes mellitus. Given the potential carcinogenic risk from the pesticides there is serious need to develop remediation processes to eliminate or minimize contamination in the environment. Biodegradation could be a reliable and cost effective technique for pesticide abatement. Since today as there were no metabolic pathway predicted for the degradation of organophosphates pesticide Malathion in KEGG database or in any of the other pathway databases. Thus in the present study, an attempt has been made to predict the microbial biodegradation pathway of Malathion using bioinformatics tools. The present study predicted the degradation pathway for Malathion. The present study also identifies, Streptomyces sp. and E.coli are capable of degrading Malathion through pathway prediction system.
Highlights
The pathway is a series of consecutive enzymatic reactions that produce specific products
Pathways prediction tools are gaining momentum, since this approach is proven to be fruitful in several biodegradation studies and reduced considerable money and time spent on wet lab research [1]
The canonical smile of Malathion was obtained from pubchem structure search and the biodegradation pathway of Malathion was predicted using EAWAG-BBD pathway prediction system
Summary
The pathway is a series of consecutive enzymatic reactions that produce specific products. Predictions use biotransformation rules based on reactions found in the EAWAG-BBD database or in the scientific literature. PPS predictions are most accurate for the compounds that are similar to compounds whose biodegradation pathways are reported in the scientific literature; in environments exposed to air, in moist soil/or water, at moderate temperature and pH with no competing chemicals or toxins; and the sole source of energy, carbon, hydrogen or other essential element for the microbes in these environments, rather than present in trace amounts. Pathways prediction tools are gaining momentum, since this approach is proven to be fruitful in several biodegradation studies and reduced considerable money and time spent on wet lab research [1]
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