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Combining docking and comparative molecular similarity indices analysis (COMSIA) to predict estrogen activity and probe molecular mechanisms of estrogen activity for estrogen compounds YANG XuShu1,2, WANG XiaoDong1†, JI Li1, LI Rong1, SUN Cheng1 & WANG LianSheng1 1

State Key Laboratory of Pollution Control and Resources Reuse, School of Environment, Nanjing University, Nanjing 210093, China; 2 School of Pharmacy, Nanjing Medical University, Nanjing 210029, China

Estrogen compounds are suspected of disrupting endocrine functions by mimicking natural hormones, and such compounds may pose a serious threat to the health of humans and wildlife. Close attention has been paid to the prediction and molecular mechanisms of estrogen activity for estrogen compounds. In this article, estrogen receptor α subtype (ERα) –based comparative molecular similarity indices analysis (COMSIA) was performed on 44 estrogen compounds with structural diversity to find out the structural relationship with the activity and to predict the activity. The model with the significant correlation and the best predictive power (R2 = 0.965, Q2LOO = 0.599, R2pred = 0.825) was achieved. The COMSIA and docking results revealed the structural features for estrogen activity and key amino acid residues in binding pocket, and provided an insight into the interaction between the ligands and these amino acid residues. estrogen compounds, receptor-based, docking, comparative molecular similarity indices analysis (COMSIA), quantitative structure-activity relationship (QSAR)

Intensive research has revealed that estrogen compounds can imitate natural hormones and have the potential to interrupt the normal functioning of the endocrine systems of humans and wildlife by regulating the estrogen-related transcriptional activity after binding the estrogen receptor, thus such compounds may pose a serious threat to the health of humans and wildlife[1]. Close attention has been paid to the prediction and molecular mechanisms of estrogen activity for estrogen compounds[2–7]. Quantitative structure-activity relationship (QSAR) techniques can be used to predict the estrogen activity on the basis of the molecular structure of the compounds for the estrogen screening and further for the ecological risk assessment of estrogen compounds[6,7]. Three-dimensional quantitative structure-activity relationship (3D-QSAR), e.g., comparative molecular field www.scichina.com | csb.scichina.com | www.springerlink.com

analysis (CoMFA), can simulate the ligand-receptor interaction and analyze the variance of three dimensional fields (steric field and electrostatic fields) to find out structure-activity relationship. Furthermore, it can reveal the mechanisms of bioactivity of compounds, thus having more and more application in environmental science, ecotoxicology and so on[3,4,8–10]. For example, Tong et al.[4,9,10] performed comparative molecular field analysis on different data sets resulting in the predictive models. However, these research mainly made an endeavour to predict the estrogen activity, yet did not elucidate the Received April 12, 2008; accepted September 15, 2008 doi: 10.1007/s11434-008-0480-5 † Corresponding author (email: [email protected]) Supported by National Natural Science Foundation of China (Grant No. 20507008), National Natural Science Foundation Key Project of China (Grant No. 20737001) and National Basic Research Program of China (973 Program) (Grant No. 2003CB415002)

Chinese Science Bulletin | December 2008 | vol. 53 | no. 23 | 3626-3633

1 Materials and methods 1.1 Data sets for analysis In this study, a total of 44 estrogen compounds including estradiol-17β (E2), estrone(E1), estriol(E3) and their derivatives, antiestrogens, phytoestrogens and stilbene estrogens were utilized to construct 3D-QSAR models using the biological data obtained from the ref. [13]. These compounds were divided into a training set (37 compounds) and a test set (7 compounds) as shown in Table 1. The logarithm of the relative binding affinity (LogRBA) was adopted as a dependent variable in the CoMSIA calculations. 1.2 Molecular modeling. The three-dimensional structures of compound 6(E2), compound 38(DES), compound 41(Tamoxifen) and compound 44(Raloxifene) were obtained from their

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X-ray structures in complex with human ERα, and all other molecules were similarly constructed based on the structure of E2 by using SYBYL programming package version 7.3. The geometry of each molecule was optimized using the Tripos force field with the conjugate gradient method to an energy change convergence criterion of 0.001 kcal/mol·Å. The Gasteiger-Hückel charges were calculated for all compounds. 1.3 Flexible alignment The flexible alignment was obtained by docking the estrogen compounds into the active site of the estrogen receptor α subtype (PDB ID: 1ERE) using Surflex-Dock available in SYBYL7.3. Consisting of molecular probes (CH4, C==O, N―H), the protomol is a representation of the receptor binding cavity to which putative ligands are aligned. Surflex-Dock’s scoring function, which contains hydrophobic, polar, repulsive, entropic and solvation terms, was trained to estimate the ligand-receptor interaction. The top-scored conformation based on the Surflex-Dock scoring functions was selected as final bioactive conformation. Surflex-Dock was used to dock estradiol-17β and DES into the active site of the E2-ERα complex (PDB ID: 1ERE) and DES-ERα complex (PDB ID:3ERD), respectively. Protomol was generated by the Automatic method, setting the Threshold and Bloat parameters as 0.5 and 1.0, respectively. The root-mean-square deviations (RMSD) of 0.155 Å and 0.482 Å were yielded by superposing the docked conformations of estradiol-17β and DES to their experimental conformations in 1ERE and 3ERD, respectively, suggesting a high docking reliability of Surflex-Dock in reproducing the experimentally observed binding mode for the estrogen compounds[14]. Then all other estrogen compounds were docked into the active site of the E2-ERα complex (PDB ID: 1ERE) under the same condition. The result of flexible alignment is shown in Figure 1. The bioactive conformations obtained from docking were subjected to COMSIA analysis. 1.4 COMSIA analysis CoMSIA calculates similarity indices at the intersections of a surrounding lattice. The similarity index AF,k for a molecule j with atoms at the grid point q is determined as follows

AFq , K ( j ) = ∑ ωprobe, k ωik e

−α ⋅riq2

,

(1)

i

YANG XuShu et al. Chinese Science Bulletin | December 2008 | vol. 53 | no. 23 | 3626-3633

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ENVIRONMENTAL CHEMISTRY

structural features for an activity and specifically the key amino acid residues in binding pocket from the viewpoint of ligand-receptor interaction. In comparison with CoMFA, comparative molecular similarity indices analysis (COMSIA) was conducted later[11], whose theory is based on that the bioactivity of a series of compounds with the same mechanisms depends on the variance of nonbonding interacting force between ligand and receptor. In comparison with CoMFA, COMSIA can simultaneously specify steric field, electrostatic field, hydrophobic field, hydrogen bond donor field and hydrogen bond acceptor field around a compound, and thus can reveal overall structural information related to the bioactivity of a compound[11,12]. It is critical for compounds to be superimposed for whether CoMFA or COMSIA[8,11,12]. Since estrogen compounds have extensive source and their structures are complex, it is difficult to determine the alignment rule especially for flexible molecules. In this article, structure-activity relationship of estrogen compounds was investigated using COMSIA based on the bioactive conformations obtained by docking all estrogen compounds into the binding site of the estrogen receptor (PDB ID: 1ERE). The statistically significant model with the best predictive power was achieved, meanwhile COMSIA and docking results revealed the structural features for estrogen activity and key amino acid residues in binding pocket, and provided an insight into the interaction between the ligands and these amino acid residues.

Table 1 Structures of the estrogen compounds

Comp 1 2 3 4 5 6(E2) 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22* 23* 24*

R1 (S)―OH ==O (R)―OH (S)―OH (S)―OH (R)―OH =O (R)―OH (R)―OH =O (R)―OH (R)―OH (R)―OH (R)―OH ==O ==O ==O ==O (R) ―OH (R) ―OH (R) ―OH (R)―OH (R) ―OH (S) ―OH

R2 H ==O (S)―OH (S)―OH (R)―OH H H H (S)―OH H H H H (S)―OH H H H H H H H =O H H

R3 H H (S)―OH H H H H H H H H H H H H H H H H H H H H H

R4 H H H H H H H H H H H H H H H H H H (S)―OH H H H H ==O

R5 H H H H H H H H H ―OH ―OH H ―OCH3 ―OCH3 H H ―NO2 ―NH2 H H H H H H Comp 25 26 27 28

R6 H H H H H H ―OH ―OH ―OH H H ―OCH3 H H ―NO2 ―NH2 H H H H H H H H

R7 H H H H H H H H H H H H H H H H H H H H H H

R8 H H H H H H H H H H H H H H H H H H H ―OCOCH3 (R)―C≡C―OCH3 H H H

―CH3 H

R (CH2)6―OH (CH2)6―O―Ph (CH2)9―SO-(CH2)3―CF2CF3 H

Comp

R

29

==O

30

(R) ―OH

Comp

R

31

(R)―OH

32

(S)―OH

33*

==O

Comp

R

34

==O

35

(R)―OH (To be continued on the next page)

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Structure

Comp

36 (Coumestrol)

41 (Tamoxifen)

37

42*

38 (DES)

43* (Hexestrol)

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(Continued) Comp

Structure

39 (Dienestrol) 44* (Raloxifene) 40 (Genistein)

* These compounds were used as a test set.

(R2pred) and the external validation parameter (Q2EXT) based on the external test set were used to evaluate the predictive power of the developed models[7].

2 Results and discussion COMSIA steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor interaction fields were calculated. Then the four kinds of combinations of the five fields were performed to build 3DQSAR models using a partial least squares (PLS) approach. The model derived from steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor interaction fields is of the highest quality, as shown in Table 2. The statistic results are as follows: PCs = 5, Q2LOO＝0.599, SEP = 0.500, R2pred = 0.825, Q2EXT = 0.830, R2 = 0.965, SEE = 0.148, F-test =170.257. The scatter plot of experimental versus predicted activities for the training set and the test set is presented in Figure 2. The steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor field contributions to the COMSIA model were 5.1%, 30.7%, 19.6%, 24.3% and 20.3%, respectively. The steric contribution contour


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where ωik is the actual value of the physicochemical property k of atom i; ωprobe,k is the probe atom with a charge of +1, radius of 1 Å, hydrophobicity of +1, hydrogen bond donating of +1, and hydrogen bond accepting of +1; riq is the mutual distance between the probe atom at grid point q and the atom i of the molecule. The value of the so-called attenuation factor α was set to 0.3. A lattice of 2 Å grid spacing was generated automatically. A partial least squares (PLS) approach was used to derive the 3D-QSAR model, in which the CoMSIA descriptors were used as independent variables and LogRBA values were used as dependent variables. The cross-validation with Leave-One-Out (LOO) option and the SAMPLS program were carried out to obtain the optimal number of components (PCs) used to determine non-cross-validated correlation coefficient R2, which together with standard error of estimate (SEE) and F-test values was used to estimate the degrees of overall correlation of the derived model. Leave-One-Out crossvalidated correlation coefficient Q2LOO together with cross-validated standard error of prediction (SEP) was used to assess the internal predictive ability of built models[7], and the predictive correlation coefficient

Table 2

The results of COMSIA COMSIAa)

COMSIAb)

COMSIAc)

COMSIAd)

Q2LOO

0.358

0.432

0.495

0.599

SEP

0.614

0.577

0.544

0.500

R2

0.831

0.846

0.900

0.965

SEE

0.315

0.301

0.242

0.148

F-test

53.995

60.491

99.133

170.257

R2pred

0.825

Q2EXT PCs

0.830 3

3

3

5

9.4

6.4

5.1

Contribution (%) Stetic

14.4

Electronstatic

85.6

Hydrophobic H-bond donor H-bond acceptor

57.5

40.6

30.7

33.1

22.5

19.6

30.5

24.3 20.3

a) The descriptors of COMSIA are composed of steric and electronstatic fields; b) The descriptors of COMSIA are composed of steric, electronstatic and hydrophobic fields; c) The descriptors of COMSIA are composed of steric, electronstatic, hydrophobic and hydrogen bond donor fields; d) The descriptors of COMSIA are composed of steric, electronstatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields.

map of CoMSIA is plotted in Figure 3(a)(compound 6 is displayed as a reference). The large green polyhedron located over the C11, C12, C13 and C17 positions indicates of the C-ring that bulky substituents at the position would be favorable for the estrogen activity. For example, compounds 6 (E2), 25, 26 and 27 which have (R)― CH3, (CH2)6―OH, (CH2)6―O―Ph, and (CH2)9―SO― (CH2)3―CF2CF3 located at this region, respectively, exhibit stronger activities. The yellow contours below the C7, C8 positions of the B-ring and the C13, C15 positions of the D-ring and over the benzene ring sug- gest bulky groups would decrease estrogen activities at these positions. The crystal structure of estrogen-receptor(ERα) complex indicates that the binding pocket is narrowly formed by residues LEU349, PHE404, LEU391, LEU387, LEU349, MET388 and so on around the benzene ring of E2, whereas the binding pocket is spaciously formed by residues MET343, THR347, LEU525, TRP383, LEU346 and so on over the C11, C12 and C13 positions of the C-ring, which agrees well with the analysis of the contour map of the steric field. The electrostatic contribution contour map of CoMSIA is plotted in Figure 3B(compound 6 is displayed as a reference). The large blue contour found in the vicinity of substituents around the C16 and C17 regions of the D-ring suggests that electropositive substituents could 3630

favor an activity at this position. The hydroxyl group (a strong electropositive substituent) at the benzene ring is a very important feature for a estrogen activity[7,15]. For example, compound 41 (Tamoxifene) does not have electropositive hydroxyl group, thus showing a lower activity. The strong electronegative ―NO2 at the benzene ring and O atom of C==O at the C17 position of compound 15 are located at the blue region, thus compound 15 shows a much lower activity (LogRBA = −0.15). Compound 6 (E2) with a strong electropositive hydroxyl group at the (R)-substituent of C17 position has an estrogen activity stronger than compound 1 (Estradiol-17α) with a weak electropositive H atom at the same position. The strong electronegative O atoms of C==O at the C16 and C17 positions of compound 2 are found at the blue region, thus compound 2 exhibits a lower activity (LogRBA = 0.25). The red contours at the (S)-substituents of C16 and C17 regions and the C5 position of the benzene ring indicate that the electronegative substituent near the position is favorable for a estrogen activity. Compounds 3 and 40 show lower activities for strong electropositive hydroxyl groups located at the red contour. The hydrophobic contribution contour map and the key amino acid residues interacting with hydrophobic and hydrophilic regions are presented in Figure 4(a). A large yellow contour is found at the benzene ring position, indicating that hydrophobic groups at this position may lead to an increase of the estrogen activity. The benzene ring (a strong hydrophobic substituent) is another important feature for the estrogen activity[7,15]. A large white contour appears at the C17 position of E2, indicating that hydrophilic groups could favor the estrogen activity at or near this position. The crystal structure of the complex indicates that the hydrophobic amino acid residues PHA404, LEU391, LEU349 and LEU387 in the binding pocket are located around the benzene ring of E2, which have a strong hydrophobic interaction with the benzene ring of compounds. The hydrophilic residues GLY521, HIS524 and LEU525 found near the C17 position form a strong hydrophilic interaction with the hydrophilic substituents at this position. The docking results are in a good agreement with the analysis of the hydrophobic contribution contour map (Figure 4(a)). The hydrogen bond donor contribution contour map and the key amino acid residues forming hydrogen bond interactions with E2 and


ARTICLES Figure 1 The result of flexible alignment of estrogen compounds in the binding pocket.

Figure 3 (a) COMSIA stDev*Coeff contour plots for steric fields; (b) COMSIA stDev*Coeff contour plots for electrostatic fields. Compound 6 is displayed as a reference. Sterically favored/disfavored areas are shown in green/yellow, while the blue/red polyhedra depict the favorable site for positively/negatively charged groups.

H2O are shown in Figure 4(b). A large cyan contour is located near the (R)-substituent of the C17 position, a purple contour appears at the (S)-substituent of the C15 position, and cyan and purple contours are found near the hydroxyl group at the benzene ring. The cyan and purple contours indicate that the introduction of the hydrogen bond donor and acceptor group at this position could be favorable for the estrogen activity, respectively. For example, compounds 6, 31 and 37 have the hydrogen bond donor group (R)-OH at the C17 position and hydroxyl group at the benzene ring as both hydrogen bond donor and acceptor, thus exhibiting higher activities. The crystal structure of the complex indicates the O atom of hydroxyl group at the benzene ring as hydrogen bond acceptor forming hydrogen bonds with residue ARG394 and the H atom of H2O and the H atom of hydroxyl group at the benzene ring as hydrogen bond do-


Figure 2 Predicted versus experimental estrogen activities (LogRBA) of compounds in the training set and the test set.

Figure 4 (a) CoMSIA stDev*Coeff contour plots for hydrophobic field and the key amino acid residues interacting with hydrophobic and hydrophilic regions. Compound 6 was used as a representative ligand. The yellow/white polyhedra depict favorable site for hydrophobic/hydrophilic groups; (b) CoMSIA stdev*Coeff hydrogen bond donor contour map and the key amino acid residues forming hydrogen bond interactions with E2 and H2O. Compound 6 is displayed as a reference. The cyan and purple contours indicate favorable and unfavorable hydrogen bond donor groups, respectively, for estrogen activities.Hydrogen bonds are shown as dotted red lines.


3631

not forming hydrogen bonds with residue GLU353 and the O atom of H2O, which matches well with the hydrogen bond donor contribution contour map (Figure 4(b)). The ligand-based CoMFA method was performed on the estrogen compounds by Zhu et al.[13] to build the 3D-QSAR model, the result which is summarized in Table 3 with the research result of this article using receptor-based COMSIA method. Table 3 shows obviously that the receptor-based COMSIA model of this article is superior to the ligand-based CoMFA model by Zhu et al.[13] With respect to data sets, the data set of this article includes the complicated and flexible compounds (compounds 27,44 and so on), which are not included in the article by Zhu et al.[13]. In this article, the data set is divided into the training set and the test set, whereas in the article by Zhu et al.[13], only training set is included. With respect to the explanation of mechanisms, Zhu et al.[13] elucidated the structure features related to the estrogen activity using steric and electrostatic fields. For example, the bulky substituents near the C16 and C17 positions would be favorable for the enhanced activity. Electropositive substituents near the C17 position would increase the activity, and electronegative substituents near the C16 and benzene ring positions are favorable for the activity. These analyses agree well with the research results of this article. In addition, this article still reveals that electropositive substituents at the C3 position of the benzene ring could favor the estrogen activity, which is in a good agreement with refs. [4, 15]. In addition to the structural features of stetic and electronstatic fields, this article still reveals the structural features of hydrophobic and hydrogen bond donor field related to the estrogen activity, investigates the ligand-receptor (ERα) interaction using flexible docking and elucidates

1

R2

SEE

PCs

F-test

Q2LOO

0.963

0.140

8

125.050

0.531

0.965

0.148

5

170.257

0.599

the key amino acid residues in binding pocket, thus revealing more overall mechanisms of the estrogen activity for compounds in respect to ligands and a receptor.

3 Conclusions In this article, the three-dimensional bioactive conformations of estrogen compounds in the binding pocket are determined by successfully using flexible docking based on the structure of the receptor (ERα), thus the difficulty is conquered to determine the alignment rule for the compounds of complicated and flexible structures. The COMSIA analysis was performed to investigate structure-activity relationships of the estrogen compounds to result in the 3D-QSAR model of a significant correlation and predictive power, which revealed the structural features related to the estrogen activity, i.e., strong electropositive substituents (hydroxyl group) at the benzene ring and the C17 position of the D-ring, hydrophobic groups (the benzene ring) and bulky substituents over the C11, C12 and C13 positions of C-ring are favorable for an estrogen activity, whereas bulky substituents at the benzene ring are unfavorable for an activity. In addition, docking analysis revealed the main hydrophobic amino acid residues PHA404, LEU391, LEU349 and LEU387, the main hydrophilic residues GLY521, HIS524 and LEU525 and the residues ARG394, GLU353 and HIS524 to form hydrogen bonds, which were related to an estrogen activity.

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Science in China Series B: Chemistry EDITOR-IN-CHIEF LI Lemin College of Chemistry and Molecular Engineering Peking University Beijing 100871, China

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