摘要
Computing chemistry was applied to understand biotransforrnation mechanism of an organochlorine pesticide, endosulfan. The stereo specific metabolic activity of human CYP-2B6 （cytochrome P450） on endosulfan has been well demonstrated. Sequence and structural similarity search revealed that the bacterium Bacillus megaterium encodes CYP-BM3, which is similar to CYP-2B6. The functional similarity was studied at organism level by batch-scale studies and it was proved that B. megaterium could metabolize endosulfan to endosulfan sulfate, as CYP-2B6 does in human system. The gene expression analyses also confirmed the possible role of CYP-BM3 in endosulfan metabolism. Thus, our results show that the protein structure based in-silico approach can help us to understand and identify microbes for remediation strategy development. To the best of our knowledge this is the first report which has extrapolated the bacterial gene for endosulfan biotransformation through in silico prediction approach for metabolic gene identification.
Computing chemistry was applied to understand biotransforrnation mechanism of an organochlorine pesticide, endosulfan. The stereo specific metabolic activity of human CYP-2B6 （cytochrome P450） on endosulfan has been well demonstrated. Sequence and structural similarity search revealed that the bacterium Bacillus megaterium encodes CYP-BM3, which is similar to CYP-2B6. The functional similarity was studied at organism level by batch-scale studies and it was proved that B. megaterium could metabolize endosulfan to endosulfan sulfate, as CYP-2B6 does in human system. The gene expression analyses also confirmed the possible role of CYP-BM3 in endosulfan metabolism. Thus, our results show that the protein structure based in-silico approach can help us to understand and identify microbes for remediation strategy development. To the best of our knowledge this is the first report which has extrapolated the bacterial gene for endosulfan biotransformation through in silico prediction approach for metabolic gene identification.
基金
supported by the Council for Scientific and Industrial Research (CSIR) under Network mode NWP-19(1.3)
