RESEARCH ARTICLE
Quantitative structure–activity relationship for the partition coefficient
of hydrophobic compounds between silicone oil and air
Yanfei Qu
1
&
Yongwen Ma
1,2,3
&
Jinquan Wan
1,2,3
&
Yan Wang
1,2
Received: 28 January 2018 / Accepted: 6 March 2018 /Published online: 25 March 2018
#
Springer-Verlag GmbH Germany, part of Springer Nature 2018
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 hydro-
phobic 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 interac-
tions 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
)couldexplain
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.
Keywords Hydrophobic compounds
.
Silicone oil-air partition coefficients (K
SiO/A
)
.
Quantitative structure–activity relationship
(QSAR)
.
Density functional theory (DFT)
Introduction
The environmental biotechnology is concerned with the ap-
plication of biotechnology in many contexts, including the
treatment of pollutants, biorefineries, ensuring the health of
the environment through biomonitoring, and genetic engineer-
ing (Poggi-Varaldo et al. 2017)(Ohara 2003) (García-Galán
et al. 2018). Early microbial technologies, such as biofilters,
biotrickling filters, and gas-phase bioreactors generally use an
aqueous phase as the liquid phase to supply nutrients to pro-
vide suitable conditions for bacterial growth. In many cases,
the pollutants or substrates, which must be transported
through a film of liquid before being transformed by microor-
ganisms are immiscible with water, leading to the poor trans-
fer rates from the gaseous to the aqueous phase(Moradkhani
et al. 2017) (Kraakman et al. 2011)(CoxandDeshusses
1998). Several investigators have attempted to enhance gas-
liquid mass transfer rate by adding a second water-immiscible
liquid phase into the process. For example, it has been shown
that using two-phase partitioning bioreactors (TPPBs) or oth-
erwise incorporating a second liquid phase in bioreactors/
biofilters can enhance transfer and partitioning the chemical
species of interest and result in better performance(San-Valero
et al. 2017) (Lu et al. 2015)(Leeetal.2017).
Responsible editor: Marcus Schulz
Electronic supplementary material The online version of this article
(https://doi.org/10.1007/s11356-018-1705-z) contains supplementary
material, which is available to authorized users.
* Yongwen Ma
ppywma@scut.edu.cn
1
College of Environment and Energy, South China University of
Technology, Guangzhou 510006, China
2
The Key Lab of Pollution Control and Ecosystem Restoration in
Industry Clusters, Ministry of Education, South China University of
Technology, Guangzhou 510006, China
3
State Key Laboratory of Pulp and Paper Engineering, South China
University of Technology, Guangzhou 510641, China
Environmental Science and Pollution Research (2018) 25:15641–15650
https://doi.org/10.1007/s11356-018-1705-z
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