Discovery of diverse hormone antagonists by high-throughput docking

Matthieu Schapira*†, Bruce M. Raaka‡, Sharmistha Das‡, Li Fan§, Maxim Totrov*, Zhiguo Zhou§, Stephen R. Wilson§, Ruben Abagyan*, and Herbert H. Samuels‡

*Molsoft LLC, 3366 North Torrey Pines Court, Suite 300, La Jolla, CA 92037; ‡Departments of Pharmacology and Medicine, New York University School of Medicine, 550 First Avenue, New York, NY 10016; and §Department of Chemistry, New York University, 100 Washington Square East, 10th Floor, New York, NY 10003

Communicated by David D. Sabatini, New York University School of Medicine, New York, NY, March 31, 2003 (received for review November 18, 2002) Treatment of , a common clinical condition that can androgen (9), or rosiglitazone, a peroxisome proliferator-activated have serious manifestations in the elderly, has remained essentially receptor-␥ agonist (PPAR␥) (10). TR is expressed as different unchanged for >30 years. Directly antagonizing the effect of the isoforms (TR␣1, TR␤1, and TR␤2) differentially expressed in thyroid hormone at the receptor level may be a significant improve- various tissues (4). Gene knockout studies in mice indicate that ment for the treatment of hyperthyroid patients. We built a computer TR␤ plays a role in the development of the auditory system and in model of the (TR) -binding domain in the negative feedback of thyroid stimulating hormone (TSH) by T3 its predicted antagonist-bound conformation and used a virtual in the pituitary (11, 12), whereas TR␣ modulates the effect of screening algorithm to select 100 TR antagonist candidates out of a thyroid hormone on calorigenesis and on the cardiovascular system library of >250,000 compounds. We were able to obtain 75 of the (13). The identification of TR antagonists could play an important compounds selected in silico and studied their ability to act as role in the future treatment of hyperthyroidism. Such molecules antagonists by using cultured cells that express TR. Fourteen of these would act rapidly by directly antagonizing the effect of thyroid compounds were found to antagonize the effect of T3 on TR with hormone at the receptor level, a significant improvement for IC50s ranging from 1.5 to 30 ␮M. A small virtual library of compounds, individuals with hyperthyroidism who require surgery, have cardiac derived from the highest affinity antagonist (1-850) that could be disease, or are at risk for life-threatening thyrotoxic storm. rapidly synthesized, was generated. A second round of virtual screen- The crystal structure of the ligand-binding domain (LBD) of ing identified new compounds with predicted increased antagonist several NRs has been solved in the absence of ligand or in the activity. These second generation compounds were synthesized, and presence of bound agonists or antagonists and has provided a their ability to act as TR antagonists was confirmed by transfection detailed model for the structural mechanism of activation and and receptor binding experiments. The extreme structural diversity of inhibition of members of the NR family (14–19). Although most of the antagonist compounds shows how receptor-based virtual screen- the LBD remains relatively static, regardless of the activation state ing can identify diverse chemistries that comply with the structural of the receptor, the most C-terminal helix (referred to as H12) is rules of TR antagonism. rather dynamic and can adopt a variety of conformations when no ligand is bound to the receptor. Binding of an agonist stabilizes a verproduction of thyroid hormone (hyperthyroidism or thy- conformation of the receptor where H12 folds like a lid onto the Orotoxicosis) is an extremely common clinical entity caused by agonist, contributing to the formation of a hydrophobic cavity at the a number of different pathological conditions of the thyroid gland. surface of the receptor, involved in the binding of coactivator Approximately 0.5% of women will experience some clinical man- proteins. Antagonists, on the other hand, destabilize this coactiva- ifestation of hyperthyroidism in their lifetime (3–5 times more tor-recruitment state by preventing H12 from folding on the ␣ frequent than men), with potentially life-threatening effects on the ligand-binding pocket. The crystal structure of ER bound to cardiovascular system (e.g., cardiac arrhythmias, heart failure, the partial antagonist raloxifene shows that H12 relocates onto the angina, and myocardial infarction), particularly in the elderly (1–3). coactivator binding site (14). Alternatively, the pure antagonist ICI The treatment of hyperthyroidism has essentially remained un- 164,384 presents an arm that extends out of the ligand-binding changed for the past 30 years and includes the use of radioactive pocket and onto the coactivator binding site (18). The crystal ␣͞ ͞ [131I], surgery, or the use of antithyroid drugs, such as structure of a PPAR antagonist corepressor peptide complex propylthiouracil, that inhibit thyroid hormone synthesis by blocking also recently showed that binding of corepressor proteins can the iodination of (1–3). Each approach has its own further destabilize the active conformation of the receptor (19). In intrinsic limitations and͞or side effects. Propylthiouracil and re- most cases, two important properties of antagonist molecules apply: lated drugs, which block thyroid hormone synthesis, act slowly and (i) they bind within the ligand-binding pocket, making specific can take up to 6–8 weeks to fully deplete the thyroid gland and interactions with pocket-lining residues in a fashion similar to that for agonists; (ii) they present an extension that protrudes [slightly intrathyroidal stores of iodinated thyroglobulin, during which time ␣ hyperthyroidism can have severe consequences in certain individ- in the case of the PPAR antagonist GW6471 (19), more exten- uals. Radiochemical destruction of thyroid tissues by 131I may sively in the case of ICI 164,384 (18)] out of the pocket and antagonizes the active conformation of H12. The recent crystal require 4–6 months to be fully effective, whereas surgical thyroid- ␤ ectomy must be preceded with antithyroid drugs to prevent life- structure of the ER -selective antagonist (R,R)-5,11-cis-diethyl- 5,6,11,12-tetrahydrochrysene-2,8-diol bound to the inactive form of threatening complications such as . ␤ The activity of the , L-thyroxin (T4) and the ER -LBD depicts an alternate mode of antagonism, where the L- (T3), is mediated by thyroid hormone nuclear ligand induces nonproductive conformations of binding pocket receptors (TRs) (for a recent review see ref. 4). The TRs are members of the nuclear hormone receptor (NR) superfamily that Abbreviations: ER, estrogen receptor; ICM, internal coordinate mechanics; LBD, ligand- also includes receptors for steroid hormones, retinoids, and 1,25- binding domain; NR, nuclear hormone receptor; PPAR␥, peroxisome proliferator-activated dihydroxyvitamin D3 (5–7). These receptors are transcription fac- receptor-␥ agonist; RAR, retinoic acid receptor; T3, L-triiodothyronine; TR, thyroid hormone tors that can regulate expression of specific genes in various tissues receptor; VLS, virtual library screening. and are targets for widely used drugs, such as tamoxifen, an See commentary on page 6902. estrogen receptor (ER) partial antagonist (8), flutamide, an anti- †To whom correspondence should be addressed. E-mail: [email protected].

7354–7359 ͉ PNAS ͉ June 10, 2003 ͉ vol. 100 ͉ no. 12 www.pnas.org͞cgi͞doi͞10.1073͞pnas.1131854100 Downloaded by guest on September 25, 2021 residues that destabilize the active state of the H12 helix (20). It is rapidly refined with both ligand and receptor side-chains flexible, unclear whether this interesting ‘‘passive-antagonism’’ mechanism according to the ICM local energy minimization method that uses is an isolated case. On the other hand, the mechanism whereby a internal coordinates and analytical derivatives (28, 29), and the SEE COMMENTARY protruding extension directly induces relocation of helix H12 was refined structures presenting unacceptable receptor͞ligand van der experimentally observed in a variety of complexes (14, 18, 19, Waals repulsions were filtered out. Each of the remaining 300 21–23). top-scoring complexes was visually inspected: parameters taken Based on such observations, we built a low-energy model of the into account were shape complementarity, hydrogen bond network retinoic acid receptor-␣ (RAR␣) LBD where H12 adopts a con- and flexibility of the ligand. Based on this final subjective selection formation similar to raloxifene-bound ER␣ and showed that such step, 100 compounds were retained to be characterized in vitro.It a model can be used for structure-based discovery of novel RAR is difficult to evaluate the relevance and enrichment generated by antagonists (24). This rationale was recently confirmed by another the different automatic or visual filters added after the initial group which designed a TR antagonist by adding a steric moiety to high-throughput docking; to better judge the efficiency of the first T3 that would destabilize the transcriptionally active conformation screening step, the score distribution of all compounds screened as of H12 (25). In this report, we demonstrate that, by deriving well as that of the active compounds is provided (Fig. 6, which is molecules from the structure of the receptor, rather than the published as supporting information on the PNAS web site, www. structure of known agonists, a large array of TR antagonists can be pnas.org): of 14 active TR antagonists identified, 9 ranked in the top identified, that present striking structural diversity. Such an ap- 600 of Ϸ250,000 compounds and 3 ranked in the top 300 [the source proach could accelerate the discovery of new chemical entities for library included Ϸ250,000 ligands but only 190,000 passed the the treatment of hyperthyroidism. Lipinski filters (35) and were assigned a score].

Materials and Methods Effect of Antagonists on T3-Stimulation of Gene Expression and Model Building of a TR Antagonist Structure. The crystal structure of T3-Association with NRs in Vivo and in Vitro. For functional chlor- raloxifene-bound ER␣ (14) was used as a template to derive from amphenicol acetyltransferase (CAT) assays, HeLa cells were inoc- the structure of agonist-bound TR␤-LBD (26) a predicted model of ulated at 50,000 cells per well in 24-well plates in DMEM containing the receptor bound to an antagonist. The conformation of the 10% calf serum. The cells were transfected5hlaterbycalcium N-terminal domain of the TR␤-LBD was left unchanged from the phosphate precipitation with 450 ng of the T3-responsive ⌬MTV- agonist-bound form, up to residue Leu-440, whereas the C-terminal IR-CAT reporter and 250 ng of a vector expressing TR␣.Atthe domain (residues His-441 to Asp-461) was remodeled in a two-step time of transfection, the cells also received 6 nM T3 and the process, as described for RAR (24). This model is based on the different concentrations of the antagonist candidates. Cells were hypothesis (derived from sequence alignment with the ER and the harvested 40 h after transfection and assayed for protein content crystal structure of the ER͞raloxifene complex) that the FXXVF and CAT activity as described (24). Results are expressed as the pattern, at positions 455, 458, and 459 of helix H12, mimics, in the extent of inhibition of the T3-stimulation of CAT activity observed antagonist conformation, the LXXLL motif of the GRIP-1 coac- in the presence of the antagonist candidates. Each data point tivator observed in the crystal structure of agonist-bound TR␤ (26). reflects the average of triplicate samples that showed Ͻ10% The isolated, flexible H12 helix was docked to a hydrophobic cavity variation. at the surface of the receptor according to the internal coordinate Inhibition of binding of [125I]T3 to TRs in intact GH4 cells by the mechanics (ICM) method (27, 37). The docked structure of helix antagonist candidate 1-850 was carried out as described (32) with H12 (residues 455–461) was then fixed, and the conformation of the slight modifications. GH4 rat pituitary cells, which contain endog- C-terminal loop joining His-441 to Phe-455 was optimized by an enous TRs (TR␣1, TR␤1, and TR␤2), were grown in monolayer extensive energy minimization Monte Carlo simulation in the culture in DMEM containing 10% calf serum. Cells were dispersed internal coordinate space with ICM (28). by incubation in a buffered solution of EDTA and incubated at 37°C for 60 min in serum-free DMEM to lower endogenous levels of High-Throughput Docking. The ICM virtual library screening (VLS) thyroid hormones. Aliquots containing Ϸ1.5 million cells were module was used (Molsoft). A series of five grid potential repre- centrifuged at 1,000 ϫ g for 10 min and then suspended in 1 ml of sentations of the receptor were automatically generated and su- serum-free medium containing 0.1 nM [125I] T3 and the indicated perimposed that accounted for the hydrophobicity, carbon-based concentrations of unlabeled T3 or the antagonist candidate, 1-850. and hydrogen-based van der Waals boundaries, hydrogen-bonding After incubation at 37°C for 60 min, the cells were chilled in ice and profile, and electrostatic potential of the predefined ligand binding then centrifuged at 4°C at 1,000 ϫ g for 10 min. The samples were site. Each of the 250,000 flexible compounds of the Available washed twice by resuspension and vortexing with 1 ml of 50 mM ⅐ Chemicals Directory database (MDL Information Systems, San Tris HCl, pH 7.85, containing 1 mM MgCl2 and 0.5% Triton X-100 Leandro, CA) that passed the Lipinski filters (35) was docked to the and centrifugation at 1,000 ϫ g for 10 min to isolate the nuclear receptor grids by the ICM method (29) and assigned a score that fraction of the cells. The amount of [125I]T3 retained in the nuclei reflects the quality of the complex and includes grid energy, was determined by using a Packard spectrometer. The results are continuum electrostatic, and entropy terms (refs. 30 and 31 for plotted as percent of [125I]T3 retained in washed nuclei from cells review). Docking took an average of 1 min per processor and per incubated with 0.1 nM [125I]T3 in the presence of unlabeled T3 or ligand. The whole process was conducted four times in parallel, and the 1-850 antagonist compared with cells incubated with 0.1 nM the lowest score assigned to each ligand was retained. Compounds [125I]T3 alone. Each point represents the average of duplicates, scoring below (i.e., better than) the ICM VLS threshold used for which varied by Ͻ5%. RAR (24) and therefore most likely to bind the TR ligand binding PHARMACOLOGY pocket were then tested in silico for their predicted antagonist Effect of Antagonist 1-850 and Derivatives on the T3-Mediated Binding activity. Although all NR antagonists do not necessarily present a of TR to the Coactivator NRC in Vitro. Full-length TR␣ was synthe- bulky moiety protruding out of the binding pocket (20), all known sized in the presence of L-[35S]methionine by using TNT reticu- ligands that do present such moiety are antagonists (14, 18, 19, locyte lysates (Promega). Approximately 2.5–5 ϫ 104 cpm of 21–23). Based on this observation, only the top 1,000 ligands that 35S-labeled TR␣ (20 fmol) in 2 ␮l of lysate was incubated with had a bound conformation incompatible with the active state of the 500 ng of GST fused to the receptor interaction region of the receptor were retained (docked compounds that were further than coactivator NRC (NRC15) immobilized on glutathione-agarose 3 Å away from Phe-455 or Phe-459 of the active form of helix H12 beads (33). The samples were incubated at room temperature for were discarded). The structure of this top 1,000 selection was 15 min in 500 ␮l of binding buffer [20 mM Hepes (pH ϭ 7.8)͞1

Schapira et al. PNAS ͉ June 10, 2003 ͉ vol. 100 ͉ no. 12 ͉ 7355 Downloaded by guest on September 25, 2021 ͞ ͞ ͞ ͞ mM MgCl2 100 mM KCl 0.05% Triton X-100 1mMDTT 10% Table 1. Name, structure, and relative activity of the 14 TR ͞ ␮ ͞ ␮ (vol/vol) glycerol 100 g/ml ovalbumin 0.1 M ZnCl2] with the antagonists identified after the first round of virtual screening indicated concentrations of 1-850 and the 1-850 derivatives D1 Concentration, Inhibition, and D4. The samples were then chilled on ice and incubated with Name Structure ␮M % 1 nM T3 for an additional 60 min at 4°C. Control samples contained no T3 or antagonists or received only T3. The beads 1-850 20 90 were collected by centrifugation (Ϸ500 ϫ g)at4°C for 5 min and washed three times with 1 ml of binding buffer. The bound [35S]TR␣ was electrophoresed in an SDS͞10% polyacrylamide gel followed by analysis and quantitation of the amount of 2-1281 20 80 [35S]TR␣ bound by using a Molecular Dynamics PhosphorIm- ager and IMAGEQUANT software. The percent inhibition of 35 ␣ T3-mediated binding of [ S]TR to GST-NRC15 by 1-850, D1, 1-2408 20 66 and D4 was determined after subtracting the amount of [35S]TR␣ bound to GST-NRC15 in the absence of T3.

Generation of a Virtual Focused Library. A virtual library of deriva- 1-3570 20 62 tives of the antagonist 1-850 (the best hit derived from first- generation VLS) was generated, based on the chemical synthesis scheme described below, so that all molecules generated in silico could be easily and rapidly synthesized. All phenylisocyanates commercially available from Sigma–Aldrich were extracted from 2-1915 20 55 virtual structure libraries with the ICM ‘‘find molecule’’ command (27) and attached to the nonvariable moiety of 1-850. Each mole- cule was then assigned ECEPP3 potentials and mmff partial charges, energy-minimized, and stored in a focused library of 101 compounds. All chemo-informatics procedures were carried out 2-1755 20 53 with ICM (27).

Preparation of 1-850 Active Analogs D1–D57. Selected compounds from the series of 1-850 analogs D1–D101 were prepared by 1-3501 20 53 coupling of compound 4 (see Supporting Text, which is published as supporting information on the PNAS web site, for more details) with commercially available phenylisocyanates (Fig. 3). The general procedure involved adding 0.5 mmol of phenylisocyanate to a 2-1276 20 50 solution of 0.13 g of compound 4 (0.5 mmol) in 1 ml of dry CH2Cl2, stirring at room temperature for 2 h, and then separation of the final product by filtration. The purity of the all library compounds was determined by LC-MS. The most active compounds D1–D4 were 2-1578 20 49 characterized more fully by 1H NMR and MS. Results Modeling of the Antagonist-Bound Conformation of TR. A low-energy model of the antagonist structure of the TR␤-LBD was built by 1-4323 20 42 homology to agonist-bound TR␤-LBD (26) and raloxifene-bound ER␣ (14). Following a strategy devised with RAR (14), we docked ␤ the C-terminal helix H12 of the TR LBD to the coactivator 1-3992 20 36 recruitment site as described (34), and remodeled the 20 C-terminal residues of the receptor by an extensive global energy minimization (27, 38).

Virtual Screening. A virtual database of 250,000 commercially available compounds was rapidly screened in silico. All continuously flexible ligands were docked to a grid representation of the receptor 2-274 20 36 and assigned a score reflecting the quality of the complex, accord- ing to the ICM method (Molsoft). Briefly, a series of grid potentials representing the shape, hydrophobicity, hydrogen bonding profile, and electrostatic potential of the receptor was generated. Each ligand was then docked to the grid representation of the receptor 2-284 20 34 by a Monte Carlo simulation in the internal coordinates space, and the complex was optimized with flexible receptor side chains (see Materials and Methods). Putative ligands that did not extend out of the binding pocket in the docked conformation were automatically filtered out. After visual inspection of the 300 best scoring com- 2-1060 4* 33 pounds, 100 were selected as potential TR antagonists, 75 of which were still commercially available (chemicals listed in the Available Chemicals Directory are often not resynthesized once they run out of stock). *Compound 2-1060 was toxic at 20 ␮M.

7356 ͉ www.pnas.org͞cgi͞doi͞10.1073͞pnas.1131854100 Schapira et al. Downloaded by guest on September 25, 2021 SEE COMMENTARY

Fig. 1. Inhibition of [125I]T3 binding to TRs by 1-850 in intact cells. The GH4C1 pituitary cell line, which contains endogenous TRs (TR␣,TR␤1, and TR␤2), was incubated with 0.1 nM [125I]T3 alone and with the indicated concentrations of unlabeled T3 and 1-850 as described in Materials and Methods. After incubation for 60 min at 37°C, the cells were chilled and washed, and the nuclei were isolated as described in Materials and Methods. The results indicate the inhibition of binding of [125I]T3 by T3 and 1-850. Fig. 2. Predicted conformation of 1-850 (gold) bound to the TR␤ ligand-binding pocket. (Upper) A hydrogen bond between His-435 and a carbonyl oxygen of Discovery of 14 Novel TR Antagonists. The ability of the 75 com- 1-850 and possibly between Arg-282 and a nitro oxygen of 1-850 constitute the mercially available compounds to inhibit the functional activity of only polar interactions. All other contacts are hydrophobic (not shown for clarity). TR in mammalian cells was assayed. The compounds were dis- (Lower)1-850 superimposes with the crystal structure of T3 (green), bound to active TR and clashes with the active conformation of helix H12 (cyan). Color code solved in DMSO, and the effect of various concentrations of the ͞ ͞ ␣ is red for oxygen, blue for nitrogen, and magenta for fluoride in 1-850 T3, compounds to inhibit T3-stimulation of a reporter gene by TR respectively. expressed in HeLa cells was studied. Fourteen of the 75 compounds showed antagonist activity; their structure and order of potency are shown in Table 1. Compound 1-850 showed the greatest antagonist were constructed in silico with ICM. The resulting chemical library activity. To verify that 1-850 inhibited the action of T3 by compe- of 101 compounds was docked to the receptor as described above, tition at the TR level, the ability of 1-850 to inhibit the binding of and each 1-850 derivative was assigned a score reflecting its [125I]T3 to endogenous TRs in GH4C1 cells was compared with predicted fit with the receptor. To address the relevance of this nonradioactive T3 (Fig. 1). Based on this study, 1-850 has an virtual automatic parallel synthesis and docking strategy, we syn- Ϸ 1,000-fold lower affinity for the receptor in intact cells compared thesized 8 of the 57 top-ranking 1-850 analogs and compared ␣ with T3. Although the results of Table 1 were obtained with TR , calculated scores with observed activities. A dose–response inhi- ␤ similar results for these compounds were also found by using TR . bition of T3-stimulation comparing 1-850 with the best two antag- All of the compounds that exhibited antagonist activity in the onist derivatives (D4 and D1) is shown in Fig. 4, and the results of presence of T3 showed no partial agonist activity in the absence of the 8 compounds are shown in Table 2. None of the 1-850 T3. In addition, these compounds had no effect on the activity of ␣ derivatives exhibited partial agonist activity in the absence of T3. RAR (data not shown), suggesting specificity for TR. The best two inhibitors (D4 and D1), were among the top four scoring compounds whereas the two less active molecules were the Structure-Based Optimization of Compound 1-850. The docking of lowest scoring ones (D37 and D57). One derivative (D4) reached 1-850, the most active antagonist identified by our first round of IC in the nanomolar range (0.75 ␮M), and all compounds virtual screening, suggests that the antagonist makes mostly hydro- 50 inhibited TR from 10% to 84% at 5 ␮M (Table 2). According to our phobic interactions with residues lining the ligand-binding pocket. docking simulation, the methyl and isopropyl groups of D4’s A carbonyl oxygen of 1-850 also forms a hydrogen bond with His-435 in the docked conformation, whereas the nitro group is hydrophobic end would make more extensive hydrophobic inter- relatively close to Arg-282 (4 Å between the nitro oxygen and the actions with the receptor than the trifluoromethyl of 1-850 (Fig. 7, closest arginine nitrogen), deep inside the receptor pocket (Fig. 2 Upper). As expected, the antagonist superimposes well with the crystal structure of bound T3 and presents an additional extension PHARMACOLOGY that would clash with the active conformation of H12 (Fig. 2 Lower). Based on this model, we synthesized derivatives of 1-850 that might display higher affinity for the receptor. 1-850 was divided into one core unit that was synthesized separately and one variable extremity, where polysubstituted phenylisocyanates could be used as building blocks to easily derivatize the hydrophobic, trifluoro- Fig. 3. Chemical synthesis of 1-850 derivatives was conducted by preparing a methylated moiety of 1-850 (Fig. 3 and Supporting Text). A virtual nonvariable core structure and rapidly linking commercially available polysub- library of all such building blocks available from the Sigma–Aldrich stituted phenylisocyanate building blocks in a simple step of parallel synthesis catalog was generated, and all corresponding derivatives of 1-850 (see Materials and Methods for details).

Schapira et al. PNAS ͉ June 10, 2003 ͉ vol. 100 ͉ no. 12 ͉ 7357 Downloaded by guest on September 25, 2021 Fig. 5. Inhibition of T3-mediated coactivator recruitment to TR by D1, D4, and 1-850 in vitro. Approximately 2.5–5 ϫ 104 cpm of 35S-labeled TR␣ (20 fmol) in 2 ␮l of lysate was incubated with 500 ng of GST fused to the receptor-interaction region of the coactivator NRC (NRC15) immobilized on glutathione-agarose beads. The samples were also incubated for 15 min at room temperature with 2 ␮M D1 or D4 or 5 ␮M 1-850 in binding buffer as indicated in Materials and Methods. The samples were then chilled on ice and incubated with 1 nM T3 for an additional 60 min at 4°C. Control samples contained no T3 or antagonists or received only T3. The beads were washed and the bound [35S]TR␣ was electro- phoresed in a an SDS͞10% polyacrylamide gel followed by analysis and quanti- 35 ␣ Fig. 4. Comparison of the antagonist activity of 1-850 and two compounds (D1 tation of the amount of [ S]TR bound by using a Molecular Dynamics Phos- and D4) identified through a VLS of derivatives of 1-850. phorImager and IMAGEQUANT software. The percent inhibition of T3-mediated binding of [35S]TR␣ to GST-NRC15 by 1-850, D1, and D4 was determined after subtracting the amount of [35S]TR␣ bound to GST-NRC15 in the absence of T3. which is published as supporting information on the PNAS web site.) To document that D4 and D1 acted through inhibition of T3 and the extent of inhibition generally parallels the relative ability of binding to receptor, we compared their activity to 1-850 using a these compounds to inhibit T3-mediated stimulation of gene ex- T3-dependent in vitro coactivator binding assay (Fig. 5). In this pression in cells (D4 Ͼ D1 Ͼ 1-850; Fig. 4). study, we incubated rabbit reticulocyte labeled [35S]TR␣ with GST-NRC15 immobilized on glutathione-agarose beads. NRC15 is Discussion a region of the nuclear receptor coactivator NRC that interacts with In this study, we used the crystal structure of agonist-bound TR␤ agonist-bound TR through the NRC LXXLL-1 motif (33). GST- and raloxifene-bound ER␣ to construct a computer model of the 35 ␣ NRC15 was incubated with [ S]TR with the indicated concen- predicted antagonist form of TR␤ and used this model as a trations of D4, D1, and 1-850 followed by incubation with 1 nM T3 template to discover in silico small molecule inhibitors of TR. Using (a concentration that leads to a maximal effect in the absence of the most active initial hit, we generated a small virtual library that antagonist). After incubation and washing as indicated in Materials can be easily and rapidly synthesized with commercially available and Methods, the samples were electrophoresed in an SDS͞10%- building blocks. High-throughput docking of this library with TR polyacryalimide gel, followed by imaging and quantitation by using identified a derivative with increased activity. a PhosphorImager. The results shown in Fig. 5 indicate that the First, this work confirms a conceptually important observation antagonists block the T3-mediated interaction of TR␣ with NRC, that we made with RAR (24), documenting that it is possible to

Table 2. Comparison of the biological activity of the 1-850 derivatives actually synthesized with the predicted ranking derived from the calculated score of the receptor͞ligand complex

Name Score Rank (pred.) Structure Concentration, ␮M Inhibition, %

1-850 Ϫ32.86 — R2 ϭ –CF3 1.5 50 580

D1 Ϫ35.98 1 R1 ϭ –CH(CH3)2 2.5 50 576

D3 Ϫ34.39 3 R1 ϭ –CH2–CH3 528 D4 Ϫ33.85 4 R1 ϭ –CH(CH3)2 0.75 50 R4 ϭ –CH3 584 D5 Ϫ33.80 5 R2 ϭ –CH3 521 R4 ϭ –OCH3 D12 Ϫ31.82 12 R2 ϭ F5 67 R3 ϭ F

D19 Ϫ30.87 19 R1 ϭ –CH3 520 R3 ϭ –CH3 R4 ϭ –CH3 D37 Ϫ29.09 37 R3 ϭ –OCH3 510 D57 Ϫ27.94 57 R3 ϭ –CF3 510

Of the 101 analogs of 1-850 docked to the receptor, 8 were synthesized and tested in vitro. The calculated score, corresponding rank (of 101), structure, and activity for each compound are listed.

7358 ͉ www.pnas.org͞cgi͞doi͞10.1073͞pnas.1131854100 Schapira et al. Downloaded by guest on September 25, 2021 rationally design NR antagonists by building a computer model of optimization process. We generated a virtual library focused on one the predicted antagonist-bound form of the receptor. This result of the initial hits (compound 1-850) by branching 101 commercially SEE COMMENTARY reinforces the hypothesis that the structural mechanism for NR available building blocks to a central core, according to a single step inhibition initially depicted for ER (14) can be generalized to other of parallel synthesis. We showed that rapid docking of this virtual members of the family, as was shown for RAR (23) or PPAR (19). library efficiently ranked the derivatives according to their activity, Although this strategy appears successful at rapidly identifying TR with the best two antagonists tested in vitro corresponding to the antagonists, it is likely that it also misses active molecules for the fourth and first best scoring analogs of 101 compounds. Such lead following reasons. (i) Our implementation of receptor modeling optimization strategy can dramatically reduce the number of com- and selection of antagonist candidates was directed toward the pounds to synthesize and test, thereby allowing better character- identification of compounds that do fit in the TR ligand binding ization of more relevant molecules. pocket but present a bulky moiety that would clash with the active Although we built an antagonist-bound conformation of TR conformation of helix H12. However, smaller compounds may where the helix H12 occupies the coactivator recruitment site, induce nonproductive conformations of binding pocket residues based on the crystal structure of the ER͞raloxifene complex (14), that could destabilize the active state of the H12 helix, as was none of the docked compounds contact receptor residues C- recently shown for the ER (20). Such active antagonists would be terminal to helix H11 (even though they all would clash with the missed by our selection strategy. (ii) The VLS algorithm is mainly active conformation of H12). Carrying out the VLS with H12 in an designed to filter out nonbinders and enrich significantly in active alternative, extended conformation, as observed in apo-RXR (36), molecules smaller focused libraries. However, it also misses true positives. For instance, the only TR antagonist known before this or with a representation of the receptor truncated at the end of H11 may also have selected the active hits identified in this work. The work, recently described by Baxter et al. (25), was assigned a VLS ␤ score that did not pass our selection threshold. Possible reasons are recent crystal structure of ER -LBD bound to ICI 164,384 showed that the receptor adopts an alternative conformation when bound that, unlike partial ER antagonists such as tamoxifen or raloxifene, to this ligand, or that the interactions with this moderate binder are this pure antagonist presents an extension long enough to reach the not strong enough to be detected. coactivator recruitment site of the receptor and prevent interaction A second observation is the extraordinary structural diversity of between helix H12 and the core of the receptor (18). If a similar the 14 TR antagonists discovered after our first round of virtual mechanism applied to other NRs, such as TR or androgen receptor, screening (Table 1). In a recent study, Baxter et al. (25) showed that performing a high-throughput docking with a receptor truncated at adding a hydrophobic moiety to 3,5-dibromo-4-(3Ј-isopropyl-4Ј- the end of helix H11 might result in the identification of pure hydroxyphenoxy)benzoic acid, a known TR agonist, resulted in TR antagonists, with potentially interesting therapeutic properties. antagonist activity. Here, we demonstrate that a diverse array of compounds, representing extremely heterogeneous chemistries, Conclusion can comply with the structural rules that govern TR inhibition. In this work, we showed that high-throughput docking can be Underlying this surprising observation is the strategy used to used to rapidly identify lead TR antagonists that differ from discover TR antagonists, where small molecule modulators for a known ligands and to prioritize subsequent lead optimization. specific target are derived from the structure of the receptor rather The extreme structural diversity of the antagonist molecules than from existing ligands. Such an approach can open up entire discovered in this work illustrates the power of receptor-based domains of the chemistry space that would be overlooked by virtual screening and demonstrates that diverse chemistry can ligand-based pharmacophore approaches. This work demonstrates comply with strict structural rules. Further optimization of TR that high-throughput docking is a relevant approach to screen very antagonists could open the way for improved modalities for the large and diverse chemical libraries that best represent the infinite treatment of hyperthyroidism. diversity of potential lead molecules. Additionally, this powerful strategy can be applied to orphan receptors, for which no ligand is This work was supported by National Institutes of Health Grant known. DK16636 (to H.H.S.) and Small Business Innovation Research͞Small Our work also suggests that receptor-based virtual screening Business Technology Transfer Grant DK59041 (to Molsoft) for collab- coupled to parallel synthesis can significantly accelerate the lead orative research with New York University.

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