Computer-Assisted Discovery of Retinoid X Receptor Modulating

Jun 14, 2018 - Among them, valerenic acid was found to be selective for RXRβ, rendering it a unique pharmacological tool compound. The NPs then serve...
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Brief Article Cite This: J. Med. Chem. 2018, 61, 5442−5447

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Computer-Assisted Discovery of Retinoid X Receptor Modulating Natural Products and Isofunctional Mimetics Daniel Merk,† Francesca Grisoni,†,‡ Lukas Friedrich,† Elena Gelzinyte,† and Gisbert Schneider*,† †

Department of Chemistry and Applied Biosciences, Swiss Federal Institute of Technology (ETH), Vladimir-Prelog-Weg 4, CH-8093 Zurich, Switzerland ‡ Department of Earth and Environmental Sciences, University of Milano-Bicocca, Piazza della Scienza, 1, IT-20126 Milan, Italy

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S Supporting Information *

ABSTRACT: Natural products (NPs) are progressively recognized as invaluable source of pharmacological tools and lead structures. To enable NP-inspired retinoid X receptor (RXR) modulator design, three novel RXR-targeting NPs were computationally identified. Among them, valerenic acid was found to be selective for RXRβ, rendering it a unique pharmacological tool compound. The NPs then served as templates for automated, ligand-based de novo design of innovative, easily accessible mimetics that inherited the biological activities of their natural templates.

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INTRODUCTION Natural products (NPs) are a prime source for innovative medicines, and they are currently experiencing a renaissance in drug discovery.1 Although their synthetic accessibility is often difficult, bioactive NPs may be considered advantageous to purely synthetic compounds in several aspects. Importantly, their molecular frameworks tend to provide a higher degree of threedimensionality and are less aromatic than synthetic drugs, suggesting greater target selectivity and overall favorable physicochemical properties.2 Therefore, pharmacologically active NPs represent well-motivated starting points for drug discovery.3,4 Meanwhile, template-based de novo design supports medicinal chemistry by creating small molecules that inherit the properties of the parent compounds, including their bioactivity and selectivity profiles.3 This concept should be ideally suited for NP-inspired drug discovery. Here, the development of NP-inspired mimetics by fully automated computational de novo design is presented. In a two-step process, new bioactive NPs that modulate retinoid X receptors (RXRs) are identified, and these NPs are employed as design templates for generating isofunctional synthetically accessible mimetics (Figure 1). RXRs are key components in the regulation of metabolic homeostasis and inflammation and, as unique members of the nuclear receptor superfamily, act as universal heterodimer partners of numerous nuclear receptors.5,6 The selective targeting of RXR subtypes by small molecules potentially offers new therapeutic avenues, such as RXRγ activation for combatting multiple sclerosis.7 However, the three receptor subtypes, RXRα, RXRβ and RXRγ, possess nearly identical ligand binding sites, © 2018 American Chemical Society

Figure 1. The Dictionary of Natural Products (DNP) was computationally screened for potential RXR modulators (without discriminating RXR subtypes). On the basis of pharmacophore and shape representations (i.e., molecular descriptors), natural products were ranked according to their predicted RXR modulatory potential using similarity-based virtual screening. Dehydroabietic acid, isopimaric acid, and valerenic acid were confirmed to be active in vitro and served as templates for the computational de novo design of RXR agonists.

which has prevented the development of subtype-selective synthetic modulators.8 Moreover, the existing synthetic RXR Received: March 29, 2018 Published: June 14, 2018 5442

DOI: 10.1021/acs.jmedchem.8b00494 J. Med. Chem. 2018, 61, 5442−5447

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targeting agents, including the approved drug bexarotene, are planar and lipophilic, resulting in poor aqueous solubility and generally poor drug-like behavior.9,10

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RESULTS AND DISCUSSION The NPs honokiol,11 drupanin,12 and bigelovin13 have been known to activate RXRs, with the last possessing significant cytotoxicity. To expand the scope of NP-inspired RXR modulator development and to discover potent NP mimetics with high RXR transactivation efficacy, additional RXRmodulating NPs were required. To this end, we virtually screened the Dictionary of Natural Products (DNP)14 for potential RXR modulators in a three-pronged computational approach: (i) The probability of RXR agonism of all DNP entries was predicted with the software SPiDER,15 considering their pharmacophoric features and molecular properties. Of note, RXR subtypes were not discriminated in this ligand-based computational approach because of insufficient data on subtypeselective RXR ligands. The SPiDER software tool infers potential molecular targets of the query compounds from known drugs and their targets by a self-organizing map consensus.16,17 Furthermore, all DNP entries were virtually screened for similarity to known RXR ligands, using (ii) the Chemically Advanced Template Search (CATS)18 descriptors that are based on pharmacophore feature distributions and (iii) a shape- and partial-charge-based molecular representation. Charged functional groups seem particularly important for the RXR modulator screening because the nuclear receptor is endogenously activated by fatty acids.5,19−21 After merging the lists of results from these three independent computational analyses, we focused on the NPs ranked among the top 100 by at least two methods. From this consolidated list (Supporting Table 1) of computationally preferred NPs, the antibiotic PF1052, isopimaric acid, dehydroabietic acid, valerenic acid, sclareol, and conocarpan were commercially available. Preliminary in vitro characterization of these NPs in specific Gal4 hybrid reporter gene assays22 for RXRα modulation indicated agonistic activity of isopimaric acid, dehydroabietic acid, and valerenic acid at a concentration of 30 μM (Supporting Figure 1). Control experiments in the absence of a chimeric receptor displayed no transactivation, thereby confirming RXR-mediated activity (Supporting Figure 2). Full dose−response analysis revealed micromolar potency of the NPs on all three RXR subtypes (Figure 2A). Isopimaric acid and dehydroabietic acid yielded intermediate micromolar EC50 values combined with moderate transactivation efficacy with up to 12-fold activation but no receptor subtype preference (Table 1). Valerenic acid, in contrast, displayed remarkable selectivity for RXRβ, in terms of EC50 (RXRα, 27 μM; RXRβ, 5 μM; RXRγ, 43 μM) and especially transactivation efficacy (RXRα, 9-fold; RXRβ, 69-fold; RXRγ, 4fold). Nuclear receptor modulators often possess considerable crossreactivity. Therefore, the selectivity of the newly identified RXR agonistic NPs was profiled (Figure 2B, Supporting Figure 3). Valerenic acid was found to be selective for RXRβ without activating RARs, PPARs, LXRs, FXR, CAR, VDR, or PXR at 30 μM. Dehydroabietic acid showed agonistic potency on PPARγ, and isopimaric acid activated several other nuclear receptors. Dehydroabietic acid and especially isopimaric acid displayed cytotoxic effects, whereas valerenic acid was significantly (t test: p < 0.001) better tolerated, up to a concentration of 100 μM (Supporting Figure 4).

Figure 2. Computational screening revealed three novel RXRmodulating natural products. Dose−response curves of valerenic acid, dehydroabietic acid, and isopimaric acid on the three RXR subtypes in Gal4-hybrid reporter gene assays conducted with HEK293T cells (A) (mean transactivation ± SEM, n ≥ 4). Nuclear receptor selectivity of valerenic acid in Gal4-hybrid reporter gene assays were conducted with HEK293T cells (B). Effects of valerenic acid, dehydroabietic acid, isopimaric acid, and mimetic 3 on the mRNA levels of the RXRregulated genes ABCA1 (C) and ApoE (D) in HepG2 cells (mean fold induction vs 0.1% DMSO ± SEM, n = 3): (∗) p < 0.05, (∗∗) p < 0.01, (∗∗∗) p < 0.001.

Then, the modulatory effects of isopimaric acid, dehydroabietic acid, and valerenic acid on RXR-regulated gene expression in HepG2 cells were studied to further validate their activity under more physiological conditions (Figure 2C,D). All three NPs induced ABCA1 and ApoE expression with similar efficacy to the synthetic reference RXR agonist bexarotene except for lower ABCA1 induction by dehydroabietic acid. This result confirms the suitability of the ligand-based similarity methods 5443

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Table 1. RXR Agonistic Activity of Natural Products and Their Mimetics 1a−8 in Vitro in Gal4-Hybrid Reporter Gene Assays Conducted with HEK293T Cellsa EC50 [μM] (fold activation) compd antibiotic PF1052 isopimaric acid dehydroabietic acid valerenic acid sclareol conocarpan 1a 2 3 4 5 6 7 8

RXRα

RXRβ

inactive 26 ± 1 (13 ± 1) 42 ± 3 (9 ± 1) 27 ± 3 (9 ± 1) toxic inactive 23.6 ± 0.8 (26 ± 1) 8.0 ± 0.5 (2.8 ± 0.1) 0.97 ± 0.07 (69 ± 1) 9.1 ± 0.6 (56 ± 2) 24 ± 1 (69 ± 3) 4.3 ± 0.2 (31 ± 1) >30 inactive

nd 32 ± 1 (7 ± 1) 42 ± 1 (6 ± 1) 5.2 ± 0.4 (69 ± 1) nd nd 13.9 ± 0.1 (30 ± 1) 16 ± 4 (3.2 ± 0.5) 4.5 ± 0.8 (121 ± 6) 2.2 ± 0.1 (64 ± 3) 27.1 ± 0.8 (99 ± 2) 6.6 ± 0.2 (48 ± 1) >30 inactive

RXRγ nd 33 ± 1 (7 ± 1) 42 ± 1 (6 ± 1) 43 ± 1 (4 ± 1) nd nd 27.2 ± 0.3 (11 ± 1) 14 ± 1 (2.0 ± 0.1) 3.4 ± 0.4 (44 ± 1) 2.5 ± 0.7 (7 ± 1) 50 ± 3 (18 ± 1) 24.8 ± 0.6 (11 ± 1) inactive inactive

Mean EC50 ± SEM in parentheses (mean fold activation ± SEM), n ≥ 4 independent experiments in duplicate. Inactive: no significant transactivation at 50 μM. nd: not determined.

a

Figure 3. RXR-modulating natural products and their de novo mimetics (1−8).

one-pot multicomponent reaction (Supporting Figure 5) but was too instable for in vitro characterization. The introduction of two fluorine atoms resulted in stable mimetic 1a, which revealed a similar micromolar potency to its template honokiol (Figure 3, Table 1). Drupanin mimetic 2 activated all RXRs with low micromolar potency but with low transactivation efficacy. From the newly identified RXR-modulating NPs, two fundamental scaffolds were repeatedly generated by the de novo design software and predicted as active, namely, the N-substituted tetrahydroindole already contained in 1 and an N-substituted pyrrole. Moreover, several identical designs were generated from more than one template. We focused on tetrahydroindoles 3−5 (including the stabilization by fluorine) and pyrroles 6−8 for synthesis and in vitro characterization. Of these six de novo designs, five showed RXR agonistic activity (Table 1). The most potent NP mimetic 3 activated all three receptor subtypes with low micromolar potency and inherited the high transactivation efficacy of its template valerenic acid on RXRβ. Its activity was also confirmed in HepG2 cells, as compound 3 significantly induced ABCA1 and ApoE expression (Figure 2B,C).

and target prediction models used for scaffold hopping from synthetic ligands to isofunctional NPs. With the expanded collection of RXR-targeting NPs, we set out to obtain novel RXR-activating NP mimetics via automated molecular design. Using honokiol, drupanin, valerenic acid, isopimaric acid, and dehydroabietic acid as individual templates, the software Design of Genuine Structures (DOGS)23 was employed to generate the de novo designs. Relying on a library of commercially available chemicals, this computational tool generates new molecular structures by fusing molecular building blocks and evaluating the resulting designs for their similarity to the given template in each growing step. The sampled designs were then ranked in silico. Again, the pharmacophore-based similarity of the designs to known RXR agonists was evaluated using the CATS pharmacophore descriptors,18 and the RXR activation probability of each design was predicted using the SPiDER15 machine-learning model. De novo designs were selected for synthesis by considering their computed ranks, building block availability, and the presence of a negatively ionizable group for neutralizing interactions with RXR. Honokiol mimetic 1 was prepared in a 5444

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Arg316 (RXRα) and Arg387 (RXRβ), respectively. In the RXRα model, the lipophilic two-ring systems of valerenic acid and its mimetic 3 are superimposed in the hydrophobic center of the Lshaped ligand binding pocket. Neither the NP nor its mimetic extend to the hydrophilic tail of the binding site. In contrast, the suggested ligand binding modes in RXRβ display greater differences, with valerenic acid protruding into a lipophilic subpocket formed by Leu507 and Trp376, which is not occupied by mimetic 3. This observation might explain the preference of valerenic acid for RXRβ.

The de novo-generated NP mimetics varied in their nuclear receptor selectivity profiles, similar to their respective templates (Supporting Figure 3). Compounds 3 and 6, both inspired by the RXR-selective NP valerenic acid, and compound 4 showed favorable receptor preference for RXRs. In contrast, the honokiol-derived mimetic 1a and design 5 displayed activity on various nuclear receptors. In terms of cytotoxicity, most of the computational designs inherited their characteristics from their respective NP templates (Supporting Figure 4). In an attempt to analyze their three-dimensional similarity and potential RXR binding modes, the crystal structures of valerenic acid and its most potent mimetic 3 were determined (Supporting Figure 6). Their experimentally obtained conformations display a strong overlap in the alignment, thereby confirming the NPmimicking shape of 3 (Figure 4A). Computational docking24 of both structures into the RXRα (Figure 4B, PDB code 4K4J25) and RXRβ (Figure 4C, PDB code 1H9U26) ligand binding sites suggested similar binding modes. In the as-obtained models of the ligand−receptor complexes, the carboxylic acid functions of NP and mimetic 3 participate in neutralizing interactions with

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CONCLUSION Enabled by automated computational analysis, new relevant bioactivities of three NPs were discovered. With valerenic acid, the first-in-class selective RXRβ agonist has become available. Valerenic acid’s in vitro pharmacological profile is unique among the known RXR-targeting small molecules and renders this NP a valuable pharmacological tool to explore RXR subtype selectivity in vitro and in vivo. With its unique subtype preference, valerenic acid appreciably contributes to the structure−activity relationship (SAR) of RXR ligands and confirms that subtype selectivity can be achieved with small molecules. Systematic SAR studies with this scaffold may allow identification of selectivity determining structural features and promote RXR targeting drug discovery. Moreover, valerenic acid may serve as starting point for hit-to-lead expansion enabling the development of NPderived RXR modulators. Using both known and newly identified RXR modulating NPs as templates for automated de novo design, we successfully developed tetrahydroindoles as NP-inspired RXR ligands. These computer-generated designs inherited the RXR agonistic properties, subtype preferences, and selectivity profiles from their structurally more intricate natural templates but were accessible in a single synthetic step. By further structural optimization of this compound series or the RXR-targeting NPs, several characteristic challenges in RXR drug discovery, such as subtype selectivity and improved druglikeness, can be addressed. The results of our study confirm that NPs are excellent templates for designing selective and potentially safer synthetic drugs. By relying on automated computer-guided chemical discovery,27 we obtained innovative, synthetically easily accessible, novel bioactive agents, rendering this concept sustainable for future medicinal chemistry.

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EXPERIMENTAL SECTION

General. All compounds (1a, 2−8) for biological evaluation had a purity of >95% according to HPLC-UV analysis at λ = 245 nm and λ = 280 nm. Preparation and Analytical Characterization of Synthetic Natural Product Mimetic 2-(4-(5,5-Difluoro-2,3-dimethyl4,5,6,7-tetrahydro-1H-indol-1-yl)phenyl)acetic Acid (3). 4,4Difluorocyclohexanone (135 mg, 1.00 mmol), 2-(4-aminophenyl)acetic acid (151 mg, 1.00 mmol), and acetoin (110 mg, 1.25 mmol) were dissolved in ethanol (1.0 mL) in a microwave vial, and glacial acetic acid (0.2 mL) was added. The vial was purged with argon and sealed. The mixture was then stirred under microwave irradiation at 100 °C for 4 h. After cooling to room temperature, the mixture was poured into 5% aqueous hydrochloric acid. The resulting suspension was extracted with ethyl acetate (3 × 25 mL), the combined organic layers were dried over magnesium sulfate, and the solvents were evaporated in vacuum. The crude product was purified by column chromatography using methylene chloride/methanol = 98:2 as mobile phase to yield 3 as a colorless solid (249 mg, 78%). 1H NMR (400 MHz, acetone-d6) δ = 1.78 (s, 3H), 1.82 (s, 3H), 2.01 (tt, J = 6.5, 13.5 Hz, 2H), 2.16−2.29 (m, 2H), 2.79 (t, J = 14.4 Hz, 2H), 3.59 (s, 2H), 7.03−7.09 (m, 2H), 7.30−7.35 (m, 2H),

Figure 4. Superimposed crystal structures (A) of valerenic acid (dark green) and its de novo-designed mimetic 3 (orange): proposed binding modes in the RXRα (panel B, PDB code 4K4J) and RXRβ (panel C, PDB code 1H9U26) ligand binding sites. Compounds were docked using GOLD24 software. 5445

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10.47 (s, 1H) ppm. 13C NMR (101 MHz, acetone-d6) δ = 8.21, 9.67, 19.56, 19.85, 31.08, 31.33, 31.69, 32.10, 39.79, 112.12, 127.46, 130.22, 134.26, 137.35, 171.10, 171.66 ppm. MS (ESI+): m/z 320.4 [M + H]+. HRMS (ESI−): m/z calculated 318.1311 for C18H18F2NO2, found 318.1312 [M − H]−. HPLC (method B): tR = 25.210 min. The small molecule X-ray structures of 3 and its template valerenic acid were solved and deposited in the Cambridge Crystallographic Data Centre (CCDC, www.ccdc.cam.ac.uk; valerenic acid, CCDC 1819314; compound 3, CCDC 1819313). For synthesis and characterization of 1a, 2, and 4−8 and for computational and in vitro pharmacological methods, refer to Supporting Information.

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(4) Hartenfeller, M.; Schneider, G. De novo drug design. Methods Mol. Biol. 2010, 672, 299−323. (5) Germain, P.; Chambon, P.; Eichele, G.; Evans, R.; Lazar, M.; Leid, M.; de Lera, A.; Lotan, R.; Mangelsdorf, D.; Gronemeyer, H. International Union of Pharmacology. LXIII. Retinoid X receptors. Pharmacol. Rev. 2006, 58, 760−772. (6) Altucci, L.; Leibowitz, M.; Ogilvie, K.; de Lera, A.; Gronemeyer, H. RAR and RXR modulation in cancer and metabolic disease. Nat. Rev. Drug Discovery 2007, 6, 793−810. (7) Huang, J. K.; Jarjour, A.; Nait Oumesmar, B.; Kerninon, C.; Williams, A.; Krezel, W.; Kagechika, H.; Bauer, J.; Zhao, C.; Baron-Van Evercooren, A.; Chambon, P.; Ffrench-Constant, C.; Franklin, R. Retinoid X receptor gamma signaling accelerates CNS remyelination. Nat. Neurosci. 2011, 14, 45−53. (8) de Lera, A.; Bourguet, W.; Altucci, L.; Gronemeyer, H. Design of selective nuclear receptor modulators: RAR and RXR as a case study. Nat. Rev. Drug Discovery 2007, 6, 811−820. (9) Yamada, S.; Kakuta, H. Retinoid X receptor ligands: a patent review (2007 − 2013). Expert Opin. Ther. Pat. 2014, 24, 443−452. (10) Vaz, B.; de Lera, A. Advances in drug design with RXR modulators. Expert Opin. Drug Discovery 2012, 7, 1003−1016. (11) Kotani, H.; Tanabe, H.; Mizukami, H.; Makishima, M.; Inoue, M. Identification of a naturally occurring rexinoid, honokiol, that activates the retinoid X receptor. J. Nat. Prod. 2010, 73, 1332−1336. (12) Nakashima, K.-I.; Murakami, T.; Tanabe, H.; Inoue, M. Identification of a naturally occurring retinoid X receptor agonist from Brazilian green propolis. Biochim. Biophys. Acta, Gen. Subj. 2014, 1840, 3034−3041. (13) Zhang, H.; Li, L.; Chen, L.; Hu, L.; Jiang, H.; Shen, X. Structure basis of bigelovin as a selective RXR agonist with a distinct binding mode. J. Mol. Biol. 2011, 407, 13−20. (14) Dictionary of Natural Products, version 20.1; Taylor & Francis Group and CRC Press: Boca Raton, FL, U.S.. http://dnp.chemnetbase. com (accessed on Jul 7, 2011). (15) Reker, D.; Rodrigues, T.; Schneider, P.; Schneider, G. Identifying the macromolecular targets of de novo-designed chemical entities through self-organizing map consensus. Proc. Natl. Acad. Sci. U. S. A. 2014, 111, 4067−4072. (16) Schneider, P.; Schneider, G. A computational method for unveiling the target promiscuity of pharmacologically active compounds. Angew. Chem., Int. Ed. 2017, 56, 11520−11524. (17) Schneider, G.; Schneider, P. Macromolecular target prediction by self-organizing feature maps. Expert Opin. Drug Discovery 2017, 12, 271−277. (18) Reutlinger, M.; Koch, C.; Reker, D.; Todoroff, N.; Schneider, P.; Rodrigues, T.; Schneider, G. Chemically advanced template search (CATS) for scaffold-hopping and prospective target prediction for ’orphan’ molecules. Mol. Inf. 2013, 32, 133−138. (19) Proschak, E.; Heitel, P.; Kalinowsky, L.; Merk, D. Opportunities and challenges for fatty acid mimetics in drug discovery. J. Med. Chem. 2017, 60, 5235−5266. (20) Dawson, M.; Xia, Z. The retinoid X receptors and their ligands. Biochim. Biophys. Acta, Mol. Cell Biol. Lipids 2012, 1821, 21−56. (21) de Lera, A.; Krezel, W.; Rühl, R. An endogenous mammalian retinoid X receptor ligand, at last! ChemMedChem 2016, 11, 1027− 1037. (22) Schmidt, J.; Rotter, M.; Weiser, T.; Wittmann, S.; Weizel, L.; Kaiser, A.; Heering, J.; Goebel, T.; Angioni, C.; Wurglics, M.; Paulke, A.; Geisslinger, G.; Kahnt, A.; Steinhilber, D.; Proschak, E.; Merk, D. A dual modulator of farnesoid X receptor and soluble epoxide hydrolase to counter nonalcoholic steatohepatitis. J. Med. Chem. 2017, 60, 7703− 7724. (23) Hartenfeller, M.; Zettl, H.; Walter, M.; Rupp, M.; Reisen, F.; Proschak, E.; Weggen, S.; Stark, H.; Schneider, G. DOGS: reactiondriven de novo design of bioactive compounds. PLoS Comput. Biol. 2012, 8, e1002380. (24) Jones, G.; Willett, P.; Glen, R. C.; Leach, A. R.; Taylor, R. Structure-based design of potent retinoid X receptor α agonists. J. Mol. Biol. 1997, 267, 727−748.

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jmedchem.8b00494. Supporting figures and tables, synthetic procedures, and analytical data of compounds 1a, 2, and 4−-8 and computational and in vitro pharmacological methods (PDF) Molecular formula strings and some data (CSV)

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. ORCID

Gisbert Schneider: 0000-0001-6706-1084 Notes

The authors declare the following competing financial interest(s): G.S. declares a potential financial conflict of interest in his role as life-science industry consultant and cofounder of inSili.com GmbH, Zurich.

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ACKNOWLEDGMENTS We thank Nils Trapp and the SMoCC crystallography platform at ETH Zurich for technical support. This research was financially supported by the Swiss National Science Foundation (Grant IZSEZ0_177477). D.M. was supported by an ETH Zurich Postdoctoral Fellowship (Grant 16-2 FEL-07).

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ABBREVIATIONS USED ABCA1, ATP-binding cassette transporter A1; ApoE, apolipoprotein E; CAR, constitutive androstane receptor; CATS, Chemically Advanced Template Search; DNP, Dictionary of Natural Products; DOGS, design of genuine structures; FXR, farnesoid X receptor; HEK293T, human embryonic kidney cell line 293T; HepG2, human hepatocellular carcinoma cell line; LXR, liver X receptor; nd, not determined; NP, natural product; PPAR, peroxisome proliferator-activated receptor; PXR, pregnane X receptor; RAR, retinoic acid receptor; RXR, retinoid X receptor; SAR, structure−activity relationship; SEM, standard error of the mean; VDR, vitamin D receptor

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REFERENCES

(1) Rodrigues, T.; Reker, D.; Schneider, P.; Schneider, G. Counting on natural products for drug design. Nat. Chem. 2016, 8, 531−541. (2) Schneider, P.; Schneider, G. Privileged structures revisited. Angew. Chem., Int. Ed. 2017, 56, 7971−7974. (3) Schneider, P.; Schneider, G. De novo design at the edge of chaos. J. Med. Chem. 2016, 59, 4077−4086. 5446

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(25) Boerma, L.; Xia, G.; Qui, C.; Cox, B.; Chalmers, M.; Smith, C.; Lobo-Ruppert, S.; Griffin, P.; Muccio, D.; Renfrow, M. Defining the communication between agonist and coactivator binding in the retinoid X receptor α ligand binding domain. J. Biol. Chem. 2014, 289, 814−826. (26) Love, J.; Gooch, J.; Benko, S.; Li, C.; Nagy, L.; Chatterjee, K.; Evans, R.; Schwabe, J. The structural basis for the specificity of retinoidX receptor-selective agonists: new insights into the role of helix H12. J. Biol. Chem. 2002, 277, 11385−11391. (27) Schneider, G. Automating drug discovery. Nat. Rev. Drug Discovery 2018, 17, 97−113.

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