{"title":"基于DFT的分子描述符预测鱼类中多氯联苯的生物富集因子","authors":"A. Soni, Pratibha Singh, V. K. Sahu","doi":"10.4236/abc.2020.101001","DOIUrl":null,"url":null,"abstract":"Experimental determination of BCFs is expensive and demanding if \nperformed correctly. Because of this, measuring the BCFs of many thousands of \nchemical substances that are potential regulatory interest is simply not \npossible. Hence, prediction of BCFs of the PCBs based on QSAR were made time to time to \nincrease the probability of success and reduce the time and cost in exploring \nthe toxicological and ecological characteristics of molecules. DFT methods are, \nin general, capable of generating a variety of isolated molecular descriptors \nas well as local reactivity descriptors quite accurately. In this work, \nprediction of BCFs of the fifty seven PCBs based on quantum chemical \ndescriptors derived from DFT method using the B88-PW91 GGA energy function with \nthe DZVP basis set have been made. The study concluded that dipole moment and ionization \npotential are reliable descriptors for correlation of bioconcentration factors \nof polychlorinated biphenyls with their electronic \nstructures. The resulted QSAR model (r2 = 0.9139, \n = 0.8986, k = 2, SE = \n0.2668) can be useful for predicting the BCFs of compounds prior to their \nsynthesis.","PeriodicalId":59114,"journal":{"name":"生物化学进展(英文)","volume":"10 1","pages":"1-15"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"DFT-Based Prediction of Bioconcentration Factors of Polychlorinated Biphenyls in Fish Species Using Molecular Descriptors\",\"authors\":\"A. Soni, Pratibha Singh, V. K. Sahu\",\"doi\":\"10.4236/abc.2020.101001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Experimental determination of BCFs is expensive and demanding if \\nperformed correctly. Because of this, measuring the BCFs of many thousands of \\nchemical substances that are potential regulatory interest is simply not \\npossible. Hence, prediction of BCFs of the PCBs based on QSAR were made time to time to \\nincrease the probability of success and reduce the time and cost in exploring \\nthe toxicological and ecological characteristics of molecules. DFT methods are, \\nin general, capable of generating a variety of isolated molecular descriptors \\nas well as local reactivity descriptors quite accurately. In this work, \\nprediction of BCFs of the fifty seven PCBs based on quantum chemical \\ndescriptors derived from DFT method using the B88-PW91 GGA energy function with \\nthe DZVP basis set have been made. The study concluded that dipole moment and ionization \\npotential are reliable descriptors for correlation of bioconcentration factors \\nof polychlorinated biphenyls with their electronic \\nstructures. The resulted QSAR model (r2 = 0.9139, \\n = 0.8986, k = 2, SE = \\n0.2668) can be useful for predicting the BCFs of compounds prior to their \\nsynthesis.\",\"PeriodicalId\":59114,\"journal\":{\"name\":\"生物化学进展(英文)\",\"volume\":\"10 1\",\"pages\":\"1-15\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"生物化学进展(英文)\",\"FirstCategoryId\":\"1089\",\"ListUrlMain\":\"https://doi.org/10.4236/abc.2020.101001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"生物化学进展(英文)","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.4236/abc.2020.101001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
如果操作正确,实验测定BCFs是昂贵和苛刻的。正因为如此,测量数千种具有潜在监管利益的化学物质的BCFs根本是不可能的。因此,基于QSAR对多氯联苯的BCFs进行预测,增加了成功的概率,减少了探索分子毒理学和生态学特性的时间和成本。一般来说,DFT方法能够相当准确地生成各种孤立分子描述符以及局部反应性描述符。本文采用DFT方法,利用B88-PW91 GGA能量函数和DZVP基集,对57种多氯联苯的BCFs进行了基于量子化学描述子的预测。研究表明,偶极矩和电离势是多氯联苯生物富集因子与其电子结构相关性的可靠描述符。所建立的QSAR模型(r2 = 0.9139, = 0.8986, k = 2, SE = 0.2668)可用于预测化合物合成前的BCFs。
DFT-Based Prediction of Bioconcentration Factors of Polychlorinated Biphenyls in Fish Species Using Molecular Descriptors
Experimental determination of BCFs is expensive and demanding if
performed correctly. Because of this, measuring the BCFs of many thousands of
chemical substances that are potential regulatory interest is simply not
possible. Hence, prediction of BCFs of the PCBs based on QSAR were made time to time to
increase the probability of success and reduce the time and cost in exploring
the toxicological and ecological characteristics of molecules. DFT methods are,
in general, capable of generating a variety of isolated molecular descriptors
as well as local reactivity descriptors quite accurately. In this work,
prediction of BCFs of the fifty seven PCBs based on quantum chemical
descriptors derived from DFT method using the B88-PW91 GGA energy function with
the DZVP basis set have been made. The study concluded that dipole moment and ionization
potential are reliable descriptors for correlation of bioconcentration factors
of polychlorinated biphenyls with their electronic
structures. The resulted QSAR model (r2 = 0.9139,
= 0.8986, k = 2, SE =
0.2668) can be useful for predicting the BCFs of compounds prior to their
synthesis.