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Author's personal copy
Science of the Total Environment 454–455 (2013) 181–183

Contents lists available at SciVerse ScienceDirect

Science of the Total Environment
journal homepage: www.elsevier.com/locate/scitotenv

Comment on “Specific binding of hydroxylated polychlorinated biphenyl metabolites and
other substances to bovine calf uterine estrogen receptor: Structure-binding relationships
[Kramer and Giesy, Sci Total Environ 1999;233:141–61]”
Sierra Rayne ⁎
Chemologica Research, PO Box 74, 318 Rose Street, Mortlach, Saskatchewan S0H 3E0, Canada

a r t i c l e

i n f o

Article history:
Received 12 February 2013
Received in revised form 5 March 2013
Accepted 5 March 2013
Available online xxxx
Keywords:
Estrogen receptor
QSAR
Endocrine disruption
Polychlorinated biphenyls

In their study, Kramer and Giesy (1999) employed molecular
modeling tools (the AM1 semiempirical method with the HyperChem
software program) to calculate a range of steric and electronic
descriptors for the neutral (undissociated) forms of a suite of 28
hydroxylated polychlorinated biphenyls (OH-PCBs), and then proceeded
to use these descriptors to generate structure-binding relationships for
the specific binding of these compounds to bovine calf uterine estrogen
receptor.
OH-PCBs are acidic, with pKa values likely ranging from 4.6 to 10.7
(Rayne and Forest, 2010). Thus, at a physiological pH of 7.4, the ionization state of OH-PCBs will vary widely from effectively entirely dissociated as the phenolate anionic form to effectively entirely undissociated
and present as the phenol form. Kramer and Giesy (1999) chose to
examine OH-PCBs with apparently widely varying pKa values. For
example, estimated pKa values of the 28 OH-PCBs considered by
Kramer and Giesy (1999) are provided in Table 1, along with the percent
ionization expected at a physiologically relevant pH of 7.4. The predicted
pKa values for the OH-PCBs studied by Kramer and Giesy (1999) range
from 5.57 (OH-PCB2) to 10.52 (OH-PCB21), resulting in an estimated
percent ionization range at pH 7.4 from 0.1% (OH-PCB21) to 98.5%
(OH-PCB2). With estimated pKa values of 6.19 and 7.13, the dihydroxy
OH-PCB13 is predicted to be dominant in the dianionic form at physiological pH values, whereas the dihydroxy OH-PCB26 (pKa of 8.03 and

⁎ Tel./fax: +1 306 690 0573.
E-mail address: sierra.rayne@live.co.uk.

0048-9697/$ – see front matter © 2013 Elsevier B.V. All rights reserved.
http://dx.doi.org/10.1016/j.scitotenv.2013.03.017

8.94) is predicted to be only partially ionized at pH 7.4 (19.0%), predominantly as the monoanionic species (Fig. 1).
Thus, the ionization state of the OH-PCBs investigated by Kramer
and Giesy (1999) at physiological pH values will likely range from
effectively entirely dissociated to effectively entirely undissociated, with
some compounds displaying only partial (but significant) ionization.
Kramer and Giesy (1999) appear to ignore the potential ionization of
OH-PCBs during their modeling efforts, and appear to restrict their studies to the neutral form of each compound. Consequently, many of the
modeling parameters calculated appear to be a form of each compound
that either does not significantly exist under physiological conditions,
or which does not represent the complete speciation space expected to
be present under physiological conditions.
Within their manuscript, the authors make the following statements based on prior literature suggesting that the estrogen receptor
active species for each OH-PCB would be the undissociated form
(recalling that a phenol/hydroxyl moiety is different from a phenolate/
oxyanion functional group): “Though estrogenic substances vary widely
in structure, some common characteristics of most estrogens include:
(1) a sterically unhindered phenol group; and (2) a hydrophobic
substituent of greater than three carbons bonded para to the phenolic hydroxyl. The aromatic A-ring with its free hydroxyl group has

Table 1
SPARC (http://archemcalc.com/sparc/; October 2011 release w4.6.1691-s4.6.1687)
estimated pKa values for the 28 OH-PCBs under study by Kramer and Giesy (1999) and
the corresponding expected phenolic moiety percent ionization at a physiological pH of
7.4 (%I(pH7.4)).
Compound ID

pKa

%I(pH7.4)

Compound ID

pKa

%I(pH7.4)

OH-PCB1
OH-PCB2
OH-PCB3
OH-PCB4
OH-PCB5
OH-PCB6
OH-PCB7
OH-PCB8
OH-PCB9
OH-PCB10
OH-PCB11
OH-PCB12
OH-PCB13
OH-PCB14

5.84
5.57
7.27
6.29
6.34
7.80
8.07
6.21
6.34
9.44
9.41
9.64
6.19/7.13
9.68

97.3
98.5
57.4
92.8
92.0
28.5
17.6
93.9
92.0
0.9
1.0
0.6
94.2
0.5

OH-PCB15
OH-PCB16
OH-PCB17
OH-PCB18
OH-PCB19
OH-PCB20
OH-PCB21
OH-PCB22
OH-PCB23
OH-PCB24
OH-PCB25
OH-PCB26
OH-PCB27
OH-PCB28

8.80
8.64
9.29
9.10
7.89
9.99
10.52
9.75
8.48
6.35
8.29
8.03/8.94
9.02
9.90

3.8
5.4
1.3
2.0
24.4
0.3
0.1
0.4
7.7
91.8
11.4
19.0
2.3
0.3

Author's personal copy
182

S. Rayne / Science of the Total Environment 454–455 (2013) 181–183

suggesting that more reactive molecules bound less well to the ER…
The parameter OCHARGE described the partial charge on the oxygen
of the hydroxyl group and was strongly affected by the substitution of
vicinal chlorine atoms… reduction of the partial charge on the oxygen
would also cause reduction of the hydrogen bond acceptor strength
(hydrogen bond basicity) of the oxygen.” When making mechanistic
interpretations from QSAR/QSBR modeling, the modeling efforts need
to be undertaken on the species expected to be engaged in the mechanistic interactions under experimental study.
Furthermore, in their “[o]ptimum QSBR model” (see Table 7 from
Kramer and Giesy (1999)), three of the five parameters in their
multiple linear regression equation have non-significant (p > 0.05)
coefficients: EGAP, p = 0.0796; OCHARGE, p = 0.0635; and ZDIPOLE,
p = 0.1980. This is not an optimum form of model development. Ideally,
all variables should have statistically significant (p b 0.05) coefficients
(Dearden et al., 2009). As well, a predicted log10 IC50 residuals plot
against the experimental log10 IC50 from the “[o]ptimum QSBR model”
multiple linear regression equation presented by these authors has a
non-zero slope (Fig. 2), suggesting systematic errors in the QSBR model
(Dearden et al., 2009).
Based on the data presented by Kramer and Giesy (1999), we must
conclude that it is not clear whether (a) the undissociated form of the
OH-PCBs is the only active form, (b) the dissociated form of the
OH-PCBs is the only active form, (c) both the undissociated and dissociated forms of the OH-PCBs are active, either to similar or widely differing degrees, or that (d) the undissociated versus dissociated activity of
the OH-PCBs must be considered on a compound-by-compound basis,
with no clear pH/pKa generalizations. One notes that OH-PCBs 4, 8,
and 9 were excluded from the QSBR of Kramer and Giesy (1999)
because they were not active for the endpoint under consideration.
These OH-PCBs are also among the most acidic compounds considered
by the authors, and are expected to be dominant (>90%) in the ionized
form at physiological pH. This may suggest that the dissociated forms of
OH-PCBs are far less active than their undissociated counterparts, but
the evidence is too limited for any broad mechanistic conclusions
(there is no significant correlation between %I(pH7.4) and log10 IC50;
p = 0.68). Consequently, caution must be exercised when using the
QSBR from Kramer and Giesy (1999) to make mechanistic interpretations regarding the interaction of OH-PCBs with the bovine calf uterine
estrogen receptor and for using this QSBR to predict the activity of
OH-PCBs not included in model development. Future QSBR modeling

Fig. 1. pH dependent speciation plots for OH-PCB13 and OH-PCB26. Data generated using
SPARC (http://archemcalc.com/sparc/; October 2011 release w4.6.1691-s4.6.1687). Vertical
dashed line represents a physiologically relevant pH of 7.4.

been cited as a key for affinity of endogenous steroid hormones to
the estrogen receptor… The hydrogen bonding attributable to the
phenolic hydroxyl group of 17β-estradiol contributes significantly
to the affinity of the ligand for estrogen receptor.” Kramer and Giesy
(1999) go on to make the following mechanistic interpretations based
on their quantitative structure–activity relationship (QSAR)/quantitative
structure-binding relationship (QSBR) studies and the corresponding
parameters calculated solely for the undissociated forms of the OH-PCBs:
“Regardless of their utility as screening tools, QSAR approaches are useful in understanding mechanisms and scaling doses in experiments…
The parameter EGAP was a ‘global’ electronic parameter that describes
the overall reactivity of the molecule. Inspection of the coefficient for
this variable indicated that EGAP varied directly with log IC50. That is,
greater values of EGAP were related with greater values of log IC50,

Fig. 2. Residuals plot for the “[o]ptimum QSBR model” from Kramer and Giesy (1999).

Author's personal copy
S. Rayne / Science of the Total Environment 454–455 (2013) 181–183

efforts need to explicitly account for potential OH-PCB ionization in
order to ensure they offer rigorous mechanistic insights and a high
level of predictive capacity.
References
Dearden JC, Cronin MTD, Kaiser KLE. How not to develop a quantitative structure–
activity or structure–property relationship (QSAR/QSPR). SAR QSAR Environ Res
2009;20:241–66.

183

Kramer VJ, Giesy JP. Specific binding of hydroxylated polychlorinated biphenyl metabolites
and other substances to bovine calf uterine estrogen receptor: structure-binding relationships. Sci Total Environ 1999;233:141–61.
Rayne S, Forest K. pKa values of the monohydroxylated polychlorinated biphenyls
(OH-PCBs), polybrominated biphenyls (OH-PBBs), polychlorinated diphenyl ethers
(OH-PCDEs), and polybrominated diphenyl ethers (OH-PBDEs). J Environ Sci Health
A 2010;45:1322–46.


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