{"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}
引用次数: 2
Abstract
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.