Nuclear Receptor ResearchVol. 1 (2014), Article ID 101076, 8 pagesdoi:10.11131/2014/101076

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Research Article

Identification of VDR Antagonists among NuclearReceptor Ligands Using Virtual Screening

Kelly Teske1, Premchendar Nandhikonda1, Jonathan W. Bogart1, Belaynesh Feleke1,Preetpal Sidhu1, Nina Y. Yuan1, Joshua Preston1, Robin Goy1, Lanlan Han1, Nicholas R.Silvaggi1, Rakesh K. Singh2, Daniel D. Bikle3, JamesM. Cook1, and Leggy A. Arnold1

1Department of Chemistry and Biochemistry, University of Wisconsin-Milwaukee, WI 53211, USA2Molecular Therapeutics Laboratory, Program in Women’s Oncology, Department of Obstetrics and Gynecology,Woman and Infant’s Hospital of Rhode Island, Alpert Medical School, Brown University, Provence, RI 02903, USA3Endocrine Research Unit, Department of Medicine, Veterans Affairs Medical Center, San Francisco, CA 94121, USA

Corresponding Author: Leggy A. Arnold; email: arnold2@uwm.edu

Received 1 January 2014; Accepted 8 April 2014

Editor: Christopher Lau

Copyright © 2014 Kelly Teske et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract. Herein, we described the development of two virtual screens to identify new vitamin D receptor (VDR) antagonistsamong nuclear receptor (NR) ligands. Therefore, a database of 14330 nuclear receptor ligands and their NR affinities was assembledusing the online available “Binding Database.” Two different virtual screens were carried out in conjunction with a reported VDRcrystal structure applying a stringent and less stringent pharmacophore model to filter docked NR ligand conformations. Thepharmacophore models were based on the spatial orientation of the hydroxyl functionalities of VDR’s natural ligands 1,25(OH2)D3and 25(OH2)D3. The first virtual screen identified 32 NR ligands with a calculated free energy of VDR binding of more than −6.0kJ/mol. All but nordihydroguaiaretic acid (NDGA) are VDR ligands, which inhibited the interaction between VDR and coactivatorpeptide SRC2-3 with an IC50 value of 15.8 𝜇M. The second screen identified 162 NR ligands with a calculated free energy ofVDR binding of more than −6.0 kJ/mol. More than half of these ligands were developed to bind VDR followed by ER𝛼/𝛽 ligands(26%), TR𝛼/𝛽 ligands (7%), and LxR𝛼/𝛽 ligands (7%). The binding between VDR and ER𝛼 ligand H6036 as well as TR𝛼/𝛽 ligandtriiodothyronine and a homoserine analog thereof was confirmed by fluorescence polarization.

Keywords: Virtual screening, nuclear receptor, vitamin D receptor, thyroid receptor, estrogen receptor

1. Introduction

Nuclear receptors (NR) are one of the most importantdrug targets today [1]. During the last decades, thousandsof small molecules have been developed to selectivelybind nuclear receptors. This development was supported byhigh-throughput screening (HTS) and rational drug design.Although the activity of NR ligands is very importantin terms of dosage and suppression of side effects, the

selectivity of ligands towards a particular NR is crucial forspecific pharmacological effects. Usually NR ligands areinvestigated with respect to their NR isoform selectivity. Forinstance, estrogen receptor (ER) ligands are evaluated forFor instance, estrogen receptor (ER) ligands are evaluatedfor their selectivity towards ER𝛼 and ER𝛽. The ER isoformsare tissue-selectively distributed in the human body. [2].Once a promising ligand has been identified, further analysiswith respect to other closely related NR is conducted based

2 Nuclear Receptor Research

on phylogenetic distance or NR sequence similarity [3, 4].Schapira et al. introduced an alternative concept of NRsimilarity based on the likelihood that two NRs share acommon ligand [5]. Therefore, sixteen NR crystal structuresand 78 NR ligands were used in a computational approachto determine the cross-reactivity of NR ligands. Herein, wepresent an alternative approach by using a large library ofNR ligands and one receptor, the vitamin D receptor (VDR).Among 14330 compounds, we identified four new VDRantagonists that were originally developed as ligands forother nuclear receptors. Thus, virtual screening represents auseful tool to identify those NRs that are likely to interactwith a newly synthesized NR ligand.

2. Materials andMethods

Reagents. LG190178 was synthesized using a publishedprocedure [6].

Virtual Screens. A library of nuclear receptor ligandswas assembled using “The Binding Database.” The databaseincluded 14330 compound structures and their nuclearreceptor binding data (EC50, IC50, or K𝐷). Weakly activeligands that had estimated binding data (e.g., >5000 𝜇M)or inactive compounds (e.g., no binding observed) wereassigned a zero activity. Compounds that were not testedwere assigned an empty field. The database only includedcompounds that are with one or more nuclear receptors.For racemic compounds only one representative stereoisomerwas used for the screen. All compounds were minimizedusing an MMFF94x force field. Energy minimization wasterminated when the root mean square gradient fell below0.1. The root mean square gradient is the norm of the gradienttimes the square root of the number of atoms. The ionizationstate of functional groups was adjusted to pH 7. Moleculeconformations were generated from a single 3D conformerby applying a collection of preferred torsion angles to therotatable bond during the virtual screen. The crystal structureof VDR bound to 1,25(OH)2D3 (PDB ID 1DB1) [7] wasprepared for docking using the MOE structure preparationfunction to repair any structural defects in the pdb file. Inaddition, a protonation 3D function was used to optimizethe hydrogen bond network and hydrogen positions. Finallyunbound water molecules were removed. The virtual screenwas carried out by selecting VDR-bound 1,25(OH)2D3 asbinding site and a triangle matcher for the placement ofcompounds. The triangle matcher function generated posesby superposition of ligand atom triplets and triplets ofreceptor site points. The receptor site points were alphasphere centers which represent locations of tight packing.At each iteration, a random triplet of ligand atoms and arandom triplet of alpha sphere centers were used to determinethe pose. The poses were scored using affinity London ΔGscoring that estimated the free energy of binding from eachgiven pose given in kJ/mol. Compound conformations that

did not satisfy the pharmacophore model 1 or 2 depicted inFigure 4 were eliminated.

Labeled Coactivator Peptides. The peptide SRC2-3(CLQEKHRILHKLLQNGNSPA) [8] was purchased andlabeled with the cysteine-reactive fluorophore (Alexa Fluor647 maleimide) in a 50:50 DMF/PBS mixture. After purifi-cation by high performance liquid chromatography, thecorresponding labeled peptide was dissolved in DMSO andstored at −20∘C.

Protein Expression and Purification. The VDR-LBDmtDNA was kindly provided by D. Moras [7] and cloned intothe pMAL-c2X vector (New England Biolabs). A detailedexpression and purification protocol for VDR-LBD wasreported previously [8].

Fluorescence Polarization Assay with VDR-SRC2-3.Agonistic and antagonistic activity was studied using aFP assay. This assay was conducted in 384-well blackpolystyrene plates (Corning) using a buffer [25 mM PIPES(pH 6.75) 50mM NaCl, 0.01% NP-40, and 2% DMSO],VDR-LBD protein (0.1 𝜇M), LG190178 (3𝜇M), and AlexaFluor 647-labeled SRC2-3 (5 nM). Small molecule transferinto a 20 𝜇L assay solution was accomplished using astainless steel pin tool (V&P Scientific), delivering 100nL of the serially diluted compound solution. Fluorescencepolarization was detected after 1 hour at excitation and emis-sion wavelengths of 650 nm and 665 nm, respectively. Threeindependent experiments were conducted in quadruplicate.The data were analyzed using nonlinear regression with avariable slope (GraphPadPrism).

3. Results

A library of 14330 NR ligands was compiled using “TheBinding Database.org” [9]. The sets of NR ligands weredownloaded individually and merged as a virtual smallmolecule library using MOE (molecular operating environ-ment). The number of ligands downloaded per NR is givenin Figure 1.

The NRs with the largest ligand databases are the per-oxisome proliferator-activated receptors (PPAR)𝛾 , PPAR𝛿,PPAR𝛼, the progesterone receptor (PR), the androgen recep-tor (AR), the ER𝛼, the ER𝛽, and the glucocorticoid receptor(GR) with more than a thousand ligands each. Overall,30 NRs are represented by their ligands in “The BindingDatabase” with a total of 14330 unique NR ligands. Manyof these ligands were investigated with regard to multipleNRs and some of them exhibited a significant affinity towardsmore than one NR.

The analysis to determine the global selectivity of ligandsamong nuclear receptors is restricted by the fact that limiteddata are available. We were surprised that only one NR wasinvestigated for the majority of NR ligands. 4006 ligands outof 14330, thus a quarter of the ligands, were investigated withtwo different NRs as illustrated in Figure 2.

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Nuclear Receptor Research 3

TRb,583 VDR,414

AR,1628

CAR,2

ERa,1826

ERb,1563

ERRa,78

ERRb,22

ERRg,29

FxR,571

GR,1738

HNR4a,242

LRH-1,52

LxRa,634

LxRb,712

MR,532

PPARa,3914

PPARd,1476

PPARg,2998

PR,1664

PxR,196

RARa,315

RARb,306

RARg,313

RORa,590

RxRa,456

TRa,481

RxRg,204RxRb,

202

Figure 1: Number of NR ligands deposited with “The Binding Database.”

157

52

7

1596

4006

41

1000

10000

100

1

10

1 2 3 4 5 7+6Number of NRs evaluated

NR

-lig

ands

Figure 2: Number of NR ligands that bind to multiple NRs.

Most of NR ligands tested with two NRs were ableto bind two NR isoforms with different affinity, such asNR𝛼 and NR𝛽, which applies to the liver X receptor (LXR),ER, and TR. Ligands that were developed for NRs havingthree isoforms such as the PPAR, the estrogen relatedreceptor (ERR), the retinoid X receptor (RXR), and theretinoic acid receptor (RAR) represent almost half of theNR library members (Figure 1). However, only a fractionof these ligands (1853) were evaluated with more thantwo NRs (Figure 2). Some examples of ligands that bindmultiple NRs, though with different affinity, are depicted inFigure 3.

Compound 1 (Figure 3(A)) was developed by LigandPharmaceuticals as RXR𝛼 antagonist [10]. Although theselectivity with respect to RARs is very high, there is amoderate selectivity toward other RXR subtypes. In addition,a synergistic activation of transcription was observed whencotransfected with PPAR𝛾 in the presence of Rosiglitazone.Guggulsterone (Figure 3(B)) was predominately evaluatedwith steroid hormone receptors [11]. The compound hasa strong affinity for the mineralocorticoid receptor (MR)and the pregnane X receptor (PXR) [12]. Compound 2(Figure 3(C)) is a very potent GR antagonist, which stillhas a significant activity towards PR and AR [13]. Finally,

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4 Nuclear Receptor Research

AR:315nM (Ki)

FxR: 12000 nM (IC50)

GR: 252 nM (Ki)

MR: 37 nM (Ki)

PR: 224 nM (Ki)

PxR: 2.4 nM (EC50

)

PPARα:1100 nM (EC50

)

PPARγ2000 nM (EC50

)

PPARδ: 1.0 nM (EC50

)

VDR: 14700 nM (IC50

)

TRα: 59900 nM (IC50

)

TRβ: 59900 nM (IC50

)

ERα: 21300 nM (95)

AR: 12100 nM (IC50

)

RARα: 6756 nM (IC50

)

RARβ: 3927 nM (IC50

)

RARγ: 8764 nM (IC50

)

RXRα: 2.3 nM (IC50

)

RXRβ:16nM(IC50

)

RXRγ: 10.9 nM (IC50

)

RXRα/PPARγ: 0.4 nM (IC50

)

AR: 8.9 nM (IC50

)

ERα: 1145 nM (IC50

)

ERβ:134 nM(IC50

)

GR: 0.4 nM (IC50

)

PR: 6.4 nM (IC50

)

MR: >1000 nM (IC50

)

TRα: 790 nM(IC50

)

TRβ: >2250 nM (IC50

)

(A)

(C) (D)

(B)

Guggulsterone

GW0742

Figure 3: NR ligands that were evaluated towards multiple nuclear receptors.

GW0742 (Figure 3(D)) was developed as selective agonistfor PPAR𝛿 by GlaxoSmithKline [14]. The evaluation ofGW0742, with respect to NR-mediated inhibition of tran-scription, identified this compound as an antagonist for ARand VDR [15].

Nevertheless, the exhaustive characterization of NR lig-ands is limited by the sheer number of different NRs resultingin a cost- and time-intensive analysis for research labs andthe pharmaceutical industry. Therefore, a prediction of NRselectivity of new ligands using computational approachesmight enable a selection of a smaller pool of NRs to beconsidered for evaluation. In addition, this approach mightalso identify groups of NRs that bind similar ligands, thusintroducing a new relationship between NRs that is differentfrom phylogenetic distance or NR sequence similarity. Inorder to test this hypothesis, we used the library of NRligands and carried out two virtual screens applying thefirst crystal structure of liganded VDR [7]. For each screen,we applied a different pharmacophore model to filter allmolecule conformations. The two different pharmacophoremodels are depicted in Figure 4.

The virtual screen 1 was carried out with a pharma-cophore model that specifies three electron donor/acceptorelements depicted as purple spheres (Figure 4(A)). Thesethree elements represent the spatial configuration of threehydroxyl groups of the most active endogenous VDRligand 1,25-dihydroxy vitamin D3 (1,25(OH)2D3) [16].1,25(OH)2D3 is a metabolic product of vitamin D3 formedfrom 25(OH)D3 by 1𝛼-hydroxylase [17]. The binding affinityof 1,25(OH)2D3 is 0.1–1 nM, whereas 25(OH)D3 binds witha moderate affinity of 1420 nM towards VDR [18]. Thevirtual screen of 14330 compounds using pharmacophoremodel A (Figure 4) identified 64 compounds. 32 of the 64compounds had a significant calculated free energy of VDRbinding of more than−6.0 kJ/mol. Nordihydroguaiaretic acid(NDGA) was the only non-VDR ligand identified with acalculated ΔG of −11.1 kJ/mol (Figure 5).

NDGA is a bioactive compound that inhibits lipoxyge-nases, functions as an antioxidant, and has shown promisinganticancer activities [19]. The compound has also beenreported to weakly interact with the androgen receptor bybinding to a new BF3 binding site [20]. Herein, we confirmedthe activity of NDGA towards VDR using a fluorescencepolarization assay. In the presence of 1,25(OH)2D3, NDGAwas able to inhibit the interaction between VDR and coacti-vator peptide SRC2-3 with IC50 values of 15.8 ± 2.1 𝜇M. Inthe absence of 1,25(OH)2D3, NDGAwas not able to promotethe recruitment of coactivator towards VDR. Because ofthe fact that the interactions between VDR and coactivatorsare essential for VDR-mediated transcription, we identifiedNDGA as a novel VDR antagonist.

Virtual screen 2 was carried out using a less-stringentpharmacophore model depicted in Figure 4(B). The twoacceptor/donor groups represent the two hydroxy functionali-ties of VDR ligand 25(OH)D3. Among the 14330 molecules,397 compounds were identified and 162 compounds exhib-ited a free energy of binding of more than −6.0 kJ/mol(Figure 7).

Among the hit compounds of virtual screen 2, themajorityof molecules were developed as ligands for VDR. Ligandsdeveloped for LxR𝛼/𝛽, TR𝛼/𝛽, and ER𝛼/𝛽 ligands wereamong the most frequent ligands that potentially interact withVDR. We picked one TR𝛼 ligand (3) and one ER𝛼 ligand(H6036) in order to confirm the activity with regard to VDR(Figure 7).

Both compounds (1 and H6036), identified by virtualscreen 2, were able to inhibit the interaction between VDRand SRC2-3 with IC50 values of 44.5 ± 6.1 𝜇M and20.0 ± 3.4 𝜇M, respectively (Figure 6(A)). The originaldocking score for these compounds was −7.9 kJ/mol (3)and −9.1 kJ/mol (H6036), respectively. The thyroid receptorligand triiodothyronine was not scored by virtual screen2 because it did not satisfy the pharmacophore model.However, we observed that triiodothyronine did inhibit the

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Nuclear Receptor Research 5

aPharmacophore models were established using MOE.

(A) (B)

Figure 4: Two different pharmacophore models for VDR ligands.a

0 1 2

120

100

80

60

40

20

0

(B)

% V

DR

-SR

C2

-3 B

ind

ing

log[Nordihydroguaiaretic acid](μM)

Nordihydroguaiaretic acid

IC50

= 15.8 ± 2.1 μM

1,25(OH)2D

3

no 1,25(OH)2D

3

(A)

Figure 5: Nordihydroguaiaretic acid is inhibiting the interaction between VDR and coactivator peptide SRC2-3.

interaction between VDR-SRC2-3, though being at higherconcentrations. In the absence of VDR ligand LG190178 norecruitment of SRC2-3 to VDR was observed in the presenceof any of these ligands (Figure 7(B)).

4. Discussion

We showed that databases such as the “Binding database” canfunction as a starting point for virtual screening. During thecompilation of this focused library we only identified a smallnumber of developed NR ligands that have been evaluatedwith other NRs. The main reason for this lack of investigationis the size of the NR superfamily in addition to the existingagonism and antagonism that would make an exhaustiveevaluation with a panel of NRs very time intensive and costly.An alternative approach to predict NR selectivity conveyed

herein is virtual screening. Using the first published VDRcrystal structure and pharmacophore models representingthe essential features of VDR ligands, we identified VDRligands among a large library of nuclear receptor ligandsusing virtual screening. The essential features of VDR ligand1,25(OH)2D3 are three hydroxyl functions that interact withVDR via hydrogen bonding. In addition, 1,25(OH)2D3 hasa large hydrophobic surface area. Using a pharmacophoremodel based on 1,25(OH)2D3 that defines the spatial orienta-tion of three hydroxyl groups as filter, we identify compoundsthat interact with VDR with 100% accuracy during virtualscreen 1 using a cutoff of −6 kJ/mol for the calculated freeenergy of VDR binding. 31 out of the 32 hit compoundswere VDR ligands such as agonists 2MD [21] or antagonist4 [22]. Both compounds have been shown to bind VDR;however, 2MD promoted the recruitment of coactivators,whereas antagonist 4 inhibited the interaction between VDR

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6 Nuclear Receptor Research

AR,3

ERa/b,42

FxR,4

GR,1

LXRa/b,12

PPARa/g/d,2

TRa/b,11

VDR,87

Figure 6: Number and affiliation of NR ligands identified by virtual screen 2 using the pharmacophore model depicted in Figure 4(B).

0 1 2 3

120

100

80

60

40

20

0

(B)

% V

DR

-SR

C2-3

Bin

din

g

log[compound](μM)0 1 2 3

120

100

80

60

40

20

0

(A)

% V

DR

-SR

C2-3

Bin

din

g

log[compound](μM)

(C) Triiodothyronine

homoserine

H6036

3

Figure 7: Interaction between virtual screen hit compounds (♦H6036, ▪compound 3, ▴triiodothyronine) and VDR. (A) Hit compoundinhibition of the interaction between SRC2-3 and VDR in the presence of VDR agonist LG190178. (B) Association of VDR-LBD andSRC2-3 in the presence of hit compounds. (C) Structure and generation of NR ligands.

and coactivator. Thus, virtual screen 1 identified VDRligands but did not differentiate between VDR agonists andantagonists.

Virtual screen 2 applied a less-stringent pharmacophoremodel based on VDR ligand 25(OH)D3, which is at least1000-fold less potent than 1,25(OH)D3. As expected, weidentified more and different NR ligands that are likely tointeract with VDR. In total we found 162 compounds witha calculated free energy of VDR binding of more than −6.0kJ/mol. 54%, that is, 87 ligands, were developed for VDR.Wehave to point out that 187 compounds of the 414VDR bindersare VDR-coactivator inhibitors developed by Mita et al. [23,24] and by us [25, 26]. These compounds do not bind VDRat the 1,25(OH)2D3 binding site. Furthermore, VDR ligandschange the three-dimensional structure of VDR upon binding

[27]. The application of a pharmacophore model based onthe 1,25(OH)2D3 binding mode will favor molecules that canbind VDR in a similar way and downscore those ligandsthat change the conformation of VDR. Nevertheless, it wasreported that those ligands have a very strong VDR affinity[27]. As a result, we have 196 false negative molecules forvirtual screen 1 and 140 false negatives for virtual screen 2using a cutoff of −6 kJ/mol for the calculated free energy ofVDR binding.

ER𝛼 and ER𝛽 ligands made up 26% of the compoundsidentified by virtual screen 2 followed by TR ligands (7%)and LxR ligands (7%). Thus, there is a relationship betweenVDR, TR, and ER that is beyond the phylogenetic distanceor NR sequence similarity. Two compounds were picked thatare commercially available or in case of 3 easy to synthesize.

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Nuclear Receptor Research 7

Both compounds inhibited the interaction between VDRand coactivator peptide SRC2-3, though being at differentconcentrations. The calculated free energy of VDR bindingcorrelated with the IC50 values observed for the newlyidentified VDR antagonists. NDGA exhibited the best VDRaffinity and the largest free energy of VDR binding followedby H6036 and 3, respectively. Interestingly, triiodothyroninewas not among the hit compounds because it failed to satisfythe pharmacophore used for virtual screen 2. Nevertheless,we confirmed triiodothyronine as a weak VDR antagonisthighlighting the fact again that other pharmacophore modelsexist to identify VDR ligands. An alternative approachto developing a new pharmacophore for a virtual screencould include the application of a VDR crystal structurebound to a VDR ligand with a low calculated free energyof VDR binding for the virtual screen 1 but an excellentreported affinity for VDR. Another approach could includethe optimization of our current pharmacophore model bychanging the volume of the donor/acceptor elements or byadding additional pharmacophore elements.

Overall, the development of NR-specific pharmacophoremodels is important because it can assist in the choice of NRsthat should be evaluated in order to determine NR selectivityof novel NR ligands. Although this approach can drasticallydecrease the cost and time to determine NR selectivity ofnewly synthesized ligands, it is not a full substitute for anexhaustive investigation of a comprehensive panel of NRswith respect to agonism and antagonism. In addition, NR-specific pharmacophore models can be used to identify newNR ligands.We demonstrate the utility of this approach usinga library of NR ligands to identify new VDR antagonists.The application of larger virtual compound libraries suchas the “Zinc Library” might result in the identification ofmore compounds that interact with VDR. Overall, it canbe concluded that virtual screening can support both theidentification of new NR ligands as well as the identificationof NRs that are likely to interact with NR ligands in order toaccelerate the determination of NR selectivity.

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8 Nuclear Receptor Research

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