{"title":"毒死蜱及其降解物作为人谷胱甘肽S-转移酶抑制剂的计算前景:DFT计算、分子对接研究和MD模拟","authors":"Nikita Tiwari , Anil Mishra","doi":"10.1016/j.comtox.2023.100264","DOIUrl":null,"url":null,"abstract":"<div><p>Chlorpyrifos is the toxicant chemical from the class of organophosphorus insecticides. The insecticide undergoes environmental degradation to chlorpyrifos‐oxon (CPYO), des‐ethyl chlorpyrifos (DEC), 3,5,6‐trichloro‐2‐methoxypyridine (TMP) and 3,5,6‐trichloro‐2‐pyridinol (TCP). Herein, CPF along with its degradants were optimized employing density functional theory (DFT) and B3LYP/6-311G+(d,p) basis set to elucidate their thermal and frontier molecular orbital properties. The DFT outcome revealed that TCP showed the lowest HOMO-LUMO gap (4.38 eV), also highest dipole moment, electrophilicity index and basicity. Docking was done using AutoDock 4.2.6 against human glutathione S-transferases to search binding affinity and interactions of all pollutants with the protein. The docking results expressed that TCP required least binding energy (−5.51 kcal mol<sup>−1</sup>) which is relatable to the DFT studies and might act as the most powerful inhibitor. GROMACS 5.1.1 was utilized to perform simulation studies for each ligand–protein docked complexes. Results concluded that CPF, DEC, TMP, CPYO and TCP could possibly perform as toxic and inhibit enzymatic activity by interrupting the metabolic pathways in humans.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Computational perspectives on Chlorpyrifos and its degradants as human glutathione S-transferases inhibitors: DFT calculations, molecular docking study and MD simulations\",\"authors\":\"Nikita Tiwari , Anil Mishra\",\"doi\":\"10.1016/j.comtox.2023.100264\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Chlorpyrifos is the toxicant chemical from the class of organophosphorus insecticides. The insecticide undergoes environmental degradation to chlorpyrifos‐oxon (CPYO), des‐ethyl chlorpyrifos (DEC), 3,5,6‐trichloro‐2‐methoxypyridine (TMP) and 3,5,6‐trichloro‐2‐pyridinol (TCP). Herein, CPF along with its degradants were optimized employing density functional theory (DFT) and B3LYP/6-311G+(d,p) basis set to elucidate their thermal and frontier molecular orbital properties. The DFT outcome revealed that TCP showed the lowest HOMO-LUMO gap (4.38 eV), also highest dipole moment, electrophilicity index and basicity. Docking was done using AutoDock 4.2.6 against human glutathione S-transferases to search binding affinity and interactions of all pollutants with the protein. The docking results expressed that TCP required least binding energy (−5.51 kcal mol<sup>−1</sup>) which is relatable to the DFT studies and might act as the most powerful inhibitor. GROMACS 5.1.1 was utilized to perform simulation studies for each ligand–protein docked complexes. Results concluded that CPF, DEC, TMP, CPYO and TCP could possibly perform as toxic and inhibit enzymatic activity by interrupting the metabolic pathways in humans.</p></div>\",\"PeriodicalId\":37651,\"journal\":{\"name\":\"Computational Toxicology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2023-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Toxicology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468111323000051\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"TOXICOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Toxicology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468111323000051","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TOXICOLOGY","Score":null,"Total":0}
Computational perspectives on Chlorpyrifos and its degradants as human glutathione S-transferases inhibitors: DFT calculations, molecular docking study and MD simulations
Chlorpyrifos is the toxicant chemical from the class of organophosphorus insecticides. The insecticide undergoes environmental degradation to chlorpyrifos‐oxon (CPYO), des‐ethyl chlorpyrifos (DEC), 3,5,6‐trichloro‐2‐methoxypyridine (TMP) and 3,5,6‐trichloro‐2‐pyridinol (TCP). Herein, CPF along with its degradants were optimized employing density functional theory (DFT) and B3LYP/6-311G+(d,p) basis set to elucidate their thermal and frontier molecular orbital properties. The DFT outcome revealed that TCP showed the lowest HOMO-LUMO gap (4.38 eV), also highest dipole moment, electrophilicity index and basicity. Docking was done using AutoDock 4.2.6 against human glutathione S-transferases to search binding affinity and interactions of all pollutants with the protein. The docking results expressed that TCP required least binding energy (−5.51 kcal mol−1) which is relatable to the DFT studies and might act as the most powerful inhibitor. GROMACS 5.1.1 was utilized to perform simulation studies for each ligand–protein docked complexes. Results concluded that CPF, DEC, TMP, CPYO and TCP could possibly perform as toxic and inhibit enzymatic activity by interrupting the metabolic pathways in humans.
期刊介绍:
Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs