Saurabh Samuchiwal, Abhishek Sahu, Koushalya Selvaraju, Shubha Singh, Anushree Malik
{"title":"揭示普氏假单胞菌偶氮还原酶高效脱色纺织品活性染料的机制:一项室内研究。","authors":"Saurabh Samuchiwal, Abhishek Sahu, Koushalya Selvaraju, Shubha Singh, Anushree Malik","doi":"10.1080/07391102.2024.2308768","DOIUrl":null,"url":null,"abstract":"<p><p>The textile industry utilizing affordable azo dyes is a high threat to aquatic life and causes environmental problems due to their toxicity. Biodegradation of azo dyes employing microbes and enzymes has proved to be an efficient method for treating industrial effluent. This study used the novel microbial consortium to decolorize reactive azo dyes (Reactive Red 120; Reactive Black 5 and Reactive Blue 13), and its azo-reductase activity was evaluated. The metagenomic analysis of the consortium identified azo-reductase-producing bacterial species. The molecular docking revealed that <i>Pp</i>AzoR from <i>Pseudomonas putida</i> had the highest binding affinities for all the three dyes such as Reactive Black 5 (-9.3 kcal/mol), Reactive Blue 13 (-9.8 kcal/mol) and Reactive Red 120 (-10.7 kcal/mol). The structural rigidity and stability of the docked complex were confirmed through MD simulations evaluated across multiple descriptors from the simulation trajectories. Further, MMPBSA analysis validated the results that binding of the ligands, i.e. dye molecules Reactive Black (RB5), Reactive Blue (RB13) and Reactive Red (RR120) binding with the Azoreductase (<i>Pp</i>AzoR) to the screened Azo-dyes was spontaneous. Based on molecular dynamics simulations for 100 ns, RR 120 showed the highest binding affinity (-411.336 ± 46.799 KJ/mol), followed by RB5 (-288.012 ± 33.371 KJ/mol). The dyes (RR120 and RB5) exhibited stable interactions with the target azoreductase (<i>Pp</i>AzoR). The present study provides insights that <i>Pp</i>AzoR shows the highest decolorization potency, which could be interpreted as a potential dye-degrading protein based on dye-degrading assay findings.</p>","PeriodicalId":15272,"journal":{"name":"Journal of Biomolecular Structure & Dynamics","volume":" ","pages":"5164-5177"},"PeriodicalIF":2.7000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unveiling the azo-reductase mechanism in <i>Pseudomonas putida</i> for efficient decolorization of textile Reactive dyes: an <i>in-silico</i> study.\",\"authors\":\"Saurabh Samuchiwal, Abhishek Sahu, Koushalya Selvaraju, Shubha Singh, Anushree Malik\",\"doi\":\"10.1080/07391102.2024.2308768\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The textile industry utilizing affordable azo dyes is a high threat to aquatic life and causes environmental problems due to their toxicity. Biodegradation of azo dyes employing microbes and enzymes has proved to be an efficient method for treating industrial effluent. This study used the novel microbial consortium to decolorize reactive azo dyes (Reactive Red 120; Reactive Black 5 and Reactive Blue 13), and its azo-reductase activity was evaluated. The metagenomic analysis of the consortium identified azo-reductase-producing bacterial species. The molecular docking revealed that <i>Pp</i>AzoR from <i>Pseudomonas putida</i> had the highest binding affinities for all the three dyes such as Reactive Black 5 (-9.3 kcal/mol), Reactive Blue 13 (-9.8 kcal/mol) and Reactive Red 120 (-10.7 kcal/mol). The structural rigidity and stability of the docked complex were confirmed through MD simulations evaluated across multiple descriptors from the simulation trajectories. Further, MMPBSA analysis validated the results that binding of the ligands, i.e. dye molecules Reactive Black (RB5), Reactive Blue (RB13) and Reactive Red (RR120) binding with the Azoreductase (<i>Pp</i>AzoR) to the screened Azo-dyes was spontaneous. Based on molecular dynamics simulations for 100 ns, RR 120 showed the highest binding affinity (-411.336 ± 46.799 KJ/mol), followed by RB5 (-288.012 ± 33.371 KJ/mol). The dyes (RR120 and RB5) exhibited stable interactions with the target azoreductase (<i>Pp</i>AzoR). 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Unveiling the azo-reductase mechanism in Pseudomonas putida for efficient decolorization of textile Reactive dyes: an in-silico study.
The textile industry utilizing affordable azo dyes is a high threat to aquatic life and causes environmental problems due to their toxicity. Biodegradation of azo dyes employing microbes and enzymes has proved to be an efficient method for treating industrial effluent. This study used the novel microbial consortium to decolorize reactive azo dyes (Reactive Red 120; Reactive Black 5 and Reactive Blue 13), and its azo-reductase activity was evaluated. The metagenomic analysis of the consortium identified azo-reductase-producing bacterial species. The molecular docking revealed that PpAzoR from Pseudomonas putida had the highest binding affinities for all the three dyes such as Reactive Black 5 (-9.3 kcal/mol), Reactive Blue 13 (-9.8 kcal/mol) and Reactive Red 120 (-10.7 kcal/mol). The structural rigidity and stability of the docked complex were confirmed through MD simulations evaluated across multiple descriptors from the simulation trajectories. Further, MMPBSA analysis validated the results that binding of the ligands, i.e. dye molecules Reactive Black (RB5), Reactive Blue (RB13) and Reactive Red (RR120) binding with the Azoreductase (PpAzoR) to the screened Azo-dyes was spontaneous. Based on molecular dynamics simulations for 100 ns, RR 120 showed the highest binding affinity (-411.336 ± 46.799 KJ/mol), followed by RB5 (-288.012 ± 33.371 KJ/mol). The dyes (RR120 and RB5) exhibited stable interactions with the target azoreductase (PpAzoR). The present study provides insights that PpAzoR shows the highest decolorization potency, which could be interpreted as a potential dye-degrading protein based on dye-degrading assay findings.
期刊介绍:
The Journal of Biomolecular Structure and Dynamics welcomes manuscripts on biological structure, dynamics, interactions and expression. The Journal is one of the leading publications in high end computational science, atomic structural biology, bioinformatics, virtual drug design, genomics and biological networks.