Quantitative structure–activity relationship for the partition coefficient of hydrophobic compounds between silicone oil and air

Quantitative structure–activity relationship for the partition coefficient of hydrophobic... The silicon oil-air partition coefficients (K SiO/A) of hydrophobic compounds are vital parameters for applying silicone oil as non-aqueous-phase liquid in partitioning bioreactors. Due to the limited number of K SiO/A values determined by experiment for hydrophobic compounds, there is an urgent need to model the K SiO/A values for unknown chemicals. In the present study, we developed a universal quantitative structure–activity relationship (QSAR) model using a sequential approach with macro-constitutional and micromolecular descriptors for silicone oil-air partition coefficients (K SiO/A) of hydrophobic compounds with large structural variance. The geometry optimization and vibrational frequencies of each chemical were calculated using the hybrid density functional theory at the B3LYP/6-311G** level. Several quantum chemical parameters that reflect various intermolecular interactions as well as hydrophobicity were selected to develop QSAR model. The result indicates that a regression model derived from logK SiO/A, the number of non-hydrogen atoms (#nonHatoms) and energy gap of E LUMO and E HOMO (E LUMO–E HOMO) could explain the partitioning mechanism of hydrophobic compounds between silicone oil and air. The correlation coefficient R 2 of the model is 0.922, and the internal and external validation coefficient, Q 2 LOO and Q 2 ext , are 0.91 and 0.89 respectively, implying that the model has satisfactory goodness-of-fit, robustness, and predictive ability and thus provides a robust predictive tool to estimate the logK SiO/A values for chemicals in application domain. The applicability domain of the model was visualized by the Williams plot. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Environmental Science and Pollution Research Springer Journals

Quantitative structure–activity relationship for the partition coefficient of hydrophobic compounds between silicone oil and air

10 pages
Read Article

Loading next page...
 
/lp/springer_journal/quantitative-structure-activity-relationship-for-the-partition-FjsR3IA9dl
Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2018 by Springer-Verlag GmbH Germany, part of Springer Nature
Subject
Environment; Environment, general; Environmental Chemistry; Ecotoxicology; Environmental Health; Atmospheric Protection/Air Quality Control/Air Pollution; Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution
ISSN
0944-1344
eISSN
1614-7499
D.O.I.
10.1007/s11356-018-1705-z
Publisher site
See Article on Publisher Site

Abstract

The silicon oil-air partition coefficients (K SiO/A) of hydrophobic compounds are vital parameters for applying silicone oil as non-aqueous-phase liquid in partitioning bioreactors. Due to the limited number of K SiO/A values determined by experiment for hydrophobic compounds, there is an urgent need to model the K SiO/A values for unknown chemicals. In the present study, we developed a universal quantitative structure–activity relationship (QSAR) model using a sequential approach with macro-constitutional and micromolecular descriptors for silicone oil-air partition coefficients (K SiO/A) of hydrophobic compounds with large structural variance. The geometry optimization and vibrational frequencies of each chemical were calculated using the hybrid density functional theory at the B3LYP/6-311G** level. Several quantum chemical parameters that reflect various intermolecular interactions as well as hydrophobicity were selected to develop QSAR model. The result indicates that a regression model derived from logK SiO/A, the number of non-hydrogen atoms (#nonHatoms) and energy gap of E LUMO and E HOMO (E LUMO–E HOMO) could explain the partitioning mechanism of hydrophobic compounds between silicone oil and air. The correlation coefficient R 2 of the model is 0.922, and the internal and external validation coefficient, Q 2 LOO and Q 2 ext , are 0.91 and 0.89 respectively, implying that the model has satisfactory goodness-of-fit, robustness, and predictive ability and thus provides a robust predictive tool to estimate the logK SiO/A values for chemicals in application domain. The applicability domain of the model was visualized by the Williams plot.

Journal

Environmental Science and Pollution Research – Springer Journals

Published: Mar 25, 2018

References

  • Gaseous hexane biodegradation by Fusarium solani in two liquid phase packed-bed and stirred-tank bioreactors
    Arriaga, S; Muñoz, R; Hernández, S; Guieysse, B; Revah, S
  • Quantitative structure-property relationship studies on n-octanol/water partitioning coefficients of PCDD/Fs
    Chen, J; Quan, X; Zhao, Y; Yan, YYF
  • Quantitative structure-property relationships for octanol-air partition coefficients of polychlorinated biphenyls
    Chen, J; Xue, X; Schramm, KW; Quan, X; Yang, F; Kettrup, A
  • Biological waste air treatment in biotrickling filters
    Cox, HH; Deshusses, MA
  • Two-phase partitioning bioreactors: a new technology platform for destroying xenobiotics
    Daugulis, AJ
  • How not to develop a quantitative structure-activity or structure-property relationship (QSAR/QSPR)
    Dearden, JC; Cronin, MTD; Kaiser, KLE
  • Determination of partition coefficients of three volatile organic compounds (dimethylsulphide, dimethyldisulphide and toluene) in water/silicone oil mixtures
    Dumont, E; Darracq, G; Couvert, A; Couriol, C; Amrane, A; Thomas, D; Andrès, Y; le Cloirec, P
  • Volumetric mass transfer coefficients characterising VOC absorption in water/silicone oil mixtures
    Dumont, E; Darracq, G; Couvert, A; Couriol, C; Amrane, A; Thomas, D; Andrès, Y; le Cloirec, P
  • Using theoretical descriptors in quantitative structure activity relationships: some physicochemical properties
    Famini, GR; Penski, CA; Wilson, L
  • Study on amphipathic modification and QSAR of volatile turpentine analogues as value-added botanical fungicides against crop-threatening pathogenic fungi
    Gao, Y; Tian, X; Li, J; Shang, S; Song, Z; Shen, M
  • Biotechnology: a highly efficient tool for the current environmental challenges
    García-Galán, MJ; Uggetti, E; Garfi, M; Olguín, EJ; García, J; Puigagut, J
  • Microbial degradation of phenanthrene and pyrene in a two-liquid phase-partitioning bioreactor
    Guieysse, B; Mattiasson, CB
  • Structure-activity analysis of harmful algae inhibition by congeneric compounds: case studies of fatty acids and thiazolidinediones
    Huang, H; Xiao, X; Shi, J; Chen, Y
  • QSAR applicabilty domain estimation by projection of the training set descriptor space: a review
    Jaworska, J; Nikolova, N; Aldenberg, T
  • Quantum-chemical descriptors in QSAR/QSPR studies
    Karelson, M; Lobanov, VS; Katritzky, AR
  • Review of mass transfer aspects for biological gas treatment
    Kraakman, NJR; Rocha-Rios, J; Loosdrecht, MCM
  • Removal of polycyclic aromatic hydrocarbons from contaminated soil in a two-phase partitioning bioreactor
    Lee, JY; Kwon, TS; Lee, YC
  • Field determination and QSPR prediction of equilibrium-status soil/vegetation partition coefficient of PCDD/Fs
    Li, L; Wang, Q; Qiu, X; Dong, Y; Jia, S; Hu, J
  • QSAR studies of bioconcentration factors of polychlorinated biphenyls (PCBs) using DFT, PCS and CoMFA
    Liu, H; Liu, H; Sun, P; Wang, Z
  • Development of TLSER model and QSAR model for predicting partition coefficients of hydrophobic organic chemicals between low density polyethylene film and water
    Liu, H; Wei, M; Yang, X; Yin, C; He, X
  • Combined removal of a BTEX, TCE, and cis-DCE mixture using Pseudomonas sp. immobilized on scrap tyres
    Lu, Q; Toledo, RA; Xie, F; Li, J; Shim, H
  • Mechanistic insight into reactivity of sulfate radical with aromatic contaminants through single-electron transfer pathway
    Luo, S; Wei, Z; Dionysiou, DD; Spinney, R; Hu, WP; Chai, L; Yang, Z; Ye, T; Xiao, R
  • A novel model to predict gas–phase hydroxyl radical oxidation kinetics of polychlorinated compounds
    Luo, S; Wei, Z; Spinney, R; Yang, Z; Chai, L; Xiao, R
  • Quantitative structure–activity relationships for reactivities of sulfate and hydroxyl radicals with aromatic contaminants through single–electron transfer pathway
    Luo, S; Wei, Z; Spinney, R; Villamena, FA; Dionysiou, DD; Chen, D; Tang, CJ; Chai, L; Xiao, R
  • UV direct photolysis of sulfamethoxazole and ibuprofen: an experimental and modelling study
    Luo, S; Wei, Z; Spinney, R; Zhang, Z; Dionysiou, DD; Gao, L; Chai, L; Wang, D; Xiao, R
  • Development and evaluation of predictive model for bovine serum albumin-water partition coefficients of neutral organic chemicals
    Ma, G; Yuan, Q; Yu, H; Lin, H; Chen, J; Hong, H
  • Oxygen mass transfer and shear stress effects on Pseudomonas putida BCRC 14365 growth to improve bioreactor design and performance
    Moradkhani, H; Izadkhah, MS; Anarjan, N; Abdi, A
  • Biorefinery
    Ohara, H
  • Assessment of methane biodegradation kinetics in two-phase partitioning bioreactors by pulse respirometry
    Ordaz, A; López, JC; Figueroa-González, I; Muñoz, R; Quijano, G
  • Determination and correlation of the partition coefficients of 48 volatile organic and environmentally relevant compounds between air and silicone oil
    Patel, MJ; Popat, SC; Deshusses, MA
  • Environmental biotechnology and engineering: crucial tools for improving and caring for the environment and the quality of life of modern societies
    Poggi-Varaldo, HM; Devault, DA; Macarie, H; Sastre-Conde, I
  • Simultaneous biodegradation of volatile and toxic contaminant mixtures by solid-liquid two-phase partitioning bioreactors
    Poleo, EE; Daugulis, AJ
  • Enhanced styrene removal in a two-phase partitioning bioreactor operated as a biotrickling filter: towards full-scale applications
    San-Valero, P; Gabaldón, C; Penya-roja, JM; Quijano, G
  • Biotrickling filter modeling for styrene abatement. Part 2: simulating a two-phase partitioning bioreactor
    San-Valero, P; Dorado, AD; Quijano, G; Álvarez-Hornos, FJ; Gabaldón, C
  • QSAR models for removal rates of organic pollutants adsorbed by in situ formed manganese dioxide under acid condition
    Su, P; Zhu, H; Shen, Z
  • QSAR models for oxidation of organic micropollutants in water based on ozone and hydroxyl radical rate constants and their chemical classification
    Sudhakaran, S; Amy, GL
  • A new combined green method for 2-Chlorophenol removal using cross-linked Brassica rapa peroxidase in silicone oil
    Tandjaoui, N; Abouseoud, M; Couvert, A; Amrane, A; Tassist, A
  • Application of quantum chemical descriptor in quantitative structure activity and structure property relationship
    Thanikaivelan, P; Subramanian, V; Rao, JR; Nair, BU
  • The importance of being earnest: validation is the absolute essential for successful application and interpretation of QSPR models
    Tropsha, A; Gramatica, P; Gombar, V
  • SIFT-MS analysis of the removal of dimethyl sulphide, n-hexane and toluene from waste air by a two phase partitioning bioreactor
    Volckaert, D; Ebude, DEL; Langenhove, H
  • Structural determination of paraffin boiling points
    Wiener, H
  • Quantitative structure-activity relationship (QSAR) for the oxidation of trace organic contaminants by sulfate radical
    Xiao, R; Ye, T; Wei, Z; Luo, S; Yang, Z; Spinney, R
  • Mechanistic insight into degradation of endocrine disrupting chemical by hydroxyl radical: an experimental and theoretical approach
    Xiao, R; Gao, L; Wei, Z; Spinney, R; Luo, S; Wang, D; Dionysiou, DD; Tang, C–J; Yang, W
  • Experimental and QSPR study of sorption properties of polychlorinated diphenyl sulfides (PCDPSs) in Yangtze River plain soil
    Yang, F; Qu, R; Wang, M; Tang, Y; Feng, M; Wang, Z
  • Rate constants of hydroxyl radical oxidation of polychlorinated biphenyls in the gas phase: a single− descriptor based QSAR and DFT study
    Yang, Z; Luo, S; Wei, Z; Ye, T; Spinney, R; Chen, D; Xiao, R
  • Comparison of the reactivity of ibuprofen with sulfate and hydroxyl radicals: an experimental and theoretical study
    Yang, Z; Su, R; Luo, S; Spinney, R; Cai, M; Xiao, R; Wei, Z
  • Chemical structure-based predictive model for the oxidation of trace organic contaminants by sulfate radical
    Ye, T; Wei, Z; Spinney, R; Tang, CJ; Luo, S; Xiao, R; Dionysiou, DD
  • Quantitative structure–activity relationship for the apparent rate constants of aromatic contaminants oxidized by ferrate (VI)
    Ye, T; Wei, Z; Spinney, R; Dionysiou, DD; Luo, S; Chai, L; Yang, Z; Xiao, R

You’re reading a free preview. Subscribe to read the entire article.

Try 2 weeks free now

DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

or browse the journals available

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off

Sign up
for free
Start 14 day
Free Trial