*J. Chem. Inf. Comput. Sci.* **2001,** *41,* 186-195

**QSAR Models Using a Large Diverse Set of Estrogens**

Leming M. Shi,^†,‡^ Hong Fang,^†^ Weida Tong,\*^,†^ Jie Wu,^†^ Roger
Perkins,^†^ Robert M. Blair,^§^\
William S. Branham,^§^ Stacy L. Dial,^§^ Carrie L. Moland,^§^ and Daniel
M. Sheehan^§^

R.O.W. Sciences, Inc., Jefferson, Arkansas 72079, and Division of
Genetic and Reproductive Toxicology,\
National Center for Toxicological Research (NCTR), Jefferson, Arkansas
72079

Received June 17, 2000

Endocrine disruptors (EDs) have a variety of adverse effects in humans
and animals. About 58 000 chemicals, most having little safety data,
must be tested in a group of tiered assays. As assays will take years,
it is important to develop rapid methods to help in priority setting.
For application to large data sets, we have developed an integrated
system that contains sequential four phases to predict the ability of
chemicals to bind to the estrogen receptor (ER), a prevalent mechanism
for estrogenic EDs. Here we report the results of evaluating two types
of QSAR models for inclusion in phase III to quantitatively predict
chemical binding to the ER. Our data set for the relative binding
affinities (RBAs) to the ER consists of 130 chemicals covering a wide
range of structural diversity and a 6 orders of magnitude spread of
RBAs. CoMFA and HQSAR models were constructed and compared for
performance. The CoMFA model had a *r*^2\ =^ 0.91 and a *q*^2^LOO =
0.66. HQSAR showed reduced performance compared to CoMFA with *r*^2\ =^
0.76 and *q*^2^LOO ) 0.59. A number of parameters were examined to
improve the CoMFA model. Of these, a phenol indicator increased the
*q*^2^~LOO~ to 0.71. When up to 50% of the chemicals were left out in
the leave-*N*-out cross­-validation, the *q*^2^ remained significant.
Finally, the models were tested by using two test sets; the *q*^2^~pred~
for these were 0.71 and 0.62, a significant result which demonstrates
the utility of the CoMFA model for predicting the RBAs of chemicals not
included in the training set. If used in conjunction with phases I and
II, which reduced the size of the data set dramatically by eliminating
most inactive chemicals, the current CoMFA model (phase III) can be used
to predict the RBA of chemicals with sufficient accuracy and to provide
quantitative information for priority setting.

INTRODUCTION

Experimental and epidemiological studies suggest that some man-made and
naturally occurring chemicals released to the environment have the
potential to interrupt normal functioning of the endocrine systems of
humans and wild­life.^1,2^ These chemicals, termed EDs, may pose serious
threats to the reproductive capability of humans and wildlife and are
thought to be the cause of declines in some wildlife populations.^3,4^
In response to scientific and public concerns on EDs, the U.S. Congress
in 1996 mandated that the Environmental Protection Agency (EPA) develop
a strategy for screening and testing a large number of chemicals\
(\~58 000) found in drinking water, food additives, and other sources
for their endocrine disruption potential.^5^ Because of the high cost
associated with screening and testing, it is crucial that priorities be
set to ensure that compounds with the highest predicted or measured
activities be given first priority for entry into the screening
procedure.^6^

Several types of hormonal activities, including, but not limited to,
estrogenic, androgenic, and thyroidal, are believed to contribute to
endocrine disruption.^1^ Recently, we proposed an integrated
"four-phase" approach for priority setting of potential estrogenic
EDs.^7^ The general approach is expected

\* Corresponding author. Telephone: (870) 543-7142. Fax: (870) 543-7382.
[[E-mail: wtong@nctr.fda.gov.]{.underline}](mailto:wtong@nctr.fda.gov.)

> † R.O.W. Sciences, Inc.

‡ Current address: BASF Corp. P.O. Box 400, Princeton, NJ 08543.

> § NCTR.

to be equally applicable to other endocrine disruption mechanisms, such
as androgen and thyroid hormonal activi­ties. The four-phase approach
integrates a suite of compu­tational models that can be used in setting
priorities for a large number of chemicals. Phase I uses four Lipinski
"rule of 5"-type simple rejection filters to eliminate the chemicals
that are most unlikely to bind the ER.^8^ The chemicals surviving phase
I are then classified as active or inactive in phase II on the basis of
the presence or absence of three key 2D structural alerts, seven
pharmacophore features, and the predictions of two classification models
using K-nearest neighbor (KNN) and classification and regression tree
(CART) methods. In phase III, QSAR models are used quantitatively to
predict activity of the chemicals categori­cally predicted to be active
in phase II. In phase IV of the integrated system, the phase II and III
predictions are combined with other available information, such as human
exposure level, environmental fate, and production volume, to determine
a chemical's priority for testing. The feasibility and application of
the first two phases were assessed for priority setting of the \~58 000
chemicals identified by Walker et al.^9^ as candidates for entry into
screening and testing. Some 9100 chemicals were predicted to bind to ER.
Of these, only 3600 were expected to bind to ER at binding affinity up
to 100 000-fold less than that of the endogenous hormone,
17*β*-estradiol (E2), which might need to be assessed in phase III using
QSAR models. Here, we report two QSAR

10.1021/ci000066d CCC: \$20.00 © 2001 American Chemical Society\
Published on Web 12/15/2000

methods that were thoroughly evaluated for application in phase III.

QSAR methods have proven successful in molecular design and drug
discovery.^10^ The endocrine disruptor screen­ing and testing advisory
committee (EDSTAC) organized by EPA considers QSAR as an important part
of its priority setting process, as described in its final report.^6^ In
the past few years, a number of QSAR models have been developed for
ligand binding to the ER.^11-19^ Most of these QSAR models were
constructed using the comparative molecular field analysis (CoMFA).
Although a predictive CoMFA model is dependent on a number of factors, a
training set with a broad representation over the chemistry space is
critical to ensure its predictive capability for a large number of
diverse chemicals. Unfortunately, most CoMFA models for ER binding
developed previously were based on data sets available in the
literature, which to date had been small data sets with limited
structural diversity.^11-19^ Although these models yield good
statistical results and explain some structural determinants for ER
binding, they have limited applicability in predicting the ER-ligand
binding affinity of chemicals that, in fact, cover a wide range of
structural diversity.

To obtain an adequate training set to develop a more robust QSAR model
for regulatory purpose, a rat ER binding assay was developed and
validated in the U.S. FDA's National Center for Toxicological Research
(NCTR) to provide a large data set for model development.^20,21^ The
resulting NCTR data set contains chemicals that were selected to cover
the structural diversity of chemicals that bind to ER with an activity
distribution ranging over 6 orders of magnitude, which is an essential
requirement for a robust predictive model for structurally diverse
estrogens. The selection process was highly interdisciplinary, involving
computational chemists, biologists, and experimental toxicologists and
has resulted in the steady improvement in performance of the QSAR
models.^22^ To the best of our knowledge, the NCTR data set is the best
consistent data set available to develop models for estrogens and was
the primary basis for construc­tion of the phase I and II models in the
integrated "four­phase" approach.

The rat uterine cytosol ER competitive binding assay is the gold
standard for in vitro ER assays. When compared to results from other ER
binding assays, there is a general consistency between relative ER
activities across different assay methods and species.^23^ For example,
we found a high linear correlation for ER binding affinities among a
diverse group of chemicals assayed with ER from rat uterine cytosol and
hERR. Further, we also found that ER assay results correlated very well
with those from a yeast-based reporter gene assay and MCF-7 cell
proliferation assay. These findings demonstrate that ER binding is the
major determi­nant across three levels of biological complexity (receptor
binding, a yeast reporter gene response, and cell proliferation) of
estrogen action. Moreover, chemicals positive in utero­trophic responses
(in vivo estrogenic activity) are also positive in the ER binding assay,
indicating that binding affinity is a good predictor of in vivo activity
with few false negatives observed.^24^ Therefore, the prediction of ER
binding activity provides an important piece of information for priority
setting.

We have previously evaluated three different techniques for the
generation of QSAR models-CoMFA, CODESSA (comprehensive descriptors for
structural and statistical analysis), and HQSAR (hologram QSAR)-for
their utility (predictivity, speed, accuracy, and reproducibility) to
screen a large number of compounds for ER binding activity.^13^ Common
to the three QSAR methods in the derivation of a regression model is the
use of PLS; the differences among these QSAR techniques are primarily in
the type of the descriptors used to represent chemical structure.
Specifically, CoMFA employs steric and electrostatic field descriptors
that encode detailed information concerning intermolecular in­teraction
in three dimensions. CODESSA calculates molec­ular descriptors on the
basis of 2D and 3D structures and quantum-chemical properties; whereas
HQSAR uses molec­ular holograms constructed from counts of substructural
molecular fragments. For three relatively small data sets under
investigation, the QSAR models generated using CoMFA and HQSAR
techniques demonstrated comparable high quality for potential usage to
identify ER ligands that may act as EDs. In this paper, these two
techniques are further investigated and compared, particularly for their
predictivity, by using the NCTR data set.

MATERIAL AND METHODS

**Data Sets.** The training set for QSAR model development was comprised
of 130 diverse chemicals (Table 1).^20,21^ The binding affinities of the
chemicals in the data set were determined by a competitive ER binding
assay with \[^3^H\]E2, using rat uterine cytosol.^20^ RBA, which is
defined as 100 times the ratio of the molar concentrations of E2 and the
competing chemical required to decrease the receptor-bound radioactivity
by 50%, was used for QSAR model develop­ment. Each experimental datum is
replicated at least twice. The mean value was used for modeling.

The constructed QSAR models were validated using external test data
sets. There are a number of experimental data sets reported in the
literature for estrogenic activity. Some of them have been used to
develop various types of QSAR models either by us or by other
researchers.^11-19^ Our earlier analysis on comparison of various in
vitro assays demonstrates that there is generally a good linear
correlation among activity measurements from the ER binding assay, the
yeast-based reporter gene assay and the E-SCREEN assay.^23^ The data
sets from other ER binding assays were used as primary sources for the
test sets. To select appropriate test data sets to validate the models,
the following general criteria were applied:

1.  Since the QSAR models developed in this study were primarily used to
    predict the activity of xenoestrogens, the test data sets should
    contain a substantial portion of xe­noestrogens.

2.  A literature survey revealed a great variability in the absolute
    activity value of a chemical obtained from different assays, or
    conducted on different species, or with the same assay performed by
    different labs.^23^ For these reasons, the activity value of the
    selected literature data set was normal­ized to the NCTR data set
    (the training set). The detailed procedure of normalization is
    reported in our previous publication.^23^ Briefly, the selected data
    set was first correlated

+-------------------+---+----+----+-------------------+---+---+----+
| **188** *J. Chem. |   |    |    |                   |   |   | S  |
| Inf. Comput.      |   |    |    |                   |   |   | HI |
| Sci., Vol. 41,    |   |    |    |                   |   |   | ET |
| No. 1, 2001*      |   |    |    |                   |   |   | A  |
|                   |   |    |    |                   |   |   | L. |
| **Table 1.**      |   |    |    |                   |   |   |    |
| Experimental,     |   |    |    |                   |   |   |    |
| CoMFA-Calculated, |   |    |    |                   |   |   |    |
| and               |   |    |    |                   |   |   |    |
| HQSAR-Calculated  |   |    |    |                   |   |   |    |
| log RBA for 130   |   |    |    |                   |   |   |    |
| Chemicals         |   |    |    |                   |   |   |    |
+-------------------+---+----+----+-------------------+---+---+----+
| name              | e | C  | H  | name              | e | C | H  |
|                   | x | oM | QS |                   | x | o | QS |
|                   | p | FA | AR |                   | p | M | AR |
|                   | t |    |    |                   | t | F |    |
|                   |   |    |    |                   |   | A |    |
+-------------------+---+----+----+-------------------+---+---+----+
| d                 | 2 | 1  | 0  | 3-methylestriol   | - | - | -0 |
| iethylstilbestrol | . | .8 | .5 |                   | 1 | 1 | .2 |
| (DES)             | 6 | 80 | 91 |                   | . | . | 40 |
|                   | 0 |    |    |                   | 6 | 2 |    |
|                   |   |    |    |                   | 5 | 5 |    |
|                   |   |    |    |                   |   | 7 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| *meso*-hexestrol  | 2 | 1  | 1  | 4-dodecylphenol   | - | - | -1 |
|                   | . | .9 | .5 |                   | 1 | 1 | .4 |
|                   | 4 | 75 | 45 |                   | . | . | 01 |
|                   | 8 |    |    |                   | 7 | 5 |    |
|                   |   |    |    |                   | 3 | 0 |    |
|                   |   |    |    |                   |   | 6 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| ethynyl estradiol | 2 | 1  | 0  | ethylhexylparaben | - | - | -2 |
|                   | . | .4 | .9 |                   | 1 | 2 | .3 |
|                   | 2 | 55 | 28 |                   | . | . | 04 |
|                   | 8 |    |    |                   | 7 | 1 |    |
|                   |   |    |    |                   | 4 | 0 |    |
|                   |   |    |    |                   |   | 5 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 4-OH-tamoxifen    | 2 | 1  | 1  | 4                 | - | - | -2 |
|                   | . | .7 | .0 | -tert-octylphenol | 1 | 2 | .1 |
|                   | 2 | 02 | 77 |                   | . | . | 38 |
|                   | 4 |    |    |                   | 8 | 2 |    |
|                   |   |    |    |                   | 2 | 2 |    |
|                   |   |    |    |                   |   | 9 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 17*β*-estradiol   | 2 | 0  | 0  | phenolphthalein   | - | - | -2 |
|                   | . | .8 | .4 |                   | 1 | 2 | .1 |
|                   | 0 | 55 | 04 |                   | . | . | 43 |
|                   | 0 |    |    |                   | 8 | 6 |    |
|                   |   |    |    |                   | 7 | 7 |    |
|                   |   |    |    |                   |   | 3 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 4-OH-estradiol    | 1 | 1  | 0  | kepone            | - | - | -1 |
|                   | . | .1 | .6 |                   | 1 | 1 | .7 |
|                   | 8 | 54 | 69 |                   | . | . | 79 |
|                   | 2 |    |    |                   | 8 | 8 |    |
|                   |   |    |    |                   | 9 | 0 |    |
|                   |   |    |    |                   |   | 3 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| α-zearalenol      | 1 | 1  | -0 | heptylparaben     | - | - | -2 |
|                   | . | .5 | .0 |                   | 2 | 2 | .3 |
|                   | 6 | 48 | 09 |                   | . | . | 29 |
|                   | 3 |    |    |                   | 0 | 4 |    |
|                   |   |    |    |                   | 9 | 3 |    |
|                   |   |    |    |                   |   | 0 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| ICI 182 780       | 1 | 1  | 1  | bisphenol A       | - | - | -2 |
|                   | . | .1 | .7 |                   | 2 | 2 | .7 |
|                   | 5 | 02 | 91 |                   | . | . | 73 |
|                   | 7 |    |    |                   | 1 | 0 |    |
|                   |   |    |    |                   | 1 | 7 |    |
|                   |   |    |    |                   |   | 9 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| dienestrol        | 1 | 1  | 0  | naringenin        | - | - | -2 |
|                   | . | .9 | .0 |                   | 2 | 2 | .5 |
|                   | 5 | 38 | 70 |                   | . | . | 77 |
|                   | 7 |    |    |                   | 1 | 7 |    |
|                   |   |    |    |                   | 3 | 3 |    |
|                   |   |    |    |                   |   | 7 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| α-zearalanol      | 1 | 1  | 0  | 4-chl             | - | - | -2 |
|                   | . | .4 | .1 | oro-4'-biphenylol | 2 | 2 | .8 |
|                   | 4 | 37 | 80 |                   | . | . | 22 |
|                   | 8 |    |    |                   | 1 | 0 |    |
|                   |   |    |    |                   | 8 | 2 |    |
|                   |   |    |    |                   |   | 4 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 2-OH-estradiol    | 1 | 0  | 0  | 3-deoxyestrone    | - | - | -0 |
|                   | . | .4 | .8 |                   | 2 | 0 | .6 |
|                   | 4 | 75 | 98 |                   | . | . | 15 |
|                   | 7 |    |    |                   | 2 | 6 |    |
|                   |   |    |    |                   | 0 | 8 |    |
|                   |   |    |    |                   |   | 3 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| diethylstibestrol | 1 | 1  | 0  | octylphenol       | - | - | -1 |
| monomethyl ether  | . | .1 | .2 |                   | 2 | 2 | .9 |
|                   | 3 | 41 | 86 |                   | . | . | 95 |
|                   | 1 |    |    |                   | 3 | 0 |    |
|                   |   |    |    |                   | 1 | 6 |    |
|                   |   |    |    |                   |   | 3 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 3,3'-dihydroxyl   | 1 | 1  | 2  | fisetin           | - | - | -2 |
| hexestrol         | . | .1 | .1 |                   | 2 | 2 | .5 |
|                   | 1 | 16 | 61 |                   | . | . | 77 |
|                   | 9 |    |    |                   | 3 | 2 |    |
|                   |   |    |    |                   | 5 | 9 |    |
|                   |   |    |    |                   |   | 8 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| droloxifene       | 1 | 0  | 0  | biochanin A       | - | - | -1 |
| Citrate           | . | .9 | .9 |                   | 2 | 2 | .9 |
|                   | 1 | 30 | 78 |                   | . | . | 79 |
|                   | 8 |    |    |                   | 3 | 6 |    |
|                   |   |    |    |                   | 7 | 9 |    |
|                   |   |    |    |                   |   | 3 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| ICI 164 384       | 1 | 1  | 1  | 4                 | - | - | -2 |
|                   | . | .1 | .7 | '-hydroxychalcone | 2 | 2 | .4 |
|                   | 1 | 37 | 69 |                   | . | . | 44 |
|                   | 6 |    |    |                   | 4 | 9 |    |
|                   |   |    |    |                   | 3 | 5 |    |
|                   |   |    |    |                   |   | 8 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| d                 | 1 | 0  | -0 | 2,2'-methylenebi  | - | - | -2 |
| imethylstibestrol | . | .4 | .2 | s(4-chlorophenol) | 2 | 2 | .8 |
|                   | 1 | 87 | 06 |                   | . | . | 24 |
|                   | 6 |    |    |                   | 4 | 6 |    |
|                   |   |    |    |                   | 5 | 0 |    |
|                   |   |    |    |                   |   | 7 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| moxestrol         | 1 | 1  | 1  | 4,4'-dih          | - | - | -2 |
|                   | . | .6 | .0 | ydoxybenzophenone | 2 | 1 | .6 |
|                   | 1 |    | 07 |                   | . | . | 26 |
|                   | 4 |    |    |                   | 4 | 7 |    |
|                   |   |    |    |                   | 6 | 7 |    |
|                   |   |    |    |                   |   | 3 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 17-deoxyestradiol | 1 | 0  | 0  | benzylparaben     | - | - | -  |
|                   | . | .4 | .2 |                   | 2 | 2 | 2. |
|                   | 1 | 44 | 94 |                   | . | . | 22 |
|                   | 4 |    |    |                   | 5 | 4 |    |
|                   |   |    |    |                   | 4 | 7 |    |
|                   |   |    |    |                   |   | 1 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 2,6-              | 1 | -0 | 2  | 4                 | - | - | -2 |
| dimethylhexestrol | . | .1 | .0 | '-hydroxychalcone | 2 | 2 | .4 |
|                   | 1 | 71 | 79 |                   | . | . | 17 |
|                   | 1 |    |    |                   | 5 | 0 |    |
|                   |   |    |    |                   | 5 | 4 |    |
|                   |   |    |    |                   |   | 0 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| estriol           | 0 | 0  | 0  | 2,4-dihy          | - | - | -2 |
|                   | . | .3 | .0 | droxybenzophenone | 2 | 2 | .7 |
|                   | 9 | 24 | 38 |                   | . | . | 08 |
|                   | 9 |    |    |                   | 6 | 2 |    |
|                   |   |    |    |                   | 1 | 0 |    |
|                   |   |    |    |                   |   | 9 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| monomethyl ether  | 0 | 1  | 1  | 4'                | - | - | -2 |
| hexestrol         | . | .2 | .2 | -hydroxyflavanone | 2 | 2 | .9 |
|                   | 9 | 21 | 40 |                   | . | . | 11 |
|                   | 7 |    |    |                   | 6 | 1 |    |
|                   |   |    |    |                   | 5 | 1 |    |
|                   |   |    |    |                   |   | 8 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| estrone           | 0 | 0  | -0 | 3α-androstanediol | - | - | -2 |
|                   | . | .9 | .1 |                   | 2 | 2 | .1 |
|                   | 8 | 00 | 12 |                   | . | . | 44 |
|                   | 6 |    |    |                   | 6 | 5 |    |
|                   |   |    |    |                   | 7 | 6 |    |
|                   |   |    |    |                   |   | 5 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| *                 | 0 | 0  | 1  | 4-phenethylphenol | - | - | -1 |
| p*-(α,*β*-diethyl | . | .9 | .5 |                   | 2 | 2 | .5 |
| -*p*-m            | 6 | 31 | 33 |                   | . | . | 00 |
| ethyl-phenethyl)‑ | 0 |    |    |                   | 6 | 2 |    |
|                   |   |    |    |                   | 9 | 2 |    |
| > *meso*-phenol   |   |    |    |                   |   | 1 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 17α-estradiol     | 0 | 0  | 0  | doisynoestrol     | - | - | -1 |
|                   | . | .4 | .4 |                   | 2 | 1 | .2 |
|                   | 4 | 65 | 04 |                   | . | . | 39 |
|                   | 9 |    |    |                   | 7 | 7 |    |
|                   |   |    |    |                   | 4 | 3 |    |
|                   |   |    |    |                   |   | 6 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| dihydroxyme       | 0 | -0 | -0 | 5,4'-dihydr       | - | - | -1 |
| thoxychloroolefin | . | .5 | .6 | oxy-7-methoxyiso‑ | 2 | 2 | .9 |
|                   | 4 | 56 | 24 |                   | . | . | 73 |
|                   | 2 |    |    | flavone           | 7 | 8 |    |
|                   |   |    |    | (prunetin)        | 4 | 1 |    |
|                   |   |    |    |                   |   | 2 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| mestranol         | 0 | -0 | 0  | myricetin         | - | - | -2 |
|                   | . | .1 | .6 |                   | 2 | 2 | .3 |
|                   | 3 | 25 | 49 |                   | . | . | 43 |
|                   | 5 |    |    |                   | 7 | 2 |    |
|                   |   |    |    |                   | 5 | 4 |    |
|                   |   |    |    |                   |   | 9 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| zearalanone       | 0 | 0  | 0  | 2-ch              | - | - | -2 |
|                   | . | .2 | .1 | loro-4-biphenylol | 2 | 2 | .6 |
|                   | 3 | 09 | 70 |                   | . | . | 85 |
|                   | 2 |    |    |                   | 7 | 3 |    |
|                   |   |    |    |                   | 7 | 7 |    |
|                   |   |    |    |                   |   | 0 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| tamoxifen         | 0 | 1  | 0  | triphenylethylene | - | - | -0 |
|                   | . | .2 | .7 |                   | 2 | 2 | .8 |
|                   | 2 | 20 | 20 |                   | . | . | 22 |
|                   | 1 |    |    |                   | 7 | 2 |    |
|                   |   |    |    |                   | 8 | 1 |    |
|                   |   |    |    |                   |   | 7 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| toremifene        | 0 | 0  | 0  | 3'                | - | - | -2 |
| citrate           | . | .7 | .7 | -hydroxyflavanone | 2 | 3 | .9 |
|                   | 1 | 47 | 14 |                   | . | . | 87 |
|                   | 4 |    |    |                   | 7 | 7 |    |
|                   |   |    |    |                   | 8 | 8 |    |
|                   |   |    |    |                   |   | 2 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| α, α              | - | 0  | 0  | chalcone          | - | - | -2 |
| -d                | 0 | .8 | .1 |                   | 2 | 2 | .7 |
| imethyl-*β*-ethyl | . | 85 | 66 |                   | . | . | 42 |
| allenolic acid    | 0 |    |    |                   | 8 | 8 |    |
|                   | 2 |    |    |                   | 2 | 3 |    |
|                   |   |    |    |                   |   | 9 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| coumestrol        | - | 0  | -1 | *o,p'*-DDT        | - | - | -1 |
|                   | 0 | .1 | .1 |                   | 2 | 2 | .6 |
|                   | . | 64 | 87 |                   | . | . | 44 |
|                   | 0 |    |    |                   | 8 | 3 |    |
|                   | 5 |    |    |                   | 5 | 4 |    |
|                   |   |    |    |                   |   | 8 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 4                 | - | -0 | -0 | 4-heptyloxyphenol | - | - | -3 |
| -ethyl-7-OH-3-(*p | 0 | .2 | .2 |                   | 2 | 2 | .4 |
| *-methoxyphenyl)‑ | . | 55 | 23 |                   | . | . | 56 |
|                   | 0 |    |    |                   | 8 | 1 |    |
| > dihydro-1       | 5 |    |    |                   | 8 | 7 |    |
| -benzopyran-2-one |   |    |    |                   |   | 3 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| Clomiphene        | - | 0  | -0 | di                | - | - | -2 |
|                   | 0 | .2 | .1 | hydrotestosterone | 2 | 3 | .3 |
|                   | . | 32 | 23 | (DHT)             | . | . | 21 |
|                   | 1 |    |    |                   | 8 | 1 |    |
|                   | 4 |    |    |                   | 9 | 4 |    |
|                   |   |    |    |                   |   | 1 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| nafoxidine        | - | -0 | 1  | formononetin      | - | - | -2 |
|                   | 0 | .2 | .5 |                   | 2 | 1 | .0 |
|                   | . | 52 | 60 |                   | . | . | 69 |
|                   | 1 |    |    |                   | 9 | 9 |    |
|                   | 4 |    |    |                   | 8 | 3 |    |
|                   |   |    |    |                   |   | 5 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 6 α-OH-estradiol  | - | 0  | 0  | bis(4-hydr        | - | - | -2 |
|                   | 0 | .9 | .4 | oxyphenyl)methane | 3 | 2 | .5 |
|                   | . | 34 | 52 |                   | . | . | 18 |
|                   | 1 |    |    |                   | 0 | 9 |    |
|                   | 5 |    |    |                   | 2 | 2 |    |
|                   |   |    |    |                   |   | 8 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| b-zearalanol      | - | -0 | 0  | *p*-phenylphenol  | - | - | -2 |
|                   | 0 | .1 | .1 |                   | 3 | 2 | .8 |
|                   | . | 37 | 80 |                   | . | . | 00 |
|                   | 1 |    |    |                   | 0 | 6 |    |
|                   | 9 |    |    |                   | 4 | 3 |    |
|                   |   |    |    |                   |   | 8 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 3-hy              | - | 0  | 0  | 6                 | - | - | -3 |
| droxy-estra-1,3,5 | 0 | .1 | .0 | -hydroxyflavanone | 3 | 2 | .0 |
| (10)-trien-16-one | . | 44 | 73 |                   | . | . | 91 |
|                   | 2 |    |    |                   | 0 | 1 |    |
|                   | 9 |    |    |                   | 5 | 7 |    |
|                   |   |    |    |                   |   | 0 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 3-deoxyestradiol  | - | -0 | -0 | 4,4'              | - | - | -3 |
|                   | 0 | .5 | .0 | -sulfonyldiphenol | 3 | 3 | .4 |
|                   | . | 73 | 99 |                   | . | . | 10 |
|                   | 3 |    |    |                   | 0 | 1 |    |
|                   | 0 |    |    |                   | 7 | 5 |    |
|                   |   |    |    |                   |   | 4 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 7,3',4'-tri       | - | -0 | -1 | butylparaben      | - | - | -2 |
| hydroxyisoflavone | 2 | .9 | .4 |                   | 3 | 2 | .7 |
|                   | . | 13 | 73 |                   | . | . | 14 |
|                   | 3 |    |    |                   | 0 | 8 |    |
|                   | 5 |    |    |                   | 7 | 0 |    |
|                   |   |    |    |                   |   | 5 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 3,6,4'-           | - | -0 | -2 | diphenolic acid   | - | - | -1 |
| trihydroxyflavone | 0 | .9 | .8 |                   | 3 | 3 | .6 |
|                   | . | 00 | 96 |                   | . | . | 25 |
|                   | 3 |    |    |                   | 1 | 4 |    |
|                   | 5 |    |    |                   | 3 | 7 |    |
|                   |   |    |    |                   |   | 8 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| genistein         | - | -1 | -1 | 1,3-diphenyltetr  | - | - | -3 |
|                   | 0 | .7 | .6 | amethyldisiloxane | 3 | 2 | .2 |
|                   | . | 86 | 73 |                   | . | . | 88 |
|                   | 3 |    |    |                   | 1 | 5 |    |
|                   | 6 |    |    |                   | 6 | 0 |    |
|                   |   |    |    |                   |   | 8 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 4,4'              | - | -0 | -1 | ethylparaben      | - | - | -2 |
| -dihydroxystibene | 0 | .6 | .4 |                   | 3 | 3 | .7 |
|                   | . | 99 | 96 |                   | . | . | 77 |
|                   | 5 |    |    |                   | 2 | 1 |    |
|                   | 5 |    |    |                   | 2 | 8 |    |
|                   |   |    |    |                   |   | 4 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| HPTE              | - | -1 | -0 | propylparaben     | - | - | -2 |
|                   | 0 | .0 | .7 |                   | 3 | 2 | .7 |
|                   | . | 96 | 78 |                   | . | . | 60 |
|                   | 6 |    |    |                   | 2 | 8 |    |
|                   | 0 |    |    |                   | 2 | 9 |    |
|                   |   |    |    |                   |   | 9 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| monohydroxy       | - | -0 | -0 | 3,3',             | - | - | -2 |
| me                | 0 | .1 | .9 | 5,5'-tetrachloro- | 3 | 2 | .0 |
| thoxychloroolefin | . | 62 | 30 | 4,4'-biphenyldiol | . | . | 21 |
|                   | 6 |    |    |                   | 2 | 9 |    |
|                   | 3 |    |    |                   | 5 | 1 |    |
|                   |   |    |    |                   |   | 4 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 2,3,4,5-tetrachl  | - | -1 | -2 | phenolred         | - | - | -3 |
| oro-4'-biphenylol | 0 | .0 | .1 |                   | 3 | 3 | .3 |
|                   | . | 23 | 70 |                   | . | . | 47 |
|                   | 6 |    |    |                   | 2 | 7 |    |
|                   | 4 |    |    |                   | 5 | 6 |    |
|                   |   |    |    |                   |   | 5 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| norethynodrel     | - | 0  | -0 | 4-                | - | - | -2 |
|                   | 0 | .6 | .6 | *tert*-amylphenol | 3 | 3 | .2 |
|                   | . | 70 | 14 |                   | . | . | 42 |
|                   | 6 |    |    |                   | 2 | 0 |    |
|                   | 7 |    |    |                   | 6 | 1 |    |
|                   |   |    |    |                   |   | 9 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 2,2',4,4'-t       | - | -0 | -0 | baicalein         | - | - | -2 |
| etrahydroxybenzil | 0 | .0 | .9 |                   | 3 | 2 | .9 |
|                   | . | 48 | 86 |                   | . | . | 83 |
|                   | 6 |    |    |                   | 3 | 6 |    |
|                   | 8 |    |    |                   | 5 | 8 |    |
|                   |   |    |    |                   |   | 3 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| *β*-zearalenol    | - | -0 | -0 | morin             | - | - | -2 |
|                   | 0 | .6 | .0 |                   | 3 | 2 | .5 |
|                   | . | 61 | 09 |                   | . | . | 94 |
|                   | 6 |    |    |                   | 3 | 8 |    |
|                   | 9 |    |    |                   | 5 | 0 |    |
|                   |   |    |    |                   |   | 9 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| equol             | - | -0 | -1 | 4-                | - | - | -2 |
|                   | 0 | .5 | .0 | *sec*-butylphenol | 3 | 3 | .4 |
|                   | . | 64 | 78 |                   | . | . | 16 |
|                   | 8 |    |    |                   | 3 | 0 |    |
|                   | 2 |    |    |                   | 7 | 7 |    |
|                   |   |    |    |                   |   | 8 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 6,4'              | - | -1 | -2 | 4-chlo            | - | - | -3 |
| -dihydroxyflavone | 0 | .1 | .8 | ro-3-methylphenol | 3 | 3 | .1 |
|                   | . | 26 | 58 |                   | . | . | 07 |
|                   | 8 |    |    |                   | 3 | 7 |    |
|                   | 2 |    |    |                   | 8 | 2 |    |
|                   |   |    |    |                   |   | 3 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| monohydroxy       | - | -0 | -1 | 6-hydroxyflavone  | - | - | -3 |
| methoxychlor      | 0 | .8 | .0 |                   | 3 | 2 | .2 |
|                   | . | 45 | 83 |                   | . | . | 08 |
|                   | 8 |    |    |                   | 4 | 5 |    |
|                   | 9 |    |    |                   | 1 | 6 |    |
|                   |   |    |    |                   |   | 0 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 3*                | - | -0 | -2 | 3-phenylphenol    | - | - | -2 |
| β*-androstanediol | 0 | .7 | .1 |                   | 3 | 4 | .8 |
|                   | . | 11 | 44 |                   | . | . | 78 |
|                   | 9 |    |    |                   | 4 | 0 |    |
|                   | 2 |    |    |                   | 4 | 6 |    |
|                   |   |    |    |                   |   | 2 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| bisphenol B       | - | -1 | -1 | 4-benzyloxphenol  | - | - | -3 |
|                   | 1 | .2 | .5 |                   | 3 | 3 | .4 |
|                   | . | 29 | 62 |                   | . | . | 46 |
|                   | 0 |    |    |                   | 4 | 6 |    |
|                   | 7 |    |    |                   | 4 | 3 |    |
|                   |   |    |    |                   |   | 8 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| phloretin         | - | -1 | -1 | methylparaben     | - | - | -2 |
|                   | 1 | .5 | .4 |                   | 3 | 3 | .9 |
|                   | . | 65 | 73 |                   | . | . | 57 |
|                   | 1 |    |    |                   | 4 | 2 |    |
|                   | 6 |    |    |                   | 4 | 9 |    |
|                   |   |    |    |                   |   | 7 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| diethylstibestrol | - | -0 | -0 | 2-                | - | - | -2 |
| dimethyl ether    | 1 | .6 | .0 | *sec*-butylphenol | 3 | 3 | .7 |
|                   | . | 90 | 20 |                   | . | . | 44 |
|                   | 2 |    |    |                   | 5 | 9 |    |
|                   | 5 |    |    |                   | 4 | 0 |    |
|                   |   |    |    |                   |   | 4 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 4,2',4'-t         | - | -1 | -1 | 4-*               | - | - | -2 |
| rihydroxychalcone | 1 | .3 | .9 | tert*-butylphenol | 3 | 3 | .9 |
|                   | . | 62 | 83 |                   | . | . | 22 |
|                   | 2 |    |    |                   | 6 | 1 |    |
|                   | 6 |    |    |                   | 1 | 7 |    |
|                   |   |    |    |                   |   | 7 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 2,5-dich          | - | -2 | -2 | 2,4'              | - | - | -3 |
| loro-4-biphenylol | 1 | .1 | .6 | -dichlorobiphenyl | 3 | 3 | .0 |
|                   | . | 03 | 18 |                   | . | . | 46 |
|                   | 4 |    |    |                   | 6 | 3 |    |
|                   | 4 |    |    |                   | 1 | 5 |    |
|                   |   |    |    |                   |   | 0 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 4,4'-(1,2-eth     | - | -1 | -1 | 2-chlo            | - | - | -3 |
| anediyl)bisphenol | 1 | .1 | .1 | ro-4-methylphenol | 3 | 4 | .0 |
|                   | . | 28 | 60 |                   | . | . | 25 |
|                   | 4 |    |    |                   | 6 | 3 |    |
|                   | 4 |    |    |                   | 6 | 0 |    |
|                   |   |    |    |                   |   | 5 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| 16b-hydroxy-1     | - | -1 | -0 | phenolphthalin    | - | - | -2 |
| 6-methyl-3-methyl | 1 | .4 | .6 |                   | 3 | 3 | .4 |
|                   | . | 70 | 80 |                   | . | . | 46 |
| > ether estradiol | 4 |    |    |                   | 6 | 3 |    |
|                   | 8 |    |    |                   | 7 | 5 |    |
|                   |   |    |    |                   |   | 1 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| aurin             | - | -1 | -0 | 4-chlo            | - | - | -3 |
|                   | 1 | .5 | .6 | ro-2-methylphenol | 3 | 4 | .2 |
|                   | . | 93 | 53 |                   | . | . | 18 |
|                   | 5 |    |    |                   | 6 | 1 |    |
|                   | 0 |    |    |                   | 7 | 8 |    |
|                   |   |    |    |                   |   | 2 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| nor               | - | -1 | -0 | 7                 | - | - | -3 |
| dihydroguaiaretic | 1 | .3 | .0 | -hydroxyflavanone | 3 | 3 | .0 |
| acid              | . | 38 | 71 |                   | . | . | 35 |
|                   | 5 |    |    |                   | 7 | 9 |    |
|                   | 1 |    |    |                   | 3 | 4 |    |
|                   |   |    |    |                   |   | 4 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| nonylphenol       | - | -1 | -1 | 3-ethylphenol     | - | - | -3 |
|                   | 1 | .7 | .8 |                   | 3 | 3 | .0 |
|                   | . | 69 | 47 |                   | . | . | 11 |
|                   | 5 |    |    |                   | 8 | 6 |    |
|                   | 3 |    |    |                   | 7 | 4 |    |
|                   |   |    |    |                   |   | 1 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| apigenin          | - | -2 | -2 | rutin             | - | - | -5 |
|                   | 1 | .4 | .6 |                   | 4 | 4 | .6 |
|                   | . | 36 | 91 |                   | . | . | 20 |
|                   | 5 |    |    |                   | 0 | 2 |    |
|                   | 5 |    |    |                   | 9 | 3 |    |
|                   |   |    |    |                   |   | 5 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| kaempferol        | - | -2 | -2 | 4-ethylphenol     | - | - | -2 |
|                   | 1 | .2 | .7 |                   | 4 | 4 | .9 |
|                   | . | 45 | 29 |                   | . | . | 48 |
|                   | 6 |    |    |                   | 1 | 2 |    |
|                   | 1 |    |    |                   | 7 | 2 |    |
|                   |   |    |    |                   |   | 0 |    |
+-------------------+---+----+----+-------------------+---+---+----+
| daidzein          | - | -1 | -1 | 4-methylphenol    | - | - | -3 |
|                   | 1 | .0 | .7 |                   | 4 | 4 | .0 |
|                   | . | 75 | 64 |                   | . | . | 37 |
|                   | 6 |    |    |                   | 5 | 4 |    |
|                   | 5 |    |    |                   | 0 | 3 |    |
|                   |   |    |    |                   |   | 5 |    |
+-------------------+---+----+----+-------------------+---+---+----+

with the NCTR data set on the basis of the shared compounds NCTR data
set on the basis of the correlation equation. To

in both data sets, and then the activity value for each ensure a valid
normalization, the selected data set should

compound not in the NCTR data set was normalized to the include a
sufficient number of chemicals shared with the

![](media/image1.png){width="4.8597222222222225in"
height="2.626388888888889in"}

**Figure 1.** Correlation of the NCTR data with Kuiper's and Waller's
data

NCTR data set to establish a statistically significant linear
correlation. The normalized activity value of a chemical can then be
compared with the model-predicted value to assess the performance of the
QSAR model.

Two data sets reported by Kuiper^25^ and Waller,^15^ respec­tively, were
selected. The activity values of both data sets were obtained from ER
competitive binding assays: In Kuiper's study, the pure human ERα was
used; whereas the mouse uterine cytosol that primarily contains ERα was
used in Waller's data. Kuiper's data set contains 60 chemicals, of which
35 chemicals are assayed in the NCTR data set. Of 35 common chemicals,
19 chemicals are active in both data sets. A nice linear correlation was
observed between the Kuiper and NCTR data sets based on these 19
chemicals (Figure 1). Similarly, Waller's data set contains 58 chemicals
with 33 common chemicals. The linear correlation between the Waller and
NCTR data sets was also observed for 21 common active chemicals (Figure
1). Both Kuiper's and Waller's data sets contain 25 chemicals that are
not assayed in the NCTR data set, which are used to test the QSAR
models.

**Molecular Modeling.** All molecular modeling and statisti­cal analyses
were performed using Sybyl 6.5 (Tripos, St. Louis, MO).

As shown in Figure 2, the basic chemical structures for the study
consisted of several categories: (1) steroidal compounds; (2) two
benzene rings separated by two carbons (DES derivatives and most
phytoestrogens); (3) two benzene rings separated by one carbon (DDTs and
bisphenol A derivatives); (4) biphenyls (PCBs); (5) chemicals with a
single phenolic ring (alkylphenols and parabens); (6) miscel­laneous
chemicals. The putative bioactive molecular con­formation for each
chemical used for CoMFA and its rules for structural alignment were
determined by selecting a starting conformation that was followed by
energy optimiza­tion using the standard Tripos force field and parameter
settings. The crystal structures of four ligands, E2, raloxifene (Ral),
diethylstilbestrol (DES), and 4-hydroxytamoxifen (OHT), binding to the
ERR were used to determine the starting conformation of steroids and DES
derivatives, as well as for antiestrogens.^26,27^ The chemical
structures of phytoestrogens are obtained or modified from the Cambridge
Structural Database. The starting conformation of the rest

![](media/image2.png){width="2.7472222222222222in"
height="3.8868055555555556in"}

**Figure 2.** Structural categories and representative chemicals of the
NCTR data set.

of the chemicals was determined using a systematic search tool for
torsion angles.

**CoMFA Alignment.** To develop a CoMFA model, the molecules of interest
must first be aligned to maximize superposition of their steric and
electrostatic fields. Although a statistically robust CoMFA model is
dependent on a number of factors, proper alignment is essential to
produce a valid QSAR model. For chemical congeners, the alignment rule
is normally defined on the basis of the maximum common substructure
among the training set chemicals, which usually leads to a statistically
robust CoMFA model. The drawback for such models is predicting
activities of chemicals whose structures are not similar to the training
set. In contrast, a CoMFA model based on a structurally diverse data set
provides more robust predictions. But the

![](media/image3.png){width="3.2in" height="2.3333333333333335in"}

**Figure 3.** Relative positions of E2, DES, raloxifene, and
4-OH-tamoxifen in the ER binding site derived from superposition of
their bound receptor crystal structures.

critical and difficult aspect for such a CoMFA model, like the one in
this study, is choosing the most appropriate set of alignment rules for
the structurally diverse training set. Fortunately, crystal structures
of four ligands binding to the ER have been published,^26,27^ which
aided our derivation of rational CoMFA alignment rules. The backbone of
the R helices (except helix 12, which shows a dramatic confor­mational
difference when binding to estrogens vs antiestro­gens) were used to
superimpose the four complexes. The superimposed complex structures
revealed the conformational conservation and flexibility of the ER
ligand binding domain. Furthermore, by overlapping of the backbone of
the R helices, the corresponding superimposition of the four ligands
(note: coordinates of these ligands were not used in the superimposition
of the complexes), as shown in Figure 3, could be examined in detail
with respect to the binding contribution from different structural
features, individually and in combination. It appears that the A-rings
overlap very nicely, whereas there is considerable flexibility at the
D-ring end. This is consistent with the observation of the importance of
the A-ring phenolic group in ER-ligand binding, where the 3-OH group
forms three hydrogen bond interactions with the ER ligand binding domain
and a water molecule.

Systematic studies on the influence of substituents at various positions
of E2 revealed that for most positions the introduction of substituents
produces a loss of binding affinity.^16-29^ However, introducing a
substituent to the 7α or 11*β* positions generally enhances binding. The
degree of increase in activity is strongly dependent on the nature of
substituents. Small steric substituents increase the activity,^30^ while
rather large substituents reduce it, but also give rise to
antiestrogenic activity, exemplified by ICI 180 780 and ICI 164 384. The
two ethyl groups of DES functionally resemble substituents at the 7α and
11*β* positions of E2. One of the ethyl groups is in the precise space
that is occupied by the 11β-substituent of E2.^31^ Dimethystilbestrol
(DMS) (RBA ) 14.50) and 4,4'-dihydroxystilbene (RBA ) 0.38) are in the
order of one carbon atom less on both side chains. The loss of RBAs for
these two chemicals was 28- and 1423-fold compared to that of DES.

The aforementioned evidences indicate that the structural features of E2
important for ER binding include (1) a phenolic A ring, (2) a D ring,
(3) 7α and/or 11*β* substituents, and (4)

a hydrophobic backbone. The combination of any three of the structural
features generally yields a strong estrogen. Using E2 as a template
molecule, these four structural features were the basis for the
alignment rules. Specifically, six pharmacophoric elements of E2-the
centroids of the A-, B-, C-, and D-rings and 7 and 11 positions-were
used for alignment. The corresponding pharmacophoric elements for each
structural category are shown in Figure 2(left panel). The alignment
rules employ a least-squares fitting of pharmacophoric elements between
E2 and the molecule from the training set, and specifically the
following: (1) Steroids were aligned on the basis of the centers of the
A- and D-rings and positions 7 and 11. (2) The corresponding
pharmacoph­oric elements for DES derivatives and phytoestrogens were the
centers of the A- and D-rings and position 11. (3) For DDT- and
bisphenol A-type chemicals the corresponding aligned positions were the
centers of the A- and D-rings and the 11 position of E2. (4) PCBs were
aligned on the basis of the positions 1, 3, 5, and 11 of E2. (5)
Alignment of alkylphenols and parabens was based on the superposition of
their phenolic rings to that of E2. (6) The alignment of the
miscellaneous chemicals was determined individually on the basis of an
appropriate rationalization consistent with overall alignment strategy.

**Calculation of QSAR Descriptors.** The calculation of CoMFA steric and
electrostatic descriptors, as well as HQSAR holograms, is described in
our previous publica­tions.^13^ Briefly, there is the following:

**CoMFA Descriptors.** After alignment, the molecules in the training
set were placed in a three-dimensional cubic lattice with 2 Å spacing.
The steric (van der Waals) and electrostatic (Coulombic) fields were
calculated for each molecule at each mesh point using an sp^3^ carbon
probe with +1.0 charge. Any calculated steric and electrostatic energies
that were greater than 30 kcal/mol were truncated to this value. Column
filtering was set to 1 kcal/mol.

**HQSAR Holograms.** The substructual fragments in the predefined size
range of atoms (the default range is 4-7) were generated for each
molecule in the training set. The information contained in each fragment
is defined by fragment distinction parameters, including atoms, bonds,
connections, hydrogen, and chirality. The generated frag­ments were then
hashed into a fixed length array to produce the molecular hologram. The
hologram length defines the dimensionality of the descriptor space,
which is determined from a range of predefined hologram lengths using a
trial­and-error approach evaluated by the smallest error generated in the
models. HQSAR descriptors encode all possible molecular fragments
(linear, branched, and overlapping). Additional3D information such as
hybridization and chirality are encoded in the molecular holograms.

**PLS-QSAR.** To form the basis for a predictive statistical model, the
method of partial least-squares (PLS) regression^32^ was used to
correlate variations in the biological activities with variations in the
respective descriptors for the NCTR data set. The optimal number of
principal components (PCs), corresponding to the smallest standard error
of prediction, was determined by the leave-one-out (LOO)
cross-validation procedure, which yields a cross-validated *q*^2^LOO to
measure the model's predictivity. Using the optimal number of PCs, the
final PLS analysis was carried out without cross-validation to generate
a predictive QSAR

![](media/image4.png){width="2.5902777777777777in"
height="5.206944444444445in"}

**Figure 4.** CoMFA (A) and HQSAR (B) models for the NCTR data set.

model with a conventional correlation coefficient, *r*^2^*.* In
addition, the leave-*N*-out (LNO) cross-validation procedure was
employed to further validate the models. In this method, the data set is
first randomly divided into *N* groups with approximately equal numbers
of chemicals in each group. Each group is systematically excluded once
from the data set, and the activities of the chemicals in the omitted
group are predicted by a model derived from the remaining chemicals in
the data set. Similar to the q^2^~LOO~ value derived from the LOO
process, the q^2^~LNO~ value for this procedure can also be calculated
on the basis of the prediction of the left-out chemicals. In this study,
a range of *N* groups *(N =* 2-10, 13, 20, 50) was used to perform the
LNO cross­validation. For each group, the cross-validation was carried
100 times to determine the mean and standard error of *q*^2^LNO.

**Model Prediction.** The QSAR models were further validated for
prediction of the external validation data sets. A statistical measure,
*q*^2^~pred,~ was used to compare the predictive capability among
different QSAR models. The predictive *q*^2^~pred~ is calculated
from^33^

*q* 2 pred = 1 - PRESS/SD

where PRESS is the sum of squared differences between the "actual
activity" (normalized to the NCTR data set in this

![](media/image5.png){width="3.089583333333333in"
height="2.0770833333333334in"}

**Figure 5.** Fold differences for experimental measurements and CoMFA
calculated results.

**Table 2.** Summary of Statistical Results for the CoMFA and HQSAR
Models

+------------+-----------+-----------+-----------+-----------+--------+
| statistics | CoMFA     | HQSAR     | s         | CoMFA     | HQSAR  |
|            |           |           | tatistics |           |        |
+------------+-----------+-----------+-----------+-----------+--------+
| >          | > 0.655   | > 0.585   | SE        | > 0.568   | >      |
|  *q*^2^LOO | >         | >         |           | >         |  0.901 |
| >          | > 0.908   | > 0.756   | PCs       | > 6       | >      |
| > *r*^2^   |           |           |           |           | > 5    |
+------------+-----------+-----------+-----------+-----------+--------+

study) and the predicted activity data for each molecule in the test set
and SD is the sum of squared deviations between the "actual activity"
data for each molecule in the test set and the mean activity of the
training set.

RESULTS

**CoMFA Model.** The CoMFA-calculated versus experi­mental RBAs (as logs)
for the training-set compounds are plotted in Figure 4A and listed in
Table 1. The conventional *r*^2^ and cross-validated *q*^2^~LOO~ were
0.91 and 0.66 (Table 2), respectively, indicating that the CoMFA model
was both internally consistent and highly predictive. The steric and
electrostatic field contributions to the CoMFA model were 43% and 57%,
respectively, which were similar to those we reported for our earlier
CoMFA models for much smaller ER ligand data sets.^11-13^

Each experimental datum for the NCTR data set is replicated at least
twice. The experimental fold-difference for each data point can be
calculated by dividing the highest value by the lowest value. Figure 5
shows two different distributions: (1) the range of fold-differences for
experi­mental replications; (2) the range of fold-differences for CoMFA
predicted and experimental means. It is apparent that the CoMFA
prediction error is in a similar range as the experimental deviation.
Predictions fell within 5-fold of experimental values for some 85% of
the chemicals.

On the basis of the evaluation of 30 DES congeners, Sadler et al.
reported significant improvement of the CoMFA model by applying the
cross-validated *r*^2^-guided region selection method.^18^ It provides
more weight on the CoMFA regions that show greater influence on the
standard CoMFA PLS model, as determined by the PLS coefficients and
CoMFA field variations for particular grids. The weighted CoMFA fields
are calculated and used to correlate with biological activity. A similar
approach, called region focusing, imple­mented in the Sybyl software was
also applied for the NCTR data set. It appears that region focusing did
not significantly improve the statistical results of the model (data not
shown).

<table>
<colgroup>
<col style="width: 7%" />
<col style="width: 6%" />
<col style="width: 7%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 7%" />
<col style="width: 11%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 5%" />
<col style="width: 5%" />
<col style="width: 5%" />
<col style="width: 6%" />
<col style="width: 4%" />
<col style="width: 7%" />
</colgroup>
<tbody>
<tr class="odd">
<td colspan="7"><strong>192</strong> <em>J. Chem. Inf. Comput. Sci.,
Vol. 41, No. 1, 2001</em></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td colspan="2"><blockquote>
<p>SHI ET AL.</p>
</blockquote></td>
</tr>
<tr class="even">
<td colspan="7"><strong>Table 3.</strong> Leave-<em>N</em>-Out
Cross-Validation Results for CoMFA</td>
<td colspan="8"><strong>Table 4.</strong> Leave-<em>N</em>-Out
Cross-Validation Results for HQSAR</td>
</tr>
<tr class="odd">
<td><p>no. of</p>
<p>CV</p>
<p>groups</p></td>
<td><p>cmpds</p>
<p>left (%)</p></td>
<td><p>min</p>
<p><em>q</em><sup>2</sup>LNO</p></td>
<td><p>max</p>
<p><em>q</em><sup>2</sup>LNO</p></td>
<td><p>mean</p>
<p><em>q</em><sup>2</sup>LNO</p></td>
<td><p>SD of</p>
<p><em>q</em><sup>2</sup>LNO</p></td>
<td><p>mean no</p>
<p>of PCs<em><sup>a</sup></em></p></td>
<td><p>no. of</p>
<p>CV</p>
<p>groups</p></td>
<td><p>cmpds</p>
<p>left (%)</p></td>
<td><p>min</p>
<p><em>q</em><sup>2</sup>LNO</p></td>
<td><p>max</p>
<p><em>q</em><sup>2</sup>LNO</p></td>
<td><p>mean</p>
<p><em>q</em><sup>2</sup>LNO</p></td>
<td><p>SD of</p>
<p><em>q</em><sup>2</sup>LNO</p></td>
<td><p>mean</p>
<p>no. of</p>
<blockquote>
<p>PCs</p>
</blockquote></td>
<td><p>mean</p>
<blockquote>
<p>HL<em><sup>a</sup></em></p>
</blockquote></td>
</tr>
<tr class="even">
<td>2</td>
<td>50</td>
<td>0.339</td>
<td>0.684</td>
<td>0.569</td>
<td>0.0540</td>
<td><blockquote>
<p>4.4</p>
</blockquote></td>
<td>2</td>
<td>50</td>
<td>0.276</td>
<td>0.652</td>
<td>0.503</td>
<td>0.0718</td>
<td><blockquote>
<p>5</p>
</blockquote></td>
<td><blockquote>
<p>347</p>
</blockquote></td>
</tr>
<tr class="odd">
<td>3</td>
<td>33.3</td>
<td>0.512</td>
<td>0.671</td>
<td>0.607</td>
<td>0.0372</td>
<td><blockquote>
<p>4.8</p>
</blockquote></td>
<td>3</td>
<td>33.3</td>
<td>0.430</td>
<td>0.655</td>
<td>0.546</td>
<td>0.0535</td>
<td><blockquote>
<p>5.4</p>
</blockquote></td>
<td><blockquote>
<p>380</p>
</blockquote></td>
</tr>
<tr class="even">
<td>4</td>
<td>25</td>
<td>0.534</td>
<td>0.706</td>
<td>0.623</td>
<td>0.0350</td>
<td><blockquote>
<p>5.0</p>
</blockquote></td>
<td>4</td>
<td>25</td>
<td>0.445</td>
<td>0.637</td>
<td>0.565</td>
<td>0.0399</td>
<td><blockquote>
<p>5.5</p>
</blockquote></td>
<td><blockquote>
<p>384</p>
</blockquote></td>
</tr>
<tr class="odd">
<td>5</td>
<td>20</td>
<td>0.528</td>
<td>0.676</td>
<td>0.623</td>
<td>0.0335</td>
<td><blockquote>
<p>5.16</p>
</blockquote></td>
<td>5</td>
<td>20</td>
<td>0.466</td>
<td>0.647</td>
<td>0.574</td>
<td>0.0343</td>
<td><blockquote>
<p>5.6</p>
</blockquote></td>
<td><blockquote>
<p>382</p>
</blockquote></td>
</tr>
<tr class="even">
<td>6</td>
<td><blockquote>
<p>16.7</p>
</blockquote></td>
<td>0.557</td>
<td>0.693</td>
<td>0.634</td>
<td>0.0288</td>
<td><blockquote>
<p>5.2</p>
</blockquote></td>
<td>6</td>
<td><blockquote>
<p>16.7</p>
</blockquote></td>
<td>0.444</td>
<td>0.640</td>
<td>0.572</td>
<td>0.0338</td>
<td><blockquote>
<p>5.6</p>
</blockquote></td>
<td><blockquote>
<p>387</p>
</blockquote></td>
</tr>
<tr class="odd">
<td>7</td>
<td><blockquote>
<p>14.3</p>
</blockquote></td>
<td>0.587</td>
<td>0.683</td>
<td>0.637</td>
<td>0.0220</td>
<td><blockquote>
<p>5.3</p>
</blockquote></td>
<td>7</td>
<td><blockquote>
<p>14.3</p>
</blockquote></td>
<td>0.481</td>
<td>0.633</td>
<td>0.575</td>
<td>0.0298</td>
<td><blockquote>
<p>5.5</p>
</blockquote></td>
<td><blockquote>
<p>386</p>
</blockquote></td>
</tr>
<tr class="even">
<td>8</td>
<td><blockquote>
<p>12.5</p>
</blockquote></td>
<td>0.579</td>
<td>0.690</td>
<td>0.641</td>
<td>0.0229</td>
<td><blockquote>
<p>5.4</p>
</blockquote></td>
<td>8</td>
<td><blockquote>
<p>12.5</p>
</blockquote></td>
<td>0.496</td>
<td>0.645</td>
<td>0.576</td>
<td>0.0309</td>
<td><blockquote>
<p>5.6</p>
</blockquote></td>
<td><blockquote>
<p>389</p>
</blockquote></td>
</tr>
<tr class="odd">
<td>9</td>
<td><blockquote>
<p>11.1</p>
</blockquote></td>
<td>0.595</td>
<td>0.689</td>
<td>0.645</td>
<td>0.0209</td>
<td><blockquote>
<p>5.5</p>
</blockquote></td>
<td>9</td>
<td><blockquote>
<p>11.1</p>
</blockquote></td>
<td>0.464</td>
<td>0.628</td>
<td>0.584</td>
<td>0.0271</td>
<td><blockquote>
<p>5.5</p>
</blockquote></td>
<td><blockquote>
<p>394</p>
</blockquote></td>
</tr>
<tr class="even">
<td>10</td>
<td><blockquote>
<p>10</p>
</blockquote></td>
<td>0.600</td>
<td>0.690</td>
<td>0.649</td>
<td>0.0188</td>
<td><blockquote>
<p>5.5</p>
</blockquote></td>
<td>10</td>
<td><blockquote>
<p>10</p>
</blockquote></td>
<td>0.524</td>
<td>0.631</td>
<td>0.584</td>
<td>0.0219</td>
<td><blockquote>
<p>5.6</p>
</blockquote></td>
<td><blockquote>
<p>392</p>
</blockquote></td>
</tr>
<tr class="odd">
<td>13</td>
<td><blockquote>
<p>7.7</p>
</blockquote></td>
<td>0.583</td>
<td>0.686</td>
<td>0.647</td>
<td>0.0185</td>
<td><blockquote>
<p>5.6</p>
</blockquote></td>
<td>13</td>
<td><blockquote>
<p>7.7</p>
</blockquote></td>
<td>0.513</td>
<td>0.634</td>
<td>0.587</td>
<td>0.0216</td>
<td><blockquote>
<p>5.5</p>
</blockquote></td>
<td><blockquote>
<p>397</p>
</blockquote></td>
</tr>
<tr class="even">
<td>20</td>
<td><blockquote>
<p>5</p>
</blockquote></td>
<td>0.617</td>
<td>0.680</td>
<td>0.652</td>
<td>0.0126</td>
<td><blockquote>
<p>5.5</p>
</blockquote></td>
<td>20</td>
<td><blockquote>
<p>5</p>
</blockquote></td>
<td>0.514</td>
<td>0.620</td>
<td>0.585</td>
<td>0.0189</td>
<td><blockquote>
<p>5.5</p>
</blockquote></td>
<td><blockquote>
<p>397</p>
</blockquote></td>
</tr>
<tr class="odd">
<td>50</td>
<td><blockquote>
<p>2</p>
</blockquote></td>
<td>0.630</td>
<td>0.674</td>
<td>0.656</td>
<td>0.0074</td>
<td><blockquote>
<p>5.6</p>
</blockquote></td>
<td>50</td>
<td><blockquote>
<p>2</p>
</blockquote></td>
<td>0.563</td>
<td>0.608</td>
<td>0.589</td>
<td>0.0098</td>
<td><blockquote>
<p>5.35</p>
</blockquote></td>
<td><blockquote>
<p>401</p>
</blockquote></td>
</tr>
<tr class="even">
<td>130</td>
<td><blockquote>
<p>0.77</p>
</blockquote></td>
<td>0.655</td>
<td>0.655</td>
<td>0.655</td>
<td>NA</td>
<td><blockquote>
<p>6</p>
</blockquote></td>
<td>130</td>
<td><blockquote>
<p>0.77</p>
</blockquote></td>
<td>0.585</td>
<td>0.585</td>
<td>0.585</td>
<td>NA</td>
<td><blockquote>
<p>5</p>
</blockquote></td>
<td><blockquote>
<p>401</p>
</blockquote></td>
</tr>
<tr class="odd">
<td colspan="3"><em><sup>a</sup></em> The maximum PC = 6.</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td colspan="6"><em>a</em> Hologram lengths (HL) were set to “53 59 61
71</td>
<td>83 97</td>
<td>151 199</td>
</tr>
</tbody>
</table>

> 257 307 353 401", with fragment length 4-7, and only atom and bonds
> flags are turned on.

For a given set of aligned molecules, CoMFA results (*q*^2^LOO) have
been reported to be largely dependent on the way in which these aligned
molecules are placed in the CoMFA region.^34^ To explore all the
possible orientations and placements of aligned molecules in the CoMFA
region, Wang et al. recently developed all-orientation search (AOS) and
all-placement search (APS) methods.^35^ These have been shown to be able
to generate CoMFA models with *q*^2^LOO significantly higher than those
obtained with standard CoMFA. However, no significant improvement of
*q*^2^~LOO~ was observed by applying AOS and APS to the NCTR data set.

To increase the precision and predictive ability of the QSAR models,
several factors were considered, such as reducing the lattice spacing
and/or the value of the filtering energy. Reducing these two parameters
did improve the *q*^2^LOO value slightly but not enough to justify the
extra computing time, which was consistent with our previous studies for
several smaller data sets.^12^

**HQSAR Model.** The performance of an HQSAR model can be optimized by
varying the fragment type and length parameters. The fragment type
parameters determine the compositional and topological structural
information encoded in the molecular hologram, while the fragment length
parameter controls the minimum and maximum length of fragments to be
included in the hologram. Through system­atic investigation of these
parameters, we used only elemental and bond-type information with the
fragment length between 4 and 7 to construct the final model. The model
results are shown in Figure 4B and Table 1. The model's *q*^2^~LOO~ and
*r*^2^ values were lower than those for the CoMFA model.

**Leave-*N*-Out Cross Validation.** In addition to the stan­dard LOO
validation, extensive LNO validation was con­ducted for both CoMFA and
HQSAR models. The predictive capability of a QSAR model for CoMFA and
HQSAR is generally determined by *q*^2^~LOO~ using the LOO
cross­validation procedure. The *q*^2^~LOO~ is primarily considered a
measure of the ability of the model to interpolate within the training
set population. Compared to the LOO procedure, the LNO procedure allows
more chemicals to be omitted for prediction to test the model's
stability. Thus, *q*^2^LNO accounts for more extrapolation of the model
than does *q*^2^LOO. In contrast to *q*^2^LOO, *q*^2^LNO is varied for a
selected *N* group

in each run because of the random nature of selection of chemicals in
the process. It is necessary to run LNO multiple

**Table 5.** Statistical Results of the CoMFA Models with or without
Inclusion of the Phenolic Ring Indicator and the log *P* Descriptors

+--------------------------+-----------+----------------+-------------+
| > statistics             | CoMFA     | > CoMFA        | > CoMFA     |
|                          |           | >              |             |
|                          |           | > with log     | with        |
|                          |           |                | phenolic    |
|                          |           | *P*            |             |
|                          |           | descriptors    | > indicator |
+--------------------------+-----------+----------------+-------------+
| *q*^2^LOO                | > 0.655   | > 0.648        | > 0.707     |
+--------------------------+-----------+----------------+-------------+
| *~r~*2                   | > 0.908   | > 0.880        | > 0.903     |
+--------------------------+-----------+----------------+-------------+
| SE                       | > 0.568   | > 0.635        | > 0.570     |
+--------------------------+-----------+----------------+-------------+
| contributions (%)        | 43        | 41.4           | 44.4        |
|                          |           |                |             |
| > steric                 |           |                |             |
+--------------------------+-----------+----------------+-------------+
| > electrostatic          | 57        | 56.3           | 48.8        |
+--------------------------+-----------+----------------+-------------+
| > log *P* and/or PhOH    | NA        | > 2.3          | > 6.8       |
+--------------------------+-----------+----------------+-------------+
| PCs                      | > 6       | > 6            | > 6         |
+--------------------------+-----------+----------------+-------------+

times (100 times in the study) for each random *N* group for valid
statistical analysis. Consequently, the standard deviation (SD) of
*q*^2^~LNO~ can be used to assess the model's stability of prediction
for diverse chemicals. As shown in Tables 3 and 4, the mean *q*^2^~LNO~
values decreased to about the same extent for both CoMFA and HQSAR
models as the left-out compounds were increased. CoMFA generated better
models than HQSAR for all left-out groups. Even when randomly leaving
33% of the training compounds out, the worst CoMFA model selected from
randomly trying 100 times still gave a highly robust *q*^2^LNO \> 0.5.
Moreover, the SD of *q*^2^LNO was smaller for CoMFA than for HQSAR,
indicating that CoMFA provided much more robust QSAR models for
prediction of structurally diverse chemicals.

**Enhancement of the CoMFA Model.** The initial com­parison between CoMFA
and HQSAR for the NCTR data set demonstrated that the CoMFA model was
more statisti­cally robust. To further improve the quality of the CoMFA
model, the effects of hydrophobic/hydrophilic characteristics and of a
phenolic ring indicator were also evaluated in combination with the
standard CoMFA field descriptors.

\(i\) **Inclusion of log *P. ***While the CoMFA descriptors encode
information for steric/electrostatic distribution on the molecular
surface, the absence of explicit representations that encode for
hydrophobic/lipophilic balance reduces its ability to model many in
vitro systems. To address this limitation, the CoMFA model was modified
by supplementing values of log *P*(log of the octanol-water partition
coefficient) with the CoMFA descriptors. As shown in Table 5, the model
was not improved with inclusion of log *P* values. The

**Table 6.** Prediction Results of the CoMFA Models with and without
PhOH and the HQSAR Model for Kuiper's Dataset

<table style="width:100%;">
<colgroup>
<col style="width: 33%" />
<col style="width: 11%" />
<col style="width: 6%" />
<col style="width: 3%" />
<col style="width: 9%" />
<col style="width: 6%" />
<col style="width: 4%" />
<col style="width: 9%" />
<col style="width: 6%" />
<col style="width: 3%" />
<col style="width: 6%" />
</colgroup>
<tbody>
<tr class="odd">
<td></td>
<td>normali zed</td>
<td colspan="3"><blockquote>
<p>CoMFA</p>
</blockquote></td>
<td colspan="3"><blockquote>
<p>CoMF A with PhOH</p>
</blockquote></td>
<td colspan="3"><blockquote>
<p>HQSAR</p>
</blockquote></td>
</tr>
<tr class="even">
<td><blockquote>
<p>name</p>
</blockquote></td>
<td><blockquote>
<p>log RBA</p>
</blockquote></td>
<td colspan="2">predicted</td>
<td>residual</td>
<td colspan="2">predict ed</td>
<td>residual</td>
<td colspan="2">predicted</td>
<td>residual</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>2,2’,3,3’,4’,5,5’-heptachloro-4-biphenylo l</p>
</blockquote></td>
<td>-1.498</td>
<td>-2.031</td>
<td></td>
<td>0.533</td>
<td>-1.792</td>
<td></td>
<td>0.294</td>
<td>-1.686</td>
<td></td>
<td>0.188</td>
</tr>
<tr class="even">
<td><blockquote>
<p>2,2’,3,3’,4’,5-hexachloro-4-biphenylol</p>
</blockquote></td>
<td>-1.650</td>
<td>-2.439</td>
<td></td>
<td>0.789</td>
<td>-1.920</td>
<td></td>
<td>0.270</td>
<td>-1.943</td>
<td></td>
<td>0.293</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>2,2’,3’,4,4’,5,5’-heptachloro-3-biphenylo l</p>
</blockquote></td>
<td>-1.549</td>
<td>-2.164</td>
<td></td>
<td>0.615</td>
<td>-1.710</td>
<td></td>
<td>0.161</td>
<td>-1.770</td>
<td></td>
<td>0.221</td>
</tr>
<tr class="even">
<td><blockquote>
<p>2,2’,3,4<em>'</em>,5,5'6-heptachloro-4-biphenylol</p>
</blockquote></td>
<td>-1.498</td>
<td>-2.194</td>
<td></td>
<td>0.696</td>
<td>-2.184</td>
<td></td>
<td>0.686</td>
<td>-1.640</td>
<td></td>
<td>0.142</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>2,2',3,4',5,5<em>'</em>-hexachloro-4-biphenylol</p>
</blockquote></td>
<td>-2.023</td>
<td>-2.175</td>
<td></td>
<td>0.152</td>
<td>-2.219</td>
<td></td>
<td>0.196</td>
<td>-2.012</td>
<td></td>
<td>0.011</td>
</tr>
<tr class="even">
<td><blockquote>
<p>2,2’,3’,4’,5’-pentachloro-4-biphenylol</p>
</blockquote></td>
<td>-1.498</td>
<td>-0.939</td>
<td></td>
<td>0.559</td>
<td>-0.820</td>
<td></td>
<td>0.678</td>
<td>-2.098</td>
<td></td>
<td>0.600</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>2,2’,3’,4’,6’-pentachloro-4-biphenylol</p>
</blockquote></td>
<td>-1.014</td>
<td>-1.211</td>
<td></td>
<td>0.197</td>
<td>-1.293</td>
<td></td>
<td>0.279</td>
<td>-1.999</td>
<td></td>
<td>0.985</td>
</tr>
<tr class="even">
<td><blockquote>
<p>2,2’,3’,5’,6’-pentachloro-4-biphenylol</p>
</blockquote></td>
<td>-1.549</td>
<td>-1.696</td>
<td></td>
<td>0.147</td>
<td>-1.187</td>
<td></td>
<td>0.362</td>
<td>-1.979</td>
<td></td>
<td>0.430</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>2,2’,4’,6’-tetrachloro-4-biphenylol</p>
</blockquote></td>
<td>-1.014</td>
<td>-1.464</td>
<td></td>
<td>0.450</td>
<td>-1.376</td>
<td></td>
<td>0.362</td>
<td>-2.263</td>
<td></td>
<td>1.249</td>
</tr>
<tr class="even">
<td><blockquote>
<p>2’,3,3’,4’,5’-pentachloro-4-biphenylol</p>
</blockquote></td>
<td>-1.458</td>
<td>-0.917</td>
<td></td>
<td>0.541</td>
<td>-1.076</td>
<td></td>
<td>0.382</td>
<td>-2.097</td>
<td></td>
<td>0.639</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>2,3,3’,4’,5-pentachloro-4-biphenylol</p>
</blockquote></td>
<td>-2.023</td>
<td>-2.537</td>
<td></td>
<td>0.514</td>
<td>-2.536</td>
<td></td>
<td>0.513</td>
<td>-2.255</td>
<td></td>
<td>0.232</td>
</tr>
<tr class="even">
<td><blockquote>
<p>2,3,3’,4’,5-pentachloro-4-biphenylol</p>
</blockquote></td>
<td>-2.507</td>
<td>-2.252</td>
<td></td>
<td>0.255</td>
<td>-1.894</td>
<td></td>
<td>0.613</td>
<td>-2.212</td>
<td></td>
<td>0.295</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>2’,3,3’,4’,6’-pentachloro-4-biphenylol</p>
</blockquote></td>
<td>-1.387</td>
<td>-1.264</td>
<td></td>
<td>0.123</td>
<td>-1.125</td>
<td></td>
<td>0.262</td>
<td>-1.971</td>
<td></td>
<td>0.584</td>
</tr>
<tr class="even">
<td><blockquote>
<p>2’,3,3’,5’,6’-pentachloro-4-biphenylol</p>
</blockquote></td>
<td>-1.720</td>
<td>-1.500</td>
<td></td>
<td>0.220</td>
<td>-1.291</td>
<td></td>
<td>0.429</td>
<td>-1.947</td>
<td></td>
<td>0.227</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>2’,3,4’,6’-tetrachloro-4-biphenylol</p>
</blockquote></td>
<td>-1.236</td>
<td>-1.506</td>
<td></td>
<td>0.270</td>
<td>-1.615</td>
<td></td>
<td>0.379</td>
<td>-2.238</td>
<td></td>
<td>1.002</td>
</tr>
<tr class="even">
<td><blockquote>
<p>2,4,6-trichloro-4’-biphenylol</p>
</blockquote></td>
<td>-0.106</td>
<td>-1.604</td>
<td></td>
<td>1.498</td>
<td>-1.496</td>
<td></td>
<td>1.390</td>
<td>-2.307</td>
<td></td>
<td>2.201</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>5-androstenediol</p>
</blockquote></td>
<td>-0.489</td>
<td>-0.658</td>
<td></td>
<td>0.169</td>
<td>-0.790</td>
<td></td>
<td>0.301</td>
<td>-2.450</td>
<td></td>
<td>1.961</td>
</tr>
<tr class="even">
<td><blockquote>
<p>16a-bromoestradiol</p>
</blockquote></td>
<td>1.408</td>
<td>0.332</td>
<td></td>
<td>1.076</td>
<td>0.868</td>
<td></td>
<td>0.540</td>
<td>0.278</td>
<td></td>
<td>1.130</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>16-ketoestradiol</p>
</blockquote></td>
<td>-0.378</td>
<td>0.582</td>
<td></td>
<td>0.960</td>
<td>1.104</td>
<td></td>
<td>1.482</td>
<td>0.264</td>
<td></td>
<td>0.642</td>
</tr>
<tr class="even">
<td><blockquote>
<p>17-epi-estriol</p>
</blockquote></td>
<td>0.984</td>
<td>-0.158</td>
<td></td>
<td>1.142</td>
<td>-0.112</td>
<td></td>
<td>1.096</td>
<td>0.038</td>
<td></td>
<td>0.946</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>2-OH-estrone</p>
</blockquote></td>
<td>-0.187</td>
<td>0.358</td>
<td></td>
<td>0.545</td>
<td>0.305</td>
<td></td>
<td>0.492</td>
<td>0.382</td>
<td></td>
<td>0.569</td>
</tr>
<tr class="even">
<td><blockquote>
<p>Raloxifene</p>
</blockquote></td>
<td>1.367</td>
<td>-0.236</td>
<td></td>
<td>1.603</td>
<td>-0.521</td>
<td></td>
<td>1.888</td>
<td>-1.840</td>
<td></td>
<td>3.207</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>Zearalenone</p>
</blockquote></td>
<td>0.368</td>
<td>-0.121</td>
<td></td>
<td>0.489</td>
<td>0.210</td>
<td></td>
<td>0.158</td>
<td>0.003</td>
<td></td>
<td>0.365</td>
</tr>
<tr class="even">
<td><blockquote>
<p>4,4’-biphenol</p>
</blockquote></td>
<td>&lt;-2.510</td>
<td>-1.805</td>
<td></td>
<td></td>
<td>-2.622</td>
<td></td>
<td></td>
<td>-2.473</td>
<td></td>
<td></td>
</tr>
<tr class="odd">
<td><blockquote>
<p>Ipriflavone</p>
</blockquote></td>
<td>&lt;-2.510</td>
<td>-4.252</td>
<td></td>
<td></td>
<td>-5.358</td>
<td></td>
<td></td>
<td>-2.712</td>
<td></td>
<td></td>
</tr>
<tr class="even">
<td><blockquote>
<p>predictive <em>q</em><sup>2</sup>pred</p>
</blockquote></td>
<td></td>
<td></td>
<td>0.63</td>
<td></td>
<td></td>
<td>0.62</td>
<td></td>
<td></td>
<td>0.15</td>
<td></td>
</tr>
</tbody>
</table>

**Table 7.** Prediction Results of the CoMFA Models with and without
PhOH and the HQSAR Model for Waller's Data Set

<table style="width:100%;">
<colgroup>
<col style="width: 31%" />
<col style="width: 11%" />
<col style="width: 6%" />
<col style="width: 4%" />
<col style="width: 9%" />
<col style="width: 6%" />
<col style="width: 4%" />
<col style="width: 9%" />
<col style="width: 6%" />
<col style="width: 4%" />
<col style="width: 6%" />
</colgroup>
<tbody>
<tr class="odd">
<td></td>
<td>normalized</td>
<td colspan="3"><blockquote>
<p>CoMFA</p>
</blockquote></td>
<td colspan="3"><blockquote>
<p>CoMFA with PhOH</p>
</blockquote></td>
<td colspan="3"><blockquote>
<p>HQSAR</p>
</blockquote></td>
</tr>
<tr class="even">
<td><blockquote>
<p>name</p>
</blockquote></td>
<td><blockquote>
<p>logRBA</p>
</blockquote></td>
<td colspan="2">predicted</td>
<td>residual</td>
<td>predicted</td>
<td></td>
<td>residual</td>
<td colspan="2">predicted</td>
<td>residual</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>2-<em>tert</em>-butylphenol</p>
</blockquote></td>
<td>-4.546</td>
<td>-3.831</td>
<td></td>
<td>0.715</td>
<td>-3.946</td>
<td></td>
<td>0.600</td>
<td>-3.393</td>
<td></td>
<td>1.153</td>
</tr>
<tr class="even">
<td><blockquote>
<p>3-<em>tert</em>-butylphenol</p>
</blockquote></td>
<td>-4.819</td>
<td>-3.225</td>
<td></td>
<td>1.594</td>
<td>-3.181</td>
<td></td>
<td>1.638</td>
<td>-3.009</td>
<td></td>
<td>1.810</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>2,4,6-trichloro-4’-biphenylol</p>
</blockquote></td>
<td>-0.158</td>
<td>-1.604</td>
<td></td>
<td>1.446</td>
<td>-1.496</td>
<td></td>
<td>1.338</td>
<td>-2.307</td>
<td></td>
<td>2.149</td>
</tr>
<tr class="even">
<td><blockquote>
<p>2-chloro-4,4’-biphenyldiol</p>
</blockquote></td>
<td>-0.610</td>
<td>-1.486</td>
<td></td>
<td>0.876</td>
<td>-1.532</td>
<td></td>
<td>0.922</td>
<td>-2.359</td>
<td></td>
<td>1.749</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>2,6-dichloro-4’-biphenylol</p>
</blockquote></td>
<td>-1.110</td>
<td>-2.406</td>
<td></td>
<td>1.296</td>
<td>-1.905</td>
<td></td>
<td>0.795</td>
<td>-2.488</td>
<td></td>
<td>1.378</td>
</tr>
<tr class="even">
<td><blockquote>
<p>2,3,5,6-tetrachloro-4,4’-bipheny ldiol</p>
</blockquote></td>
<td>-2.180</td>
<td>-0.815</td>
<td></td>
<td>1.365</td>
<td>-0.572</td>
<td></td>
<td>1.608</td>
<td>-1.528</td>
<td></td>
<td>0.652</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>2,2’,3,3’,6,6’-hexachloro-4-biph enylol</p>
</blockquote></td>
<td>-2.739</td>
<td>-3.055</td>
<td></td>
<td>0.316</td>
<td>-1.917</td>
<td></td>
<td>0.822</td>
<td>-1.852</td>
<td></td>
<td>0.887</td>
</tr>
<tr class="even">
<td><blockquote>
<p>2,2’3,4’,6,6’-hexachloro-4-biph enylol</p>
</blockquote></td>
<td>-2.596</td>
<td>-2.479</td>
<td></td>
<td>0.117</td>
<td>-1.985</td>
<td></td>
<td>0.611</td>
<td>-1.850</td>
<td></td>
<td>0.746</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>2,2’,3,6,6’-pentachloro-4-biphe nylol</p>
</blockquote></td>
<td>-1.966</td>
<td>-3.073</td>
<td></td>
<td>1.107</td>
<td>-2.280</td>
<td></td>
<td>0.314</td>
<td>-2.031</td>
<td></td>
<td>0.065</td>
</tr>
<tr class="even">
<td><blockquote>
<p>2,2’,5,5’-tetrachlorobiphenyl</p>
</blockquote></td>
<td>-2.667</td>
<td>-2.737</td>
<td></td>
<td>0.070</td>
<td>-3.956</td>
<td></td>
<td>1.289</td>
<td>-2.806</td>
<td></td>
<td>0.139</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>2,2’,4,4’,5,5’-hexachlorobiphe nyl</p>
</blockquote></td>
<td>-2.834</td>
<td>-1.522</td>
<td></td>
<td>1.312</td>
<td>-3.282</td>
<td></td>
<td>0.448</td>
<td>-2.568</td>
<td></td>
<td>0.266</td>
</tr>
<tr class="even">
<td><blockquote>
<p>2,2’,4,4’,6,6’-hexachlorobiphe nyl</p>
</blockquote></td>
<td>-1.870</td>
<td>-1.826</td>
<td></td>
<td>0.045</td>
<td>-2.982</td>
<td></td>
<td>1.111</td>
<td>-2.282</td>
<td></td>
<td>0.411</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>2,2’,3,3’,5,5’-hexachloro-6-bip henylol</p>
</blockquote></td>
<td>-2.691</td>
<td>-3.008</td>
<td></td>
<td>0.317</td>
<td>-2.176</td>
<td></td>
<td>0.515</td>
<td>-2.158</td>
<td></td>
<td>0.533</td>
</tr>
<tr class="even">
<td><blockquote>
<p>4’-deoxyindenestrol</p>
</blockquote></td>
<td>-1.371</td>
<td>-0.526</td>
<td></td>
<td>0.845</td>
<td>-0.010</td>
<td></td>
<td>1.361</td>
<td>2.281</td>
<td></td>
<td>3.652</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>4’-deoxyindenestrol</p>
</blockquote></td>
<td>-0.230</td>
<td>0.111</td>
<td></td>
<td>0.341</td>
<td>0.629</td>
<td></td>
<td>0.859</td>
<td>2.281</td>
<td></td>
<td>2.511</td>
</tr>
<tr class="even">
<td><blockquote>
<p>5’-deoxyindenestrol</p>
</blockquote></td>
<td>-0.587</td>
<td>-0.999</td>
<td></td>
<td>0.413</td>
<td>-0.382</td>
<td></td>
<td>0.204</td>
<td>2.129</td>
<td></td>
<td>2.715</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>5’-deoxyindenestrol</p>
</blockquote></td>
<td>0.353</td>
<td>-0.591</td>
<td></td>
<td>0.944</td>
<td>0.267</td>
<td></td>
<td>0.086</td>
<td>2.129</td>
<td></td>
<td>1.776</td>
</tr>
<tr class="even">
<td><blockquote>
<p>indenestrol A <em>(R)</em></p>
</blockquote></td>
<td>1.078</td>
<td>0.288</td>
<td></td>
<td>0.790</td>
<td>0.473</td>
<td></td>
<td>0.605</td>
<td>2.637</td>
<td></td>
<td>1.559</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>indenestrol A <em>(S)</em></p>
</blockquote></td>
<td>2.386</td>
<td>0.622</td>
<td></td>
<td>1.764</td>
<td>0.993</td>
<td></td>
<td>1.393</td>
<td>2.637</td>
<td></td>
<td>0.251</td>
</tr>
<tr class="even">
<td><blockquote>
<p>R5020</p>
</blockquote></td>
<td>-1.811</td>
<td>-0.703</td>
<td></td>
<td>1.108</td>
<td>-1.413</td>
<td></td>
<td>0.398</td>
<td>-2.306</td>
<td></td>
<td>0.495</td>
</tr>
<tr class="odd">
<td><blockquote>
<p>Zearalenone</p>
</blockquote></td>
<td>0.912</td>
<td>-0.121</td>
<td></td>
<td>1.033</td>
<td>0.210</td>
<td></td>
<td>0.702</td>
<td>0.003</td>
<td></td>
<td>0.909</td>
</tr>
<tr class="even">
<td><blockquote>
<p>DACT</p>
</blockquote></td>
<td><blockquote>
<p>NA<em><sup>a</sup></em></p>
</blockquote></td>
<td>-5.255</td>
<td></td>
<td></td>
<td>-6.258</td>
<td></td>
<td></td>
<td>-3.642</td>
<td></td>
<td></td>
</tr>
<tr class="odd">
<td><blockquote>
<p>Hydroxyflutamide</p>
</blockquote></td>
<td><blockquote>
<p>NA</p>
</blockquote></td>
<td>-1.041</td>
<td></td>
<td></td>
<td>-3.224</td>
<td></td>
<td></td>
<td>-4.049</td>
<td></td>
<td></td>
</tr>
<tr class="even">
<td><blockquote>
<p>M1</p>
</blockquote></td>
<td><blockquote>
<p>NA</p>
</blockquote></td>
<td>-2.550</td>
<td></td>
<td></td>
<td>-3.526</td>
<td></td>
<td></td>
<td>-3.761</td>
<td></td>
<td></td>
</tr>
<tr class="odd">
<td><blockquote>
<p>M2</p>
</blockquote></td>
<td><blockquote>
<p>NA</p>
</blockquote></td>
<td>-4.353</td>
<td></td>
<td></td>
<td>-5.672</td>
<td></td>
<td></td>
<td>-3.766</td>
<td></td>
<td></td>
</tr>
<tr class="even">
<td><blockquote>
<p>predictive <em>q</em><sup>2</sup>pred</p>
</blockquote></td>
<td></td>
<td></td>
<td>0.68</td>
<td></td>
<td></td>
<td>0.71</td>
<td></td>
<td></td>
<td>0.22</td>
<td></td>
</tr>
</tbody>
</table>

> *^a^* NA = no activity.

contribution of log *P* to the model was insignificant (2.3%), which was
consistent with our previous observation for several smaller estrogen
data sets.^12^

**(ii) Inclusion of Phenol Indicator (PhOH).** The crystal structure of
the E2-ER complex reveals that the hydroxyl group at the 3 position of
the A-ring forms hydrogen bonds with Glu 353 and Arg 394 and a water
molecule in the receptor binding site,^26^ thus stabilizing the binding
conforma­tion. Moreover, crystal evidence suggests this binding actionis
exactly the same for the other three ligands, DES, 4-OH-tamoxifen, and
raloxifene. That is, the crystal structure data are consistent with
historical observation that a chemical with a phenolic ring structure is
likely to exhibit estrogenic activity. Accordingly, a phenolic indicator
(PhOH) for the presence or absence of a phenolic ring of a molecule was
included in conjunction with the basic CoMFA descriptors. As shown in
Table 5, the inclusion of PhOH significantly enhanced the quality of the
model. Although the steric/

electrostatic field contributed predominately to the ER binding, the
6.8% contribution from PhOH confirms the appropriateness of inclusion of
appreciable contribution of the phenolic functional group.

**Prediction of the Test Sets.** Estrogenic EDs cover a wide range of
structurally diverse chemicals. The current challenge in developing QSAR
models for ER binding is no longer in constructing a statistically
robust model but in developing a model with the capability to accurately
predict the activity of such structurally diverse estrogens. The three
QSAR models, i.e., the CoMFA models with and without phenolic indicator
as well as the HQSAR model, were compared in their ability to predict
RBAs of two test sets. The predicted vs normalized activities for
Waller's and Kuiper's data sets as well as the predictive *q*^2^~pred~
results are listed in Tables 6 and 7, respectively. The CoMFA models
generally provided better prediction than the HQSAR model, which was
confirmed by much lower *q*^2^~pred~ values of the HQSAR model for both
test sets compared to those of the CoMFA models. Of 44 active chemicals,
the number of predictions with the residuals larger than 1.0 (a 10-fold
difference between predicted and normalized activity value) was 13, 11,
and 16 for the CoMFA, CoMFA with PhOH, and HQSAR models, respectively.
Moreover, 6 out of 16 predictions were off 100-fold or more for the
HQSAR models. The CoMFA models with and without PhOH were comparable for
prediction of active chemicals. However, the CoMFA with PhOH was better
in discriminating inactive from active chemicals. For 6 chemicals that
were reported to be inactive or to have undetectable activity in the
original references, the CoMFA model with PhOH provided best estimation
of their activities. 4,4*\'*-Biphenol shows undetectable activity from
the maximum experimentally determined limit in Kuiper's data set, while
it is active with log RBA = -1.7 in the ER binding assay using mouse
uterine cytosol.^18^ All three models predicted it to be active with an
average log RBA around -2.1.

DISCUSSION

Two QSAR methods, CoMFA and HQSAR, were evalu­ated for their ability to
predict ER binding of chemicals based on a larger structurally diverse
data set. The resultant QSAR models were compared with respect to the
statistical mea­sures from the leave-one-out and leave-*N*-out
cross-validation processes. The CoMFA yielded the best QSAR models in
terms of self-consistency and ability to predict test chemicals.
Furthermore, the results showed that it was advantageous to include the
phenolic indicator (PhOH) in the CoMFA model. The CoMFA model with PhOH
was not only internally robust but also provided the best activity
predictions for both active and inactive chemicals.

The rate of false positives and false negatives should be considered for
application of QSAR models for priority setting of a large number of
environmental chemicals. The positives or negatives are defined for the
chemicals whose activity values are larger or less than a predefined
cutoff activity value, respectively. The criteria to use for determin­ing
a cutoff are dependent on the nature of application. For drug discovery,
false positives are of primary concern because of the cost to bring such
a chemical with a low probability of being efficacious to the
development phase. A relativly higher cutoff value could be used for
such

application. In contrast, minimizing false negatives is more important
for regulatory purpose. Once a toxicant is labeled as a low priority, it
will cause more potential threat to public health than the one without
such a label, even though it might show active at lower doses. With
application of the present QSAR models for the prediction of 42 unique
active chemicals from Waller's and Kuiper's data sets, no false
negatives were observed, even for the chemicals with activities 1
million-fold below that of E2. This indicates that the QSAR models
reported in the study, particularly the CoMFA model with PhOH, have
potential utility for regula­tory purposes.

The utility of CoMFA has been demonstrated in a wide range of
applications.^36-39^ Since CoMFA employs steric and electrostatic field
descriptors that encode detailed information concerning intermolecular
interaction in three dimensions, it is able to provide the best model by
capturing the salient features associated with molecular recognition in
ER binding. However, aligning molecules requires substantial chemical
and biological knowledge and may be too time-consuming to allow
processing of a large number of diverse structures in CoMFA. This
difficulty limits the potential usage of CoMFA for screening tens of
thousands of chemicals. In the current form of our integrated four-phase
approach, the CoMFA model with PhOH is being applied in phase III to
provide quantitative predictions for chemicals passing through phases I
and II. To optimize the efficiency of phase III, a suite of
computational models in phase I and II with rapid screening capability
was used to eliminate the majority of chemicals that are the most
unlikely to bind to the ER. Care was exercised to minimize false
negatives when constructing the first two phases. The reduced data set
is now tractable for CoMFA prediction in phase III.

The use of CoMFA and other QSAR models can likely be used to predict
activity of chemicals that may act by other mechanisms, such as androgen
or other receptor binding, or mechanisms with more biological
complexity. This provides the possibility of developing a suite of
models for predicting multiple activities of a single chemical and/or
linking models through a mechanism sequence to predict activity at a
downstream event. This more comprehensive suite of models provides an
additional alternative for priority setting of potential EDs.

ACKNOWLEDGMENT

The authors acknowledge the Chemical Manufacturers Association (CMA) for
partial financial support of the project. H.F. and R.M.B. gratefully
acknowledge the Oak Ridge Institute for Science and Education Program,
supported by the U.S. Department of Energy (DOE) and the U.S. Food and
Drug Administration (FDA), for postdoctoral support. This work was also
partially supported by the FDA's Office of Women's Health.

REFERENCES AND NOTES

\(1\) Kavlock, R. J.; Daston, G. P.; DeRosa, C.; Fenner-Crisp, P.; Gray,
L. E.; Kaattari, S.; Lucier, G.; Luster, M.; Mac, M. J.; Maczka, C.;
Miller, R.; Moore, J.; Rolland, R.; Scott, G.; Sheehan, D. M.; Sinks,
T.; Tilson, H. A. Research needs for the risk assessment of health and
environ­mental effects of endocrine disruptors: a report of the U.S. EPA‑

> sponsored workshop. *En*V*iron. Health Perspect.* **1996,** *104,
> Suppl 4,* 715-740.

(2) Cooper, R. L.; Kavlock, R. J. Endocrine disruptors and reproductive
    development: a weight-of-evidence overview. *J. Endocrinol.*
    **1997,** *152,* 159-166.

(3) Colborn, T. Environmental estrogens: health implications for humans
    and wildlife. *En*V*iron. Health Perspect.* **1995,** *103, Suppl
    7,* 135-136.

(4) Colborn, T.; vom Saal, F. S.; Soto, A. M. Developmental effects of
    endocrine-disrupting chemicals in wildlife and humans \[see
    comments\]. *En*V*iron. Health Perspect.* **1993,** *101,* 378-384.

(5) U.S. Congress. The Food Quality Protection Act (FQPA) and the Safe
    Drinking Water Act (SDWA), 1996.

(6) EDSTAC.
    [[http://www.epa.gov/opptintr/opptendo/finalrpt.htm.]{.underline}](http://www.epa.gov/opptintr/opptendo/finalrpt.htm.)

(7) Shi, L. M.; Tong, W.; Fang, H.; Perkins, R.; Wu, J.; Tu, M.; Blair,
    R.; Branham, W.; Waller, C.; Sheehan, D. An integrated "Four-Phase"
    approach for priority setting of endocrine disruptors-Part 1: Phase
    I and II for prediction of potential estrogenic endocrine disruptor.
    *SAR QSAR En*V*iron. Res.* **2000,** submitted for publication.

(8) Lipinski, C. A.; Lombardo, F.; Dominy, B. W.; Feeney, P. J.
    Experimental and computational approaches to estimate solubility and
    permeability in drug discovery and development settings. *Ad*V*.
    Drug Deli*V*ery Re*V*.* **1997,** *23,* 3-25.

(9) Walker, J. D.; Waller, C. W.; Kane, S. *The Endocrine Disruption
    Priority Setting Database (EDPSD): A Tool to Rapidly Sort and
    Prioritize Chemicals for Endocrine Disruption Screening and
    Testing;* Walker, J. D., Ed.; SETAC: 2000.

(10) Hansch, C.; Leo, A. Exploring QSAR-Fundamentals and applications in
     chemistry and biology, American Chemical Society: Washington, DC,
     1995.

(11) Tong, W.; Perkins, R.; Strelitz, R.; Collantes, E. R.; Keenan, S.;
     Welsh, W. J.; Branham, W. S.; Sheehan, D. M. Quantitative
     structure-activity relationships (QSARs) for estrogen binding to
     the estrogen receptor: predictions across species. *En*V*iron.
     Health Perspect.* **1997**,*105*,1116-1124.

(12) Tong, W.; Perkins, R.; Xing, L.; Welsh, W. J.; Sheehan, D. M. QSAR
     models for binding of estrogenic compounds to estrogen receptor
     alpha and beta subtypes. *Endocrinology* **1997,** *138,*
     4022-4025.

(13) Tong, W.; Lowis, D. R.; Perkins, R.; Chen, Y.; Welsh, W. J.;
     Goddette, D. W.; Heritage, T. W.; Sheehan, D. M. Evaluation of
     quantitative structure-activity relationship methods for
     large-scale prediction of chemicals binding to the estrogen
     receptor. *J. Chem. Inf. Comput. Sci.* **1998,** *38,* 669-677.

(14) Bradbury, S.; Mekenyan, O.; GT, A. Quantitative structure-activity
     relationships for polychlorinated hydroxybiphenyl estrogen receptor
     binding affinity- An assessment of conformer flexibility.
     *En*V*iron. Toxicol. Chem.* **1996,** *15,* 1945-1954.

(15) Waller, C. L.; Oprea, T. I.; Chae, K.; Park, H. K.; Korach, K. S.;
     Laws, S. C.; Wiese, T. E.; Kelce, W. R.; Gray, L. E., Jr.
     Ligand­based identification of environmental estrogens. *Chem. Res.
     Toxicol.* **1996,** *9,* 1240-1248.

(16) Wiese, T. E.; Polin, L. A.; Palomino, E.; Brooks, S. C. Induction
     of the estrogen specific mitogenic response of MCF-7 cells by
     selected analogues of estradiol-17*β:* a 3D QSAR study. *J. Med.
     Chem.* **1997,** *40,* 0, 3659-3669.

(17) Xing, L.; Welsh, W. J.; Tong, W.; Perkins, R.; Sheehan, D. M.
     Comparison of estrogen receptor alpha and beta subtypes based on
     comparative molecular field analysis (CoMFA). *SAR QSAR En*V*iron.
     Res.* **1999,** *10,* 215-237.

(18) Sadler, B. R.; Cho, S. J.; Ishaq, K. S.; Chae, K.; Korach, K. S.
     Three­dimensional quantitative structure-activity relationship study
     of nonsteroidal estrogen receptor ligands using the comparative
     molecular field analysis/cross-validated *r*^2^-guided region
     selection approach. *J. Med. Chem.* **1998,** *41,* 2261-2267.

(19) Zheng, W.; Tropsha, A. A novel variable selection QSAR approach
     based on the k-nearest neighbor principle. *J. Chem. Inf. Comput.
     Sci.* **2000,** *40,* 185-194.

(20) Blair, R.; Fang, H.; Branham, W. S.; Hass, B.; Dial, S. L.;
     Moland, C. L.; Tong, W.; Shi, L.; Perkins, R.; Sheehan, D. M.
     Estrogen receptor relative binding affinities of 188 natural and
     xenochemicals: structural diversity of ligands. *Toxicol. Sci.*
     **2000,** *54,* 138-153.

(21) Branham, W. S.; Dial, S. L.; Moland, C. L.; Hass, B.; Blair, R.;
     Fang, H.; Shi, L.; Tong, W.; Perkins, R.; Sheehan, D. M.
     Phytoestrogen

> and mycoestrogen binding to rat uterine estrogen receptor. *Am. J.
> Nutr.* **2000,** in press.

(22) Perkins, R.; Anson, J.; Branham, W.; Fang, H.; Tong, W.; Welsh, W.;
     Chen, Y.; Meehan, J.; Jackson, M.; Nossaman, R.; Shi, L.;
     Sheehan, D. *The Estrogen Knowledge Base (EKB), A Prototype
     Toxicological Knowledge Base for Endocrine Disrupting Compounds;*
     Walker, J. D., Ed.; SETAC: 2000.

(23) Fang, H.; Tong, W.; Perkins, R.; Soto, A.; Prechtl, N.;
     Sheehan, D. M. Quantitative comparison of in vitro assays for
     estrogenic activity. *En*V*iron. Health Perspect.* **2000,** *108,*
     723-729.

(24) Zacharewski, T. Identification and assessment of endocrine
     disrup­tors: limitations of in vivo and in vitro assays. *En*V*iron.
     Health Perspect.* **1998,** *106, Suppl 2,* 577-582.

(25) Kuiper, G. G.; Lemmen, J. G.; Carlsson, B.; Corton, J. C.; Safe, S.
     H.; van der Saag, P. T.; van der Burg, B.; Gustafsson, J. A.
     Interaction of estrogenic chemicals and phytoestrogens with
     estrogen receptor beta. *Endocrinology* **1998,** *139,* 4252-4263.

(26) Brzozowski, A. M.; Pike, A. C.; Dauter, Z.; Hubbard, R. E.; Bonn,
     T.; Engstrom, O.; Ohman, L.; Greene, G. L.; Gustafsson, J. A.;
     Carlquist, M. Molecular basis of agonism and antagonism in the
     oestrogen receptor. *Nature* **1997,** *389,* 753-758.

(27) Shiau, A. K.; Barstad, D.; Loria, P. M.; Cheng, L.; Kushner, P. J.;
     Agard, D. A.; Greene, G. L. The structural basis of estrogen
     receptor/ coactivator recognition and the antagonism of this
     interaction by tamoxifen. *Cell* **1998,** *95,* 927-937.

(28) von Angerer, E. *The estrogen receptor as a target for rational
     drug design;* R.G. Landes Co.: Georgetown, TX, 1995.

(29) Anstead, G. M.; Carlson, K. E.; Katzenellenbogen, J. A. The
     estradiol pharmacophore: ligand structure-estrogen receptor binding
     affinity relationships and a model for the receptor binding site.
     *Steroids* **1997,** *62,* 268-303.

(30) Bucourt, R.; Vignau, M.; Torelli, V. New Biospecific adsorbents for
     the purification of estradiol receptor. *J. Biol. Chem.* **1978,**
     *253,* 8221-8228.

(31) Fang, H.; Tong, W.; Shi, L.; Blair, R.; Perkins, R.; Branham, W.
     S.; Dial, S. L.; Moland, C. L.; Sheehan, D. M. Structure activity
     relationship for a large diverse set of natural, synthetic and
     environ­mental chemicals. *Chem. Res. Toxicol.* **2000,** in press.

(32) Cramer, R. D. I.; Bunce, J. D.; Patterson, D. E. Crossvalidation,
     bootstrapping, and partial least squares compared with multiple
     regression in conventional QSAR studies. *QSAR* **1988,** *7,*
     18-25.

(33) Cramer, R. D.; Patterson, D. E.; Bunce, J. D. Comparative molecular
     field analysis (CoMFA). 1. Effect of shape on binding of steroids
     to carrier proteins. *J. Am. Chem. Soc.* **1988,** *110,*
     5959-5967.

(34) Cho, S. J.; Tropsha, A. Cross-validated *R*^2^-guided region
     selection for comparative molecular field analysis: a simple method
     to achieve consistent results. *J. Med. Chem.* **1995,** *38,*
     1060-1066.

(35) Wang, R.; Gao, Y.; Lin, L.; Lai, L. All orientation search and
     all­placement search in Comparative Molecular Field Analysis. *J.
     Mol. Model.* **1998,** *4,* 276-283.

(36) Tong, W.; Collantes, E. R.; Chen, Y.; Welsh, W. J. A comparative
     molecular field analysis study of *N*-benzylpiperidines as
     acetylcho­linesterase inhibitors. *J. Med. Chem.* **1996,** *39,*
     380-387.

(37) Tong, W.; Collantes, E. R.; Welsh, W. J.; Berglund, B. A.;
     Howlett, A. C. Derivation of a pharmacophore model for anandamide
     using constrained conformational searching and comparative
     molecular field analysis. *J. Med. Chem.* **1998,** *41,*
     4207-4215.

(38) Welsh, W. J.; Tong, W. D.; Collantes, E. R.; Chickos, J. S.;
     Gagarin, S. G. Enthalpies of sublimation and formation of
     polycyclic aromatic hydrocarbons (PAHs) derived from comparative
     molecular field analysis (CoMFA)-Application of moment of inertia
     for molecular alignment. *Thermochim. Acta* **1997,** *290,* 55-64.

(39) Welsh, W.; Tong, W.; Collantes, E. Heats of sublimition and
     formation of polycyclic aromatic hydrocarbons (PAHs) derived from
     comparative molecular field analysis (CoMFA): Application of moment
     of inertia for molecular alignment. *Thermochim. Acta* **1996,**
     *290,* 55-64.

> CI000066D