Research ResourceInnate Immunity

Identification of Toll-like receptor signaling inhibitors based on selective activation of hierarchically acting signaling proteins

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Science Signaling  14 Aug 2018:
Vol. 11, Issue 543, eaaq1077
DOI: 10.1126/scisignal.aaq1077

Developing TLR inhibitors

Toll-like receptors (TLRs) are critical initiators of the inflammatory immune response in bacterial sepsis and other inflammatory diseases. To identify specific inhibitors of TLR signaling, Ippagunta et al. developed a stepwise phenotypic screen based on the chemically induced dimerization of TLR signaling intermediates. One compound specifically inhibited TLR signaling and prevented oligomerization of the TLR adaptor protein MyD88. Pretreatment of mice with an analog of this compound prevented bacterial toxin–induced inflammation, thus validating this strategy for the development of TLR-specific inhibitors.

Abstract

Toll-like receptors (TLRs) recognize various pathogen- and host tissue–derived molecules and initiate inflammatory immune responses. Exaggerated or prolonged TLR activation, however, can lead to etiologically diverse diseases, such as bacterial sepsis, metabolic and autoimmune diseases, or stroke. Despite the apparent medical need, no small-molecule drugs against TLR pathways are clinically available. This may be because of the complex signaling mechanisms of TLRs, which are governed by a series of protein-protein interactions initiated by Toll/interleukin-1 receptor homology domains (TIR) found in TLRs and the cytoplasmic adaptor proteins TIRAP and MyD88. Oligomerization of TLRs with MyD88 or TIRAP leads to the recruitment of members of the IRAK family of kinases and the E3 ubiquitin ligase TRAF6. We developed a phenotypic drug screening system based on the inducible homodimerization of either TIRAP, MyD88, or TRAF6, that ranked hits according to their hierarchy of action. From a bioactive compound library, we identified methyl-piperidino-pyrazole (MPP) as a TLR-specific inhibitor. Structure-activity relationship analysis, quantitative proteomics, protein-protein interaction assays, and cellular thermal shift assays suggested that MPP targets the TIR domain of MyD88. Chemical evolution of the original MPP scaffold generated compounds with selectivity for distinct TLRs that interfered with specific TIR interactions. Administration of an MPP analog to mice protected them from TLR4-dependent inflammation. These results validate this phenotypic screening approach and suggest that the MPP scaffold could serve as a starting point for the development of anti-inflammatory drugs.

INTRODUCTION

Toll-like receptors (TLRs) are a critical part of the innate pathogen recognition system (1). Composed of a family of 10 functional receptors in humans, TLRs recognize different pathogen- and host-derived molecules to initiate cellular and inflammatory immune responses (24). They are primarily expressed on innate immune cells and activate a large number of cytotoxic and inflammatory mediators, such as nitric oxide, tumor necrosis factor–α (TNFα), and interleukin-1 (IL-1). Exaggerated or prolonged TLR-mediated inflammation can lead to pathology in etiologically distinct diseases, including bacterial sepsis, ischemia reperfusion injury during stroke, systemic lupus erythematosus (SLE), and obesity-related metabolic inflammation (59). TLRs signal through Toll/IL-1 receptor (IL-1R) domain (TIR)–containing proteins, which are shared with members of the IL-1 family, including the IL-1R and IL-18R (1012). Members of the IL-1 family are also stimulated by other inflammatory receptors, such as Nod-like receptors (NLRs) (13). Therefore, development of small-molecule inhibitors of TLR/IL-1R signaling pathways may have broad therapeutic application beyond TLR-mediated inflammation to other diseases, such as NLR-mediated gout (1416). Still, despite the pressing need, TLR inhibitors are currently not clinically available, at least in part due to the complexities of TLR signal transduction [for reviews, see (8, 17)]. Here, we describe a screening platform for the identification of small-molecule inhibitors of TLR-specific signal transduction pathways.

TLR signaling depends on the homotypic protein interactions between the TLR TIR domain– and the TIR-containing intracellular adaptor protein MyD88 (also myeloid differentiation primary response 88; Fig. 1A) (11, 18, 19). In most cases, MyD88 binds directly to the intracellular TLR moiety, whereas in the case of TLR2 and TLR4, the TIR-containing protein TIRAP/MAL (Toll/IL-1R domain–containing adapter protein/MyD88 adapter-like protein) appears to act as a molecular bridge between TLR and MyD88 (Fig. 1A) (2022). An exception to this rule is the double-stranded RNA receptor TLR3, whose signaling does not depend on MyD88 but is mediated by two other TIR-containing proteins, TRAM and TRIF (2327). Although this “TRIF pathway” is also used by TLR4 (23), MyD88 is a critical mediator of TLR4-dependent lipopolysaccharide (LPS)–induced sepsis (28). Oligomerization of MyD88 results in sequential recruitment of IRAK (IL-1R–associated kinase) family members through death domain (DD) interactions (11, 29). IRAK family members then bind and oligomerize TRAF6 (TNF receptor–associated factor 6), which is necessary to activate nuclear factor κB (NF-κB) and mitogen-activated protein kinase (MAPK) downstream signaling pathways (Fig. 1A) (3032). Whereas the function of TLR signaling proteins acting upstream of TRAF6 is largely restricted to TLR/IL-1R members, activation of TRAF6 and its downstream targets is used by various receptors and signaling pathways, including members of the TNFR (TNF receptor) family (33). Consequently, mice deficient in MyD88 do not show overt adverse symptoms unless challenged with infectious agents (12). However, these mice are protected from septic shock (28). MyD88-deficient humans are more susceptible to bacterial infections during childhood, but are largely unaffected as adults, suggesting compensatory mechanisms mediated by other parts of the immune system (34). Together, these data suggest that targeting TLR signaling upstream of TRAF6 may be most suitable for the development of TLR/IL-1R inhibitors because even complete inhibition of signal transduction is unlikely to result in unmanageable adverse events.

Fig. 1 A phenotypic HTS platform based on hierarchically acting TLR signaling proteins.

(A) Model of the MyD88 signaling pathway activated by different TLR and IL-1R family members. Established protein interactions are highlighted (yellow circles). Proteins activated by coumermycin (CM)–induced Gyrase B (GyrB) dimerization are indicated with green bolts. TIR domains are shown in purple, and DDs in dark blue. KD, kinase domain; AP1, activator protein 1. (B) NF-κB luciferase (Luc.) reporter activity in human embryonic kidney (HEK) 293T cells expressing the indicated GyrB fusion proteins and treated as indicated. Fold change data normalized to vehicle-treated controls (Ctrl) are means ± SD from three independent experiments. (C) Western blot analysis of MyD88 expression in TIRAP-GyrB–expressing HEK293T cells that were infected with lentivirus expressing Cas9 and control sgRNA (ctrl) or sgRNA against MyD88 (MyD). Blots are representative of three independent experiments. (D) NF-κB luciferase reporter activity of TIRAP-GyrB–expressing HEK293T cells transduced with Cas9/indicated sgRNA and stimulated as indicated. RLU, relative light units; Co, control. Data are means ± SD from three independent experiments. **P < 0.01, ***P < 0.001, ****P < 0.0001 by Mann-Whitney U test (B) or two-way analysis of variance (ANOVA) with Sidak’s multiple comparison test (D).

TLR-mediated cell activation can be mimicked by chemically induced dimerization of fusion proteins of Gyrase B (GyrB) and the TLR signaling proteins MyD88 and TRAF6 (30, 35). Here, we extended this approach to TIRAP, which was also fused to GyrB, allowing inducible dimerization after exposure to the bivalent antibiotic coumermycin A1 (CM) (36). Expression of TIRAP, MyD88, or TRAF6 fusion proteins allowed for selective activation of specific TLR signaling intermediates that recapitulate the hierarchy of signal transduction observed during physiological receptor activation (30). When stably expressed in HEK293T cells expressing an NF-κB luciferase reporter, this stepwise system of three inducible TLR signaling proteins allowed us to identify small-molecule drugs that interfered with activation of distinct signaling intermediates (Fig. 1A). Using a bioactive compound library, we identified one compound with TLR-specific inhibitory activity, which we further characterized in more detail with respect to mechanism of action, in vivo activity, and developmental opportunities through structure-activity investigations.

RESULTS

A high-throughput screen identifies TLR inhibitory compounds

Because genetic and biochemical evidence suggests that TIRAP acts upstream of MyD88 to mediate TLR signaling (20, 21, 37), we fused GyrB to the TIR domain–containing protein TIRAP. When expressed in HEK293T cells, GyrB-TIRAP fusion proteins initiated robust CM-inducible signaling activity, similar to fusion proteins of GyrB and MyD88/TRAF6 (Fig. 1B). To confirm that TIRAP was activated upstream of MyD88, we deleted MyD88 in GyrB-TIRAP cells by single guide RNA (sgRNA)/CRISPR associated protein 9 (Cas9)–mediated deletion, which ablated TIRAP-mediated NF-κB activation (Fig. 1, C and D) and response to IL-1β but not TNFα (Fig. 1D). Thus, GyrB-TIRAP can be used to activate the TLR pathway upstream of MyD88, recapitulating TLR2- and TLR4-mediated signal transduction.

Three inducible cell lines (TIRAP-GyrB, MyD88-GyrB, and TRAF6-GyrB) were optimized for large-scale stepwise 384-well format high-throughput screening (HTS). As a primary screen, TIRAP-GyrB cells were used to identify compounds with NF-κB–specific inhibitory activity and to exclude compounds with nonspecific activity (toxicity; Fig. 2A). We screened a total of 4364 unique compounds from our bioactive compound library, which was acquired from various sources and included 913 FDA (U.S. Food and Drug Administration)–approved drugs or clinical candidates. Because IκBα-kinase (IKK) is required for NF-κB activation downstream of TRAF6 (38, 39), we used as pathway-specific reference compound PS1145, a selective inhibitor of IKK. As nonspecific reference compound, we used staurosporine, a kinase inhibitor with largely nonselective toxicity (40). Dimethyl sulfoxide (DMSO) testing demonstrated tolerance of the cell lines up to a concentration of 0.63% DMSO (fig. S1). Assay validation included analysis of within-plate and between-plate variation, which consistently gave Z′ factors of >0.5, demonstrating the robustness of this phenotypic screening platform (fig. S2). The primary screen criteria identified 213 hits, which were further screened by generating full dose-response curves on all three cell lines (Fig. 2A). Compound selectivity was determined by preferential inhibition of signaling initiated by an individual adaptor protein. Compounds that inhibited TRAF6 were eliminated as TLR–nonspecific. Compounds with selective activity against TIRAP but not MyD88 and TRAF6 suggest selectivity for the TLR2/TLR4 pathway, whereas activity against TIRAP and MyD88 suggests general or “pan” activity against all TLRs (Fig. 2A). Only eight compounds exhibited preferential activity against TIRAP or TIRAP/MyD88 over TRAF6 [ratio IC50 (half maximal inhibitory concentration), >5-fold]. Tertiary screens were performed with resynthesized compounds using physiological TLR ligand-mediated stimulation of the RAW264.7 macrophage cell line or primary macrophages (41). Of the eight compounds identified, seven were excluded because of lack of activity on RAW264.7 cells or additional activity against cell activation by TNFα or Curdlan, a β-1,3-glucan that activates cells TLR-independently through Dectin-1 (42).

Fig. 2 Identification of MPP as TLR inhibitory compound using HTS based on inducible TLR signaling proteins.

(A) Schematic of HTS workflow. (B) NF-κB luciferase reporter activity (left) and Alamar blue–determined cell viability (right) for the indicated reporter cell lines after treatment with MPP. Data are means ± SD from three independent experiments. (C) Enzyme-linked immunosorbent assay (ELISA) analysis of TNFα production by mouse BMM stimulated with TLR agonists for 6 hours in the presence of the indicated concentration of MPP. Data are means ± SD of three independent experiments. Pam, Pam3Cys. (D) Western blot analysis of the indicated proteins in lysates from CpG-DNA–, R848-, and Curdlan (Curd)–treated BMM in the presence or absence of MPP. Antibodies against total p38 were used as loading control. Blots are representative of three independent experiments. (E) ELISA analysis of TNFα production by wild-type (WT) and ERα-deficient BMM that were treated for 6 hours with CpG-DNA in the presence of the indicated concentration of MPP. Data are means ± SD of three independent experiments. (F) Western blot analysis of IκBα and MAPK phosphorylation in lysates from ERα-deficient BMM that were treated for 20 min with CpG-DNA in the presence or absence of MPP. Antibodies against total p38 were used as loading control. Blots are representative of three independent experiments. **P < 0.01, ***P < 0.001, ****P < 0.0001 by one-way ANOVA with Dunett’s multiple comparisons test (C) or a paired t test (two-tailed; E).

The remaining compound, methyl-piperidino-pyrazole (MPP), exhibited promising properties. This basic side chain–containing pyrazole (BSC-pyrazole) is an estrogen receptor α (ERα)–selective inhibitor (43). Computational analysis identified that MPP was unique in our bioactive library. MPP inhibited TIRAP- and MyD88-mediated NF-κB activity comparably at low micromolar concentrations, suggesting that it has general (pan)-TLR inhibitory activity (Fig. 2B). Consistent with this interpretation, MPP interfered with TNFα release from primary macrophages that were stimulated with CpG-DNA (TLR9), Resiquimod (R848; TLR7), Pam3Cys (TLR2), or LPS (TLR4; Fig. 2C). In contrast, MPP did not reduce TNFα release induced by Curdlan (42). Thus, MPP interfered selectively with TLR-induced cell activation.

MPP inhibits TLR signaling by preventing dimerization of the MyD88 TIR domain

TLR signaling downstream of TRAF6 activates multiple well-defined pathways, including the NF-κB and MAPK pathways (Fig. 1A) (30, 32). When we investigated the effect of MPP on TLR-induced signaling activation in bone marrow–derived macrophages (BMM) after CpG-DNA activation, we found that MPP blocked degradation of IκBα, reflecting NF-κB activation, as well as phosphorylation of multiple MAPK pathways almost completely (Fig. 2D). Because we observed no preferential activity toward a specific pathway, these data suggest that MPP acts upstream of TRAF6. MPP also blocked NF-κB and MAPK pathway activation downstream of the TLR7 ligand R848, albeit not completely (Fig. 2D). As observed earlier, Curdlan-induced cell activation remained largely unaffected (Fig. 2, C and D). Similarly, MPP inhibited TLR9-induced TNFα release and activation of signaling pathways comparably in both wild-type and ERα-deficient BMM, strongly suggesting that the effects of MPP on TLR and ERα inhibition are independent events (Fig. 2, E and F). Together, the data suggest that MPP blocks the MyD88 pathway upstream of TRAF6, independent of ERα inhibition.

To understand how MPP inhibits TLR signaling, we investigated the assembly of the MyD88 signaling complex after CpG-DNA stimulation. Using stable isotope labeling with amino acids in cell culture (SILAC) and quantitative mass spectrometry (MS), we identified proteins interacting with MyD88 from unstimulated and CpG-DNA–stimulated cells treated with and without MPP. Whereas the bait protein MyD88 was detected at similar amount in all conditions, reflected by protein ratios close to 1 (Fig. 3A), CpG stimulation increased the interaction between known components of the TLR/MyD88 signaling complex. For example, IRAK4 was identified with 17 unique peptides at 8.4-fold higher amount in CpG-DNA–stimulated samples as compared to unstimulated control samples (Fig. 3A). Strikingly, MPP treatment almost completely blocked recruitment of all activation-dependent MyD88-interacting proteins, including IRAK4, which directly interacts with MyD88 (44, 45). We confirmed this finding in small-scale coimmunoprecipitation (co-IP) experiments with antibodies against IRAK4 and TRAF6 (Fig. 3B). These data suggest that MPP blocked a very early event in MyD88 activation.

Fig. 3 TSI block formation of the MyD88 signaling complex by interference with TIR-mediated dimerization.

(A) Quantitative MS analysis of proteins copurifying with MyD88 in CpG-DNA–stimulated RAW264.7 cells treated with MPP, as indicated. Data are the fold change in peptide abundance from CpG-DNA–treated versus control cells (open bars) and CpG-DNA plus MPP-treated versus control cells (closed bars). Numbers in parenthesis indicate the number of unique peptides identified. Data are from one experiment. (B and C) Western blot analysis of the indicated proteins coprecipitating with MyD88 in lysates (Ly) from MyD88-GyrB-F (Flag)–expressing RAW264.7 cells treated with CpG-DNA (45 min) (B) or CM (20 min) (C) and MPP, as indicated. Endo, endogenous. Blots (left) are representative of four independent experiments. Normalized band intensities (right) are pooled from all experiments. (D) Western blot analysis of MyD88 domains coprecipitating with MyD88 in lysates from HEK293T cells transfected with full-length (MyD88-F) or TIR domain [TIR–hemagglutinin (HA)] of MyD88 and treated with MPP, as indicated. Blots (left) are representative of four independent experiments. Normalized band intensities (right) are pooled from all experiments. (E) Western blot analysis of MyD88 domains coprecipitating with MyD88 in lysates from HEK293T cells transfected with full-length (MyD88-F) or death domain of MyD88 (MyD88-DD-HA) and treated with MPP, as indicated. Blots are representative of four independent experiments. (F to I) CETSA analysis of the stability of endogenous MyD88 in HEK293T cells exposed to 50 μM TSI-13-57 and the indicated temperatures in degree Celsius (F and G) or the indicated concentrations of TSI-13-57 and 43.8°C (H and I). Western blots (F and H) are representative of three independent experiments. MyD88 band intensities (G and I) normalized to β-ACTIN relative to controls [37°C (G) and 12.5 μM (I)] are means ± SD pooled from three independent experiments. TCL, total cell lysate. *P < 0.05, **P < 0.01, ****P < 0.0001 by two-way ANOVA with Sidak’s multiple comparison test (B and D), one-way ANOVA with Sidak’s multiple comparison test (C), paired t test (two-tailed) (G), and one-way ANOVA with Dunett’s multiple comparisons test (I).

The currently favored model of MyD88 activation involves TLR-induced, TIR domain–mediated dimerization of MyD88 as the first step of signal induction, followed by a spiral assembly of further MyD88 molecules (29, 46). When we investigated the effect of MPP on MyD88 homodimerization after TLR stimulation by co-IP, we found that MPP inhibited recruitment of endogenous MyD88 and IRAK4 to GyrB-MyD88 (Fig. 3C). Furthermore, co-IP experiments in HEK293T cells coexpressing the TIR domain or the death domain with full-length MyD88 indicated that MPP strongly reduced the interaction of the TIR domain but not the death domain with full-length MyD88 (Fig. 3, D and E). Together, these data indicated that MPP inhibited homotypic MyD88 dimerization, thereby preventing assembly of a higher-order MyD88 complex, which were required for consecutive recruitment and activation of IRAK4.

To validate that MyD88 is a direct target of MPP, we performed cellular thermal shift assays (CETSAs). In these experiments, we treated HEK293T cells with an analog of MPP, TSI-13-57, which exhibited similar activity in the low micromolar range but reduced toxicity in comparison to MPP (Table 2). Cells were heated briefly before lysates were collected and probed by Western blot for endogenous MyD88 and β-ACTIN. TSI-13-57 treatment stabilized and protected MyD88 from temperature-sensitive loss; however, β-ACTIN was not affected (Fig. 3, F and G). Moreover, we found that the concentrations of TSI-13-57 required for MyD88 stabilization and inhibition of TLR-mediated TNFα release corresponded well to each other, with median effective concentration (EC50) values in the low micromolar range (Fig. 3, H and I). Together, our results indicate that MPP and its analog TSI-13-57 likely bind directly the TIR domain of MyD88 to prevent TLR-mediated cell activation.

Optimizing the chemical structure of MPP identifies determinants of potency and selectivity

To understand the chemical requirements for MPP-mediated TLR inhibition, we generated various analogs of MPP (Tables 1 and 2 and tables S1 and S2) and assessed their activity by evaluating TLR9-mediated TNFα production in RAW264.7 cells and ER binding affinity. We found that the appended BSC at position R5 of MPP’s pyrazole core was necessary for the inhibitory activity of MPP because compound TSI-13-03 that lacked this group did not inhibit CpG oligonucleotide-stimulated TLR9 activity (Table 1, entry 2). By contrast, blocking of the free phenols on N1 and C3 of MPP as methyl ethers decreased ER binding affinity without compromising TLR9 inhibition (Table 1, entry 3), suggesting that TLR9 inhibition and ERα binding may be separable. By substituting side chains of various sizes at position C4 of the pyrazole, we found that smaller groups were preferred (Table 1, entries 1, 4, and 5) and the presence of a phenol ring was poorly tolerated (Table 1, entry 6). The effect of the substituent on C4 on ERα binding is roughly the opposite as on TLR9 inhibition. From our previous studies on MPP, we know that the location of the BSC can significantly influence the binding affinity for ER (4749). As the BSC was moved from C5 to C4 (Table 1, entries 7 and 8), TLR9 inhibition was retained as was substantial ERα binding and, curiously, affinity for ERβ increased as compared to MPP. Moving the BSC to C3 (Table 1, entry 9) caused a major decrease in binding affinity to the ERs while retaining TLR9 inhibition. Thus, we identified a chemical modification that limits ER binding without affecting TLR inhibition to limit potential ER-related off-target effects.

Table 1 Initial SAR to differentiate TLR inhibition from ER binding affinity.

IC50 and EC50values for TLR9 were obtained using RAW264.7 cells. Values are presented as means ± SD of three independent experiments.


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Table 2 Initial hit compounds that demonstrate selective TLR inhibition.

IC50 and EC50 values were obtained using RAW264.7 cells. n.d., not done. Values are presented as means ± SD of three independent experiments.


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When MPP-derived compounds with the BSC on C3 were tested for inhibitory activity against multiple TLRs and Dectin-1, we found that the location and number of free phenolic groups had a marked effect on both TLR inhibitory activity and toxicity (table S2). We noted that compounds with a phenol group at N1 (Table 2, entries 1 and 3) only weakly inhibited TLR activity. Movement of the phenol to C5 (Table 2, entry 2) increased potency against all TLRs and decreased toxicity. When both of these phenols were present (Table 2, entry 3), the TLR activity was moderate, and toxicity was relatively low. Moving the hydroxyl on the C5 phenyl from the para position to the meta position completely abolished TLR inhibition (Table 2, entry 4), which suggests that there may be some geometrically specific interactions with the phenol or an electronic donating effect of the hydroxyl group into the pyrazole ring that assists with interaction with the TLR target.

As we expanded our scope to include additional functional groups, we observed that only compounds with an electron-withdrawing para-nitro group on N1 specifically inhibited TLR9 activity (Table 2, entry 5, and Fig. 4A). In contrast, addition of an electron-donating group on the C5 ring restored pan-TLR inhibitory activity (Table 2, entry 6). Moreover, removal of the N1 substituent and increased electron-donating capability at C5 resulted in a compound with TLR9- and TLR7-selective activity (Table 2, entry 7, and Fig. 4A). Last, replacement of the MPP 1-piperidinyl BSC with a 1-pyrazolyl BSC (Table 2, entry 8, and Fig. 4A) afforded a compound complete selectivity for TLR7. Thus, our data indicate that slight modifications to the electron density of the pyrazole core or alterations to the identity of the BSC can influence the specificity of the compounds. These results could lead to the development of selective and specific TLR modulators.

Fig. 4 MPP analogs with selectivity against specific TLR signaling pathways and TIR domains.

(A) ELISA analysis of TNFα production and Alamar blue (AB) staining for cell viability in RAW264.7 cells treated as indicated. Data are mean IC50 values ± SD from three independent experiments. (B) Interaction-dependent luciferase activity and cell toxicity in HEK293T cells transfected with the indicated M2H protein pairs and a Gal4 luciferase reporter treated with TSI-13-48 and TSI-13-57 at indicated concentrations. Data relative to maximal inhibition by staurosporine are means ± SD from three independent experiments. **P <0.01, ***P < 0.001, ****P < 0.0001 by two-way ANOVA with Sidak’s multiple comparison test (A) or paired t test (two-tailed) (B).

We speculated that the apparent selectivity in TLR inhibition might reflect preferential interference with specific TIR domain interactions. To test this possibility, we established a mammalian two-hybrid (M2H) system that allowed analysis of specific protein interactions quantitatively. Like the yeast two-hybrid system, this assay is based on the reconstitution of the function of a transcriptional activator in transfected HEK293T cells that drives expression of a luciferase reporter. In the presence of either a TLR9-selective (TSI-13-48) or pan-TLR (TSI-13-57) inhibitor, we tested the interaction of MyD88 TIR with MyD88 TIR, TLR9 TIR with MyD88, and TIRAP with MyD88 (Fig. 4B). Consistent with our earlier data (Fig. 3, F to I), we found that TSI-13-57 inhibited homodimerization of the TIR domain of MyD88 but showed little inhibitory activity on the interaction between TLR9 TIR and MyD88 and no activity against interaction between TIRAP and MyD88 (Fig. 4B). In marked contrast, TSI-13-48 did not affect homodimerization of MyD88 TIR or interaction between TIRAP and MyD88 but reduced interaction between TLR9 TIR and MyD88 (Fig. 4B). The IC50 values obtained in this M2H system matched closely those obtained during physiological TLR activation of macrophages, with respect to both inhibition of MyD88 dimerization by TSI-13-57 and inhibition of TLR9 TIR–MyD88 interaction by TSI-13-48 (Fig. 4, A and B, and Table 2). Thus, modifications of the MPP scaffold that generates compounds with selective activity against specific TLRs block specific TIR domain interactions.

An MPP analog protects mice from sepsis in vivo

Release of the gram-negative cell wall component LPS (or endotoxin) is the basis of sepsis, mediated through TLR4 and executed by TNFα-induced liver injury (5, 50). Characterization of the in vivo pharmacokinetics (PK) of TSI-13-57 indicated a dose-dependent increase in the maximum serum concentration (Cmax) after intraperitoneal administration and a plasma half-life of ≥9.0 hours (Table 3). No significant changes in hematological parameters, clinical chemistry, or gross organ anatomy were observed at the terminal point of the study, corresponding to the lack of apparent toxicity against various cell lines in vitro (Table 4). Mice treated with either 100 or 200 mg/kg of TSI-13-57 were challenged with LPS. Analysis of the TNFα concentration in the serum 90 min after challenge indicated that low-dose treatment reduced systemic inflammatory responses to TLR stimulation, and high-dose treatment almost completely blocked LPS-induced TNFα release (Fig. 5A). In vivo inhibitory activity correlated well with plasma concentrations of TSI-13-57 and its known in vitro IC50 of 6.73 μM for LPS-induced TNFα release from macrophages (Fig. 4A and Table 2). These data provide proof of principle that MPP analogs with TLR inhibitory activity can be used to counteract TLR-induced effector functions in vivo.

Table 3 In vivo PK of TSI-13-57.

Mice were intraperitoneally treated with TSI-13-57, and the serum concentrations of compound were determined during time to assess Cmax (peak plasma concentration), Tmax (time to reach Cmax), AUCall (total area from zero to the last sampling time point), Vd (volume of distribution), Cl (clearance), and t1/2 (half-life). i.p., intraperitoneally; N.A., not analyzed.

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Table 4 In vitro early ADMET analysis of TSI-13-57.

Absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of TSI-13-57 were analyzed in vitro to assess suitability for in vivo applications. CLint, intrinsic clearance.

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Fig. 5 TSI-13-57–mediated inhibition of LPS-induced TNFα release in vivo.

(A) ELISA analysis of TNFα concentration in the plasma of mice that were pretreated as indicated and challenged with intraperitoneal LPS. Data relative to vehicle control treatment are means ± SD of five mice per group from two independent experiments. (B) Liquid chromatography (LC)–MS/MS analysis of TSI-13-57 concentration in the plasma of mice described in (A). Data are means ± SD of five mice per group from two independent experiments. ****P < 0.0001 by one-way ANOVA with Dunett’s multiple comparisons test (A).

DISCUSSION

The screening approach presented resembles other phenotypic screening methods where a series of events that lead to a complex phenotype are interrogated for perturbation by compound libraries. An important advantage of phenotypic screening is that not only known but also unknown cellular mechanisms can be explored. In particular, molecular events that are more difficult to recapitulate in vitro, such as dynamic protein interactions, which are less amenable to targeted drug development, can be investigated during their physiological function in the natural context in living cells. The major disadvantage of phenotypic screening approaches is that the identity of the drug target remains unknown and criteria to prioritize hit series are primarily driven by the chemical nature of the compounds. The labor-intensive identification process may postpone the discovery of the actual drug target, which may reveal undesirable properties. Thus, the process from hit identification to target validation can be time-consuming and difficult.

Our screening approach addresses these problems by two particular features. First, on the basis of artificially activated, hierarchically acting signaling molecules, we narrow the phenotypic window to a (largely) defined process of signaling events that are known to be restricted to TLR signaling pathways. Although this procedure adds additional effort to the screening procedure itself, it simplifies drastically the following steps of drug target identification. We took advantage of GyrB-mediated induced proximity (dimerization), which allowed us to activate distinct intermediates in the TLR signaling cascade. Given that induced proximity is a common principle in signal transduction, it is likely that similar screening paradigms can be developed for other signaling pathways. Second, we developed a method to assess quantitatively the entire signaling process in question using SILAC-based quantitative MS, which captures the assembly of all essential components of the TLR-specific pathway. The first aspect allowed us to reduce the number of 213 hits to only eight compounds, whose analysis in more detailed, yet still relatively simple assays could be managed with reasonable effort. The second aspect, the recapitulation of the phenotypic signaling window by quantitative MS, allowed us to focus on MyD88 dimerization as the most likely affected mechanism, an interpretation that was supported by additional evidence based on co-IPs, two-hybrid assays, and CETSA. Our attempts to further characterize drug target interaction, such as thermal shift assays based on recombinant protein or structural analyses based on x-ray cocrystallography, were impeded by unfavorable properties of the recombinant MyD88 TIR domain (MyD88 TIR), most likely due to protein aggregation. MyD88 TIR had been crystallized before using coincubation with the Escherichia coli protein TcpC to prevent aggregation (51). Possibly, a similar strategy could be used to support structural investigation of the interaction between compound and MyD88, which may guide future compound optimization. Although in vitro and in vivo PK analyses did not reveal apparent liabilities of the compounds investigated, improved potency will be an important goal for optimization and will facilitate further in vivo testing, particularly in long-term studies. Together, our work validates a novel phenotypic screening approach and identifies one chemotype with highly selective TLR inhibitory activity.

The relative scarcity of TLR signaling inhibitors developed on the basis of targeted approaches highlights the strategic opportunity of this screening approach. One interesting compound, the peptidomimetic ST2825, was developed on the basis of the BB-loop peptide of MyD88 TIR, which contributes to MyD88 dimerization (52, 53). Consistent with the expected mechanism of action, ST2825 blocked MyD88 dimerization, IRAK recruitment, and signal transduction. Potency of ST2825 was, however, relatively modest with an IC50 >10 μM for IL-1β–induced NF-κB activity (53). Another compound, C29, was selected as TLR2-specific compound based on computer-aided drug design and was shown to reduce TLR2-mediated cell activation (54). Potency, however, was low (IC50, ≥20 μM), and toxicity and therapeutic window were not assessed. Thus, alternate strategies to identify TLR signaling inhibitors are warranted.

Another, emerging class of compounds that interfere with TLR-mediated inflammatory responses are IRAK4 kinase inhibitors. Although these inhibitors take advantage of a defined structure for targeted drug development, the specific pathway and cell functions controlled by IRAK4 kinase activity are less certain. In contrast to the scaffolding function of IRAK4, which is essential for canonical signaling pathways such as NF-κB, the kinase function of IRAK4 appears to play a minor role in canonical TLR pathways, but rather controls a subset of TLR-induced genes in a monocyte-specific way, possibly through mRNA stabilization (44, 5558). Still, inhibition of IRAK4 kinase activity in monocytes results in strongly reduced cytokine production (55, 57), and an increasing number of chemically diverse, selective kinase inhibitors have been developed, several of which demonstrated in vivo efficacy in proof-of-principle models (5968). Although most IRAK4 inhibitors showed in vivo PK properties requiring further improvement, a very recently published compound, Pf-06650833, showed remarkable in vivo potency (2.4 nM IC50 on R848-induced peripheral blood mononuclear cells) and selectivity and has been moved forward to clinical studies (69). Together, IRAK4 inhibitors represent an interesting class of TLR inhibitors with a most likely more selective interference with TLR biology. Thus, the therapeutic impact of IRAK4 inhibitors is expected to be different from TSI identified in this study or genetic loss-of-function models. Comparing the effects of TSI and IRAK4 kinase inhibitors will be an important future goal, possibly establishing specific therapeutic indications for the two classes of compounds.

A particularly interesting observation of the MPP-derived compounds described in this study was their developmental potential toward inhibition of specific TLR pathways. Although the original compound, MPP, displayed pan-TLR inhibitory activity and had high ERα binding affinity, through our structure-activity relationship studies, we were quickly able to make modifications to the substituents on the pyrazole core of MPP that eliminated binding to both ERα and ERβ while retaining and improving potency as TSIs. In addition to compounds that were inhibitory for TLR2/TLR4/TLR7/TLR9 (pan-TLR antagonists), a number of compounds emerged having highly selective activity against TLR7-, TLR9-, and TLR7/TLR9-induced cell activation. Compounds with selectivity for specific TLRs (or a combination thereof) are particularly interesting with respect to diseases that are mediated by defined TLRs, for example, SLE, which appears primarily promoted by the nucleic acid–recognizing TLRs, TLR7 and TLR9 (70). TLR2/TLR4-selective compounds were not identified. The pan-TLR and TLR9-selective activity of TSI-13-57 and TSI-13-48 correlated with their interference with MyD88 TIR homodimerization and interaction between TLR9 and MyD88, respectively. These data suggest that selectivity is governed by interference with specific TIR domain interactions. Still, the molecular mechanism controlling selectivity is unclear. We favor a model where all compounds bind to the MyD88 TIR, whose engagement by upstream TIRs may involve structurally distinct motifs, which may be differentially affected by specific compounds. Alternatively, different compounds could bind to homologous regions of different TIR domains. It is likely that structural data will be required to delineate the precise mechanism of action. In any case, we expect that understanding the molecular basis of compound activity and selectivity will contribute to our understanding of the molecular mechanism of TLR signal transduction and, hopefully, successful future drug development.

MATERIAL AND METHODS

Reagents and plasmids

CpG-DNA refers to the phosphothioate backbone containing oligonucleotide 1668 (TCCATGACGTTCCTGATGCT; TIB Molbiol). Other agonists used were LPS (E. coli 0127:B8; Sigma-Aldrich), coumermycin A1 (Sigma-Aldrich), R848 (GLSynthesis), tripalmitoyl cysteinyl lipopeptide (Pam3Cys; EMC Microcollections), and Curdlan (InvivoGen). The following antibodies were used: FLAG [M2 (soluble and bead immobilized)], β-ACTIN (Sigma-Aldrich), MyD88, IκBα, P-p38, P-JNK, P-ERK, p38, and Myc-Tag (Cell Signaling Technology), and HA (Roche); secondary antibodies were conjugated to horseradish peroxidase (GE Healthcare Life Sciences). Chemiluminescent substrate was from Thermo Fisher Scientific. ELISA kits were from eBiosciences (TNFα). Luciferase assay system was from Promega. Alamar blue assay system and Lipofectamine 2000 were from Invitrogen. Full-length human ERα and ERβ were obtained from PanVera/Invitrogen; tritiated estradiol was obtained from PerkinElmer.

Expression plasmids were established by conventional molecular biology techniques and verified by DNA sequencing. Epitope tags used consisted in tandem triple tags (HA and FLAG) or single tag (Myc), which were fused N-terminal to the complementary DNA of full-length mouse MyD88, the MyD88 DD (amino acids 2 to 109), or the MyD88 TIR domain (amino acids 157 to 296). FLAG-tagged TIRAP-GyrB was expressed as fusion protein consisting in triple FLAG-tagged, full-length mouse TIRAP, and a C-terminal GyrB moiety using a lentiviral vector containing a PGK1 promoter. FLAG-tagged MyD88-GyrB was expressed as fusion protein consisting in triple FLAG-tagged, full-length MyD88, and a C-terminal GyrB moiety using a murine stem cell virus (MSCV)–based retroviral vector (MSCV-puro; Clontech). FLAG-tagged TRAF6-GyrB was expressed as fusion protein consisting in a triple FLAG-tagged, N-terminal part of human TRAF6 (amino acids 2 to 351), and a C-terminal GyrB moiety using a pcDNA3-based vector with EF1α (elongation factor 1α) promoter.

Reporter cell lines

To establish NF-κB–responsive luciferase reporter cell lines, HEK293T cells were transduced with a lentiviral vector containing a luciferase reporter gene under control of three NF-κB–binding sites. Single cell clones of transduced cells were established by limiting dilution, and inducible NF-κB activity was confirmed by transfection with various TLR adaptor proteins. Stable reporter cell lines expressing GyrB fusion proteins were established by viral transduction (MyD88-GyrB and TIRAP-GyrB) or lipofectamine transfection (TRAF6-GyrB), followed by antibiotic selection. Stably growing cells were cloned by limiting dilution, and clones that showed CM-mediated NF-κB activation were selected for further experiments.

Cell culture and retrovirus generation

HEK293T cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM; Life Technologies), supplemented with 10% (v/v) fetal bovine serum (FBS; HyClone), 50 μM 2-mercaptoethanol, antibiotics [penicillin G (100 IU/ml) and streptomycin sulfate (100 IU/ml)], and 1 mM pyruvate. RAW264.7 cells were cultured in RPMI 1640 (Life Technologies), supplemented with 10% (v/v) FBS (Hyclone), 50 μM 2-mercaptoethanol, and antibiotics [penicillin G (100 IU/ml) and streptomycin sulfate (100 IU/ml)], as described (30, 71). BMMs were generated by cultivating unfractionated BM cells {obtained from female C57BL/6 mice or ERα-deficient mice [Esr1tm1Ksk (72); The Jackson Laboratories] and corresponding wild-type control mice, as indicated in figure legends} for 6 days in DMEM (Invitrogen), supplemented with 10% (v/v) FBS (Hyclone), 50 mM 2-mercaptoethanol, antibiotics [penicillin G (100 IU/ml) and streptomycin sulfate (100 IU/ml); Invitrogen], and 30% L cell–conditioned medium, as described (73).

For testing of compounds, RAW264.7 cells were seeded in complete RPMI 1640 (without phenol red) medium in 96-well plates at a cell density of 50,000 per well at least 12 hours before stimulation. Cells were treated with compounds in dose-response settings (50 to 0.023 μM in threefold dilutions) or DMSO for 30 min, followed by stimulation with various physiological TLR agonists at predetermined, roughly equieffective concentrations [CpG DNA (1 μM), R848 (300 nM), Pam3Cys (100 ng/ml), LPS (10 ng/ml)] or Curdlan (100 μg/ml). TNFα concentrations were determined in cell culture supernatants 6 hours after stimulation by ELISA, and cell viability was analyzed by the Alamar blue assay system (Invitrogen).

Replication-deficient lentivirus and MSCV were generated on the basis of Lipofectamine 2000 (Invitrogen)–based transient transfection of HEK293T cells using a four-plasmid system that was generously provided by I. Verma (for lentivirus), or an ecotropic, MSCV-based two-plasmid system. Cas9-mediated deletion of MyD88 was performed by lentiviral delivery of MyD88-specific sgRNA (genomic target sequence: GTTCTTGAACGTGCGGACAC) that was expressed by the lentiviral vector LentiCRISPR v2 provided through Addgene (74). Transduced cells were selected with puromycin (10 μg/ml) and used as polyclonal cell population.

Bioactive compound library

The St. Jude “bioactive” compound library used in this study consisted of 4364 unique compounds (a total of 8904 compounds including replicates) acquired from commercial sources (Microsource, Prestwick, and Sigma-Aldrich) and external academic collaborators or synthesized in-house by our chemistry group. It includes FDA-approved drugs or clinical candidates (913), nuclear hormone receptor ligands (108), the GSK published kinase toolset (358), kinase inhibitors (1,642), nuclear hormone receptor–based pharmacophore library (744), artemisinin-like compounds (535), certain rare chemical scaffolds (1665), and some other chemicals with reported biological activities (2939). The purity of purchased and in-house prepared chemicals was >85% and >90%, respectively. All chemicals were solubilized in DMSO at a stock concentration of 10 mM.

High-throughput screening

The TIRAP-GyrB, MyD88-GyrB, and TRAF6-GyrB cell lines were stored in multiple aliquots as frozen stocks and thawed for HTS in a standardized manner 10 days (five passages) before HTS. Phenol red–containing standard DMEM was replaced by growth medium without phenol red during HTS assays. The concentration of FBS was not optimized toward lower concentrations because all follow-up experiments had been established at 10%. In the primary HTS, TIRAP-GyrB cells (10,000 cells in 25 μl of assay medium) were seeded in white 384-well solid-bottom tissue culture–treated plates (PerkinElmer) with a WellMate dispenser (Thermo Scientific Matrix), and plates were incubated in an automated tissue culture incubator (LiCONiC Instruments). After 24 hours, DMSO stock solutions of test chemicals (the St. Jude Bioactive collection), along with coumermycin A1 (Sigma-Aldrich), PS-1145 (Sigma-Aldrich), staurosporine (LC Laboratories), or DMSO (Thermo Fisher Scientific), were transferred with a Pin Tool (V&P Scientific) equipped with a 10H pin head to give a final test chemical concentration of 12 μM, along with 100 nM coumermycin A1 (one replicate per compound). In addition, groups of wells with 100 nM coumermycin A1 alone and 100 nM coumermycin A1 with 30 μM PS-1145 or 40 μM staurosporine were included in each plate as well. The final DMSO concentration in each well was 0.24%. Twenty-four hours later, each plate was treated with 5 μl per well Dulbecco’s phosphate-buffered saline (DPBS) (Thermo Fisher Scientific)–diluted (1:12 dilution) AlamarBlue (Invitrogen), incubated at 37°C for 1 hour, cooled down to room temperature for 15 min, followed by fluorescence analysis using an Envision HTS microplate reader (PerkinElmer). Next, the luminescence signals were measured using SteadyLite HTS luminescence assay reagent (PerkinElmer) and the Envision plate reader. In the AlamarBlue cell toxicity assay, the 40 μM staurosporine with 100 nM coumermycin A1 group and the 100 nM coumermycin A1 alone group were assigned as the positive (100% inhibition) and negative (0% inhibition) controls, respectively. In the luminescence assay, the 30 μM PS-1145 with 100 nM coumermycin A1 group and the 100 nM coumermycin A1 alone group were assigned as the corresponding positive (100% inhibition) and negative (0% inhibition) controls. Test compound activity was normalized to those of positive and negative controls in the individual assays. Two hundred thirteen unique chemicals with luminescence inhibitory activity ≥50% and with AlamarBlue cytotoxic inhibitory activity ≤20% were selected for further dose-response confirmation testing.

In the dose confirmation tests, the basic primary screening protocol was followed with minor modifications, including that 10 concentrations from 56 μM to 2.8 nM, along with 100 nM coumermycin A1 in triplicates, were tested. The activity data for individual chemicals were fit into sigmoidal dose-response curves if applicable to derive IC50 values with GraphPad Prism 7.00 (GraphPad Software).

Calculation Z′ values

The Z′ values were calculated using the equation Z=13σ++3σMean+Mean (79). σ+ is the SD of the negative control group (negative control groups in the luciferase reporter assay and AlamarBlue cytotoxicity assay for each cell line as defined above), σ is the SD of the positive control group (positive control groups in the luciferase reporter assay and AlamarBlue cytotoxicity assay for each cell line as defined above), Mean+ is the mean of the negative control group, and Mean is the mean of the positive control group.

Affinity purification and quantitative MS

For SILAC, RAW264.7 cells expressing stably a FLAG-tagged form of MyD88-GyrB were cultured in arginine- and lysine-free RPMI 1640 (Invitrogen) supplemented with 10% dialyzed fetal bovine serum (Invitrogen), penicillin-streptomycin, and either l-arginine and l-lysine (light), l-arginine-HCl [13C6; CLM-2265 (R6)], and l-lysine-2HCl [4,4,5,5 D4; DLM-2640 (K4)] (medium), or l-arginine-HCl [13C6, 15N4; CLM-539 (R10)] and l-lysine-2HCl [13C6, 15N2; DLM-291 (K8)] (heavy) (Cambridge Isotope Laboratories) (75). For complete incorporation of labeled amino acids, cells were passaged three times in SILAC medium over a period of 5 days. The labeled cells were treated with 10 μM MPP for 20 min (heavy), followed by stimulation with 1 μM CpG-DNA for 60 min (medium and heavy). The medium was replaced by ice-cold phosphate-buffered saline (PBS), and cells were collected by cell scraping and centrifugation. Cell pellets were incubated with lysis buffer [LB; 20 mM Hepes/NaOH (pH 7.5), 1.5 mM MgCl2, 150 mM NaCl, 1 mM EDTA, 10% glycerol, 10 mM β-glycerophosphate, 5 mM 4-nitrophenyl-phosphate, 10 mM sodium fluoride, and complete protease inhibitors (Roche)] supplemented with 0.5 % NP-40 for 20 min. Samples were cleared by centrifugation and loaded five times over M2 FLAG-bead–containing columns. Unbound proteins were removed by washing column with LB plus 0.1% NP-40, and proteins were eluted at pH 3.5 in water supplemented with 100 mM glycine, 50 mM NaCl, 0.1% NP-40, and Roche complete protease inhibitors. The proteins were concentrated by trichloroacetic acid precipitation and dissolved in SDS–polyacrylamide gel electrophoresis (PAGE) loading buffer (Bio-Rad). The dissolved proteins were combined, followed by separation on a 10 % Bis-Tris gel (Bio-Rad) and staining with SYPRO Ruby protein stain (Invitrogen). The entire lane was cut into individual bands and analyzed by LC-MS/MS using a nanoACQUITY ultra-performance liquid chromatography (UPLC) (Waters) coupled to an Orbitrap Elite high-resolution mass spectrometer (Thermo Fisher Scientific).

Sample preparation and LC-coupled electrospray ionization

The protein gel bands were reduced with dithiothreitol and alkylated with iodoacetamide and then digested overnight with trypsin (Promega). The digest was introduced into the instrument by on-line chromatography using reversed-phase (C18) ultrahigh-pressure LC on a nanoACQUITY UPLC (Waters). The column used was a Waters BEHC18 with an inner diameter of 75 μm and a bed length of 10 cm. The particle size was 1.7 μm. Tryptic peptides were gradient-eluted over a gradient [0 to 70% B for 60 min and 70 to 100% B for 10 min, where B was 70% (v/v) acetonitrile, 0.2% formic acid] using a flow rate of 250 nl/min into the high-resolution Orbitrap Elite through a noncoated spray needle with voltage applied to the liquid junction.

MS/MS using a hybrid ion trap-orbitrap mass spectrometer (LTQ Orbitrap XL)

Data-dependent scanning was incorporated to select the 20 most abundant ions (one microscan per spectrum; precursor isolation width, 2.0 Da; 35% collision energy; 10-ms ion activation; 15-s dynamic exclusion duration; 5-s repeat duration; and a repeat count of 1 from a full-scan mass spectrum at 60,000 resolution for fragmentation by collision-activated dissociation). Database searches were performed using raw files in combination with Andromeda search engine that is part of the MaxQuant software (version 1.1.1.32) developed at the Max Planck Institute (76). The SwissProt 2012_08 (537,505 sequences; 190,795,142 residues) (taxonomy: Mus musculus (16,605 sequences) database was used for peptide and protein identification. MaxQuant was also used to quantitate peptides and proteins and to provide ratios generated in Excel format. Protein assignments were made on the basis of both MS and MS/MS spectra, whereas peptide quantitation was based solely on MS data. The following residue modifications were allowed in the search: carbamidomethylation on cysteine (fixed modification), oxidation on methionine (variable modification), label:13C(6) on arginine, label:13C(10) on arginine, label:13C(4) on lysine, and label:13C(8) on lysine. The MS1 mass tolerance was set to 15 parts per million, the MS/MS tolerance was set to 0.5 Da, and protein false discovery rate (FDR) was set to 0.01. The identifications from the automated search were verified by manual inspection of the raw data.

Immunoprecipitation

IP studies were performed in HEK293T cells that were transfected using Lipofectamine 2000 (Life Technologies) with epitope-tagged forms of MyD88. MPP or DMSO was added 7 hours after transfection. Twenty hours after transfection, cells were lyzed for 20 min at 4°C in LB [20 mM Hepes/NaOH (pH 7.5), 1.5 mM MgCl2, 150 mM NaCl, 1 mM EDTA, 0.5% NP-40, and 10% glycerol) supplemented with complete protease inhibitors (Roche Applied Science). After clearance of lysates by centrifugation (10 min, 20,817g, 4°C), lysates were subjected to IP using FLAG M2 resin (Sigma-Aldrich) for 1 hour at 4°C. IP samples and total cell lysates were analyzed by immunoblotting.

Cellular thermal shift assay

CETSA was performed as described (78). Briefly, HEK293T cells were treated with TSI-13-57 or DMSO as control at 37°C with 5% CO2 for 60 min in cell culture dishes. Cells were resuspended in medium and spun down at 240g for 5 min at room temperature. Medium was carefully removed, and cells were resuspended in PBS. Cells were spun down again at 240g for 5 min at room temperature. PBS was carefully removed, and the cell pellet was resuspended in PBS supplemented with protease inhibitors to obtain a cell density of 8 × 106 cells/ml. The cell suspension (0.8 million in 100 μl of volume) was transferred to multiple tubes in a real-time polymerase chain reaction (PCR) plate (Applied Biosystems). The PCR plate was loaded to the heating block of a PTC-200 Gradient Thermocycler (MJ Research) at 25°C. Samples were heated to their desired temperatures in parallel by applying a temperature gradient covering a range between 40° and 64°C. The respective temperatures were maintained for 3 min before the samples were cooled and maintained at 25°C for 3 min. Next, the tubes were immediately shock-frozen in liquid nitrogen. Cells were lysed by two alternating thaw-freeze cycles in a heating block (25°C) and in liquid nitrogen, respectively. The resulting suspensions were centrifuged at 20,000g for 20 min at 4°C. For the following steps the lysates were kept on ice. Supernatants of each sample were carefully transferred to reaction tubes without touching or disturbing the pellets and were analyzed by SDS-PAGE, followed by immunoblot analysis.

Chemical synthesis, compound identity, and purity

A full description of synthetic routes and details of methods, compound purity, and spectroscopic characterization are provided in the Supplementary Materials. The purity of all compounds tested for biological activity was >95%, established by 1H nuclear magnetic resonance spectroscopy at high concentrations.

ER binding assay

Competitive radiometric binding assays were performed on 96-well microtiter filter plates (Millipore), using full-length human ERα and ERβ, with tritiated estradiol as tracer, as previously described (77). After incubation on ice for 18 to 24 hours, ERα-bound tracer was absorbed onto hydroxyapatite (Bio-Rad), washed with buffer, and measured by scintillation counting. RBA values are the average ± SD of two to three determinations, unless determined to be <1/1000 of estradiol (RBA values, <0.1), and then one experiment was performed.

M2H assay

Plasmids used for the M2H assays were based on the CheckMate mammalian two-hybrid system (Promega). The TIR domain of mouse MyD88 (amino acids 158 to 296) was cloned into the Gal4 vector (pBIND) and VP16 vector (pACT), full-length mouse MyD88 was cloned into pACT, the TIR domain of mouse TLR9 (amino acids 867 to 1032) was cloned into pBind, and mouse TIRAP (amino acids 1 to 241) was cloned into pBind. HEK293T cells were transiently transfected with bait and prey plasmids in 96-well format using Lipofectamine 2000, along with a Gal4-driven firefly luciferase reporter plasmid (pGL5-luc, Promega) and Renilla luciferase control vector (Promega). DMSO or compound was added to cells 7 hours after transfection. Cells were harvested 13 hours later, and luciferase activity was determined using the dual-luciferase kit (Promega). Firefly luciferase activity values were normalized to Renilla luciferase activity.

In vitro analysis of ADMET

Solubility assays were carried out on a Biomek FX lab automation workstation (Beckman Coulter Inc.) using μSOL Evolution software (pION Inc.). Compound stock (16.7 μM) (in DMSO) was used to make the reference plate. Compound stock (0.1 mM) was used in storage plate and incubated at room temperature for 18 hours. The suspension was then filtered through a 96-well filter plate (pION Inc.), diluted with 1-propanol to make the sample plate, and the ultraviolet (UV) spectrum of the reference and sample plate was read. Calculations were carried out with μSOL Evolution software based on the area under the curve (AUC) of the UV spectrum of the sample and reference plates. All compounds were tested in triplicate. For analysis of permeability, a parallel artificial membrane permeability assay (PAMPA) was conducted with the same instrument using PAMPA Evolution 96 Command software (pION Inc.). Compound stock (50 μM) was used to make the reference plate, and the UV spectrum of this plate was read. Gastrointestinal tract (GIT) lipid (pION Inc.) was used as the membrane on the preloaded PAMPA Sandwich (pION Inc.). The acceptor and donor chamber of the sandwich was then filled with 200 μl of acceptor solution buffer (pION Inc.) and test compound. The PAMPA Sandwich was assembled, placed on the Gut-Box, and stirred for 30 min. Then, the UV spectrum of the donor and the acceptor was read. The permeability coefficient was calculated on the basis of the AUC of the reference plate, the donor plate, and the acceptor plate. All compounds were tested in triplicate. Cytotoxicity studies were based on BJ (human foreskin fibroblasts), HEK293 (HEK cells), HepG2 (human hepatocellular carcinoma cells), and Raji (human lymphoblast cells; Burkitt’s lymphoma) cell lines [American Type Culture Collection (ATCC)], which were cultured according to recommendations and cell culture media from ATCC. Exponentially growing cells were plated in 384-well white custom assay plates (Corning) and incubated overnight at 37°C in a humidified 5% CO2 incubator. DMSO inhibitor stock solutions were added the following day to a top final concentration of 25 μM of 0.25% DMSO and then diluted 1:3 for a total of 10 testing concentrations. Cytotoxicity was determined after 72 hours of incubation using Cell Titer Glo Reagent (Promega), according to the manufacturer’s recommendation. Luminescence was measured on an Envision plate reader (PerkinElmer).

Compound stability was assessed using mouse liver microsomes (microsomes, 20 mg/ml) in potassium phosphate buffer (0.1 M, pH 7.4). Compound stocks (10 mM) in DMSO were diluted with DMSO and acetonitrile to three different intermediate concentrations. Only one concentration of controls (diphenhydramine HCl, verapamil HCl, and ketoprofen) was used. Each diluted compound stock (37.83 μl) was added to an aliquot of the liver microsomal solution (3 ml), vortexed, and transferred to five 96-well assay plates. A single assay plate was tested at each time point: 0, 0.5, 1, 2, and 4 hours. For the 0-hour time point, precooled (4°C) internal standard (2 μM warfarin in methanol) was added to the plate before the reaction starts. For other time points, NADPH solution (Thermo Fisher Scientific) was added first. The plates were sealed, and all plates except the 0-hour plate were incubated at 37°C, shaken at a speed of 60 rpm. At each time point, 437.5 μl of precooled internal standard was added to quench the reaction. The final compound concentrations were 20, 4, and 0. 8 μM. The centration of controls was 4 μM. The quenched plate was then centrifuged at 4000 rpm for 15 min at 4°C. The resulting supernatant was transferred to a 96-well plate and analyzed by UPLC-MS (Waters Inc.). The compounds and internal standard were detected by selected ion recording. The amount of material was measured as a ratio of peak area to the internal standard and graphed. Using the slope from the most linear portion of this curve, the degradation rate constant is calculated. The rate constant was then used to calculate the compounds half-life in plasma. Intrinsic clearance was calculated as CLint′ = (0.693/(t1/2)) × (1/microsomal concentration in the reaction solution) × (45 mg of microsome/gram liver) × (gram liver/kg body weight), where microsomal concentration in the reaction solution is 0.5 mg/ml and gram liver/kg body weight of mouse is 52.

In vivo pharmacokinetic study

Female C57BL/6 mice with average weight of 19 g were purchased from Charles River Laboratories. Food and water were provided ad libitum. Fifteen mice were divided into three dosage groups: 0, 10, and 20 mg/kg. For each mouse, 0.1 ml of compound suspension in formulation (0.5% O-carboxymethylcellulose and 0.4% Tween 80) was given by intraperitoneal injection. Blood (0.1 ml) was collected retroorbitally from a different mouse within each dosage group at 5 min, 15 min, 30 min, 1 hour, 4 hours, and 24 hours. Animals were euthanized by cardiac puncture at 48 hours after injection. Blood samples were treated with 10 μl of EDTA sodium solution to prevent coagulation. Blood was kept on ice and centrifuged for 3 min at 13,000 rpm in a desktop centrifuge to collect plasma. Twenty-five microliters of plasma samples were combined with 75 μl of internal standard (2 μM warfarin) in acetonitrile in a 96-well plate and centrifuged at 4000 rpm for 20 min at 4°C. The supernatant (40 μl) was collected, mixed with two parts of Milli-Q water (EMD Millipore), and centrifuged again at 3000 rpm for 20 min at 4°C. Plasma concentration was determined with partially validated LC/MS-MS assay with multiple reaction monitoring (MRM) detection (AB Sciex). The assay limit of quantification (LLOQ) was 1.5 nM in plasma. The processed plasma concentration–time data were analyzed using noncompartmental analysis in WinNonlin 6.0 with the plasma (200-202) model type.

The area under the concentration-time curve was calculated with the linear trapezoidal, linear interpolation rule using mean concentrations and nominal times. The terminal elimination rate (Lambda_z) and half-life (HL_Lambda_z) were determined using the default “Best Fit” method. The predicted AUC from the last time point to infinity (AUCINF_pred) was calculated as AUClast plus Clast(pred)/Lambda_z.

In vivo LPS challenge model

Female C57BL/6J mice (The Jackson Laboratory) were treated intraperitoneally with TSI-13-57 formulated in 5% N-methyl-2-pyrrolidone (NMP), 5% Solutol HS 15, 90% normal saline, or vehicle control. Sixty minutes later, the mice were intraperitoneally administered with LPS (2500 ng/kg body weight) in PBS. Ninety minutes later, mice were bled, and plasma TNFα concentrations were analyzed by ELISA (eBioscience).

Statistics

Statistical analyses were performed using GraphPad Prism 7 software. Pairwise comparisons were analyzed with the Mann-Whitney U test or paired t test (two-tailed). Multiple comparisons were analyzed by one-way or two-way ANOVA, followed by posttests.

SUPPLEMENTARY MATERIALS

www.sciencesignaling.org/cgi/content/full/11/543/eaaq1077/DC1

Fig. S1. DMSO tolerance of reporter cell lines during stimulation.

Fig. S2. Z′ values of the HEK293T cell–based screening system.

Table S1. Complementary data for Table 1.

Table S2. Complementary data for Table 2.

Methods

References (8082)

REFERENCES AND NOTES

Acknowledgments: We acknowledge the staff of the Animal Resource Center at the St. Jude Children’s Research Hospital and the Centers of the Department of Chemical Biology and Therapeutics. We also thank L. Tang and Y. Sun (St. Jude Children’s Research Hospital) for support with statistical analyses, and R. Wu for technical contributions. Funding: This work was supported by the NIH (PHS 5R01 DK015556 to J.A.K. and T32ES007326 to J.A.P.), the St. Jude Children’s Infection Defense Center, and the American Lebanese Syrian Associated Charities. Author contributions: H.H. conceived and coordinated the project. H.H., J.A.K., and J.A.P. developed the project and wrote the manuscript. S.K.I., J.A.P., N.S., K.T., Y.C., and H.H. performed the experiments, and S.K.I., J.A.P., N.S., W.L., T.C., A.A.H., Y.C., J.M., R.K.G., V.R., J.A.K., and H.H. analyzed and discussed the data. W.L. and T.C. performed the HTS. A.A.H. performed the MS. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper or the Supplementary Materials.
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