Integrated Proteomics Characterization of NLRP3 Inflammasome Inhibitor MCC950 in Monocytic Cell Line Confirms Direct MCC950 Engagement with Endogenous NLRP3

Inhibition of the NLRP3 inflammasome is a promising strategy for the development of new treatments for inflammatory diseases. MCC950 is a potent and selective small-molecule inhibitor of the NLRP3 pathway and has been validated in numerous species and disease models. Although the capacity of MCC950 to block NLRP3 signaling is well-established, it is still critical to identify the mechanism of action and molecular targets of MCC950 to inform and derisk drug development. Quantitative proteomics performed in disease-relevant systems provides a powerful method to study both direct and indirect pharmacological responses to small molecules to elucidate the mechanism of action and confirm target engagement. A comprehensive target deconvolution campaign requires the use of complementary chemical biology techniques. Here we applied two orthogonal chemical biology techniques: compressed Cellular Thermal Shift Assay (CETSA) and photoaffinity labeling chemoproteomics, performed under biologically relevant conditions with LPS-primed THP-1 cells, thereby deconvoluting, for the first time, the molecular targets of MCC950 using chemical biology techniques. In-cell chemoproteomics with inlysate CETSA confirmed the suspected mechanism as the disruption of inflammasome formation via NLRP3. Further cCETSA (c indicates compressed) in live cells mapped the stabilization of NLRP3 inflammasome pathway proteins, highlighting modulation of the targeted pathway. This is the first evidence of direct MCC950 engagement with endogenous NLRP3 in a human macrophage cellular system using discovery proteomics chemical biology techniques, providing critical information for inflammasome studies.

Direct activation of KCC2 arrests benzodiazepine refractory status epilepticus and limits the subsequent neuronal injury in mice

Hyperpolarizing GABA_AR currents, the unitary events that underlie synaptic inhibition, are dependent upon efficient Cl^- extrusion, a process that is facilitated by the neuronal specific K⁺/Cl^- co-transporter KCC2. Its activity is also a determinant of the anticonvulsant efficacy of the canonical GABA_AR-positive allosteric: benzodiazepines (BDZs). Compromised KCC2 activity is implicated in the pathophysiology of status epilepticus (SE), a medical emergency that rapidly becomes refractory to BDZ (BDZ-RSE). Here, we have identified small molecules that directly bind to and activate KCC2, which leads to reduced neuronal Cl^- accumulation and excitability. KCC2 activation does not induce any overt effects on behavior but prevents the development of and terminates ongoing BDZ-RSE. In addition, KCC2 activation reduces neuronal cell death following BDZ-RSE. Collectively, these findings demonstrate that KCC2 activation is a promising strategy to terminate BDZ-resistant seizures and limit the associated neuronal injury.

Chemical Biology Approaches Confirm MCT4 as the Therapeutic Target of a Cellular Optimized Hit

Lactic acid transport is a key process maintaining glycolytic flux in tumors. Inhibition of this process will result in glycolytic shutdown, impacting on cell growth and survival and thus has been pursued as a therapeutic approach for cancers. Using a cell-based screen in a MCT4-dependent cell line, we identified and optimized compounds for their ability to inhibit the efflux of intracellular lactic acid with good physical and pharmacokinetic properties. To deconvolute the mechanism of lactic acid efflux inhibition, we have developed three assays to measure cellular target engagement. Specifically, we synthesized a biologically active photoaffinity probe (IC₅₀ < 10 nM), and using this probe, we demonstrated selective engagement of MCT4 of our parent molecule through a combination of confocal microscopy and in-cell chemoproteomics. As an orthogonal assay, the cellular thermal shift assay (CETSA) confirmed binding to MCT4 in the cellular system. Comparisons of lactic acid efflux potencies in cells with differential expression of MCT family members further confirmed that the optimized compounds inhibit the efflux of lactic acid through the inhibition of MCT4. Taken together, these data demonstrate the power of orthogonal chemical biology methods to determine cellular target engagement, particularly for proteins not readily amenable to traditional biophysical methods.

Discovery of Clinical Candidate AZD0095, a Selective Inhibitor of Monocarboxylate Transporter 4 (MCT4) for Oncology

Due to increased reliance on glycolysis, which produces lactate, monocarboxylate transporters (MCTs) are often upregulated in cancer. MCT4 is associated with the export of lactic acid from cancer cells under hypoxia, so inhibition of MCT4 may lead to cytotoxic levels of intracellular lactate. In addition, tumor-derived lactate is known to be immunosuppressive, so MCT4 inhibition may be of interest for immuno-oncology. At the outset, no potent and selective MCT4 inhibitors had been reported, but a screen identified a triazolopyrimidine hit, with no close structural analogues. Minor modifications to the triazolopyrimidine were made, alongside design of a constrained linker and broad SAR exploration of the biaryl tail to improve potency, physical properties, PK, and hERG. The resulting clinical candidate 15 (AZD0095) has excellent potency (1.3 nM), MCT1 selectivity (>1000×), secondary pharmacology, clean mechanism of action, suitable properties for oral administration in the clinic, and good preclinical efficacy in combination with cediranib.

POS0966 DEVELOPMENT AND VALIDATION OF AN ANKYLOSING SPONDYLITIS RISK PREDICTION MODEL USING LONGITUDINAL REAL-WORLD DATA FROM A LARGE INTEGRATED HEALTHCARE DELIVERY SYSTEM

Background

Early detection and diagnosis of Ankylosing spondylitis (AS) is challenging due to heterogeneity in disease presentation, lack of specific biomarkers and high prevalence of mechanical back-pain that is difficult to distinguish from inflammatory back-pain. However, if diagnosed and treated early, the risk of AS complications and disease progression can be slowed.

Objectives

To develop and validate a risk prediction model for early identification of patients at high risk of AS, using a large longitudinal real-world clinical data in the US.

Methods

This retrospective study included all members aged ≥ 21 years with back pain symptoms who were enrolled in the Kaiser Permanente Southern California health plan between 01/2009-12/2013. Patients who presented with back pain symptoms at a physician visit were followed until 12/2020 to see if they subsequently developed AS. The cohort was randomly divided into a training (60%) and a validation (40%) sample. A proportional odds model was specified to create a risk score for AS in the training sample. Best fit model was determined based on Area Under the Curve (AUC) and Akaike Information Criterion (AIC). The cut off threshold of “high-risk” was based on Youden’s (1950) index.1 We assessed the model performance for internal validity using split-samples. The model was further validated using manual chart review of 900 patient records. These 900 records were selected such that 70% (N=630) met the high-risk cut-off and the remainder had scores below the cut-off. We also derived the probability of AS in each chart reviewed case using the method proposed by Feldtkeller et al. (2013) and Rudwaleit et al. (2006).2,3

Results

The cohort comprised 527,509 members with mean age 54 years and majority female (58%). Sixty-six percent were White race and 33% were Hispanic ethnicity. The crude incidence of AS was 1% and increased steadily during the follow-up period (Figure 1). The final risk prediction model included 15 risk factors and had an AUC of 0.72 (Table 1). Using Youden’s index, a cut-off value of 11 or higher was identified as the threshold to define high-risk. No evidence of overfitting to our training sample was observed based on the split-sample analysis. The model validation based on manual chart review of 900 records showed sufficient ability to discriminate between those at high-risk vs those not identified to be high-risk. When a concrete rule out or rule in determination could be made using Feldtkeller et al. approach, our model correctly classified 75% of such records.

Table 1.

Final Model Coefficients and Derived Risk Score

Model CoefficientPr(>|z|)Risk ScoreAge above 45 years0.1460.0111.46Male Sex-0.292<0.001-2.92White Race0.259<0.0012.59Non-Hispanic Ethnicity0.177<0.0011.77Corticosteroid Use (Yes/No)0.235<0.0012.35*NSAID User (Yes/No)0.202<0.0012.02Opioid Analgesic User (Yes/No)0.416<0.0014.16Had Enthesitis (Yes/No)0.298<0.0012.98Had Disorders of the Back (Yes/No)0.973<0.0019.73Had Fatigue and/or Malaise (Yes/No)0.1550.0561.55Had Psoriasis (Yes/No)0.2880.0082.88Had Spondylosis (Yes/No)0.838<0.0018.38Had Synovitis (Yes/No)0.1430.0661.43Had Uveitis (Yes/No)0.6210.0076.21Depression Diagnosis (Yes/No)0.0990.0170.99

* NSAID: Non-steroidal anti-inflammatory drugs

Figure 1.

Cumulative Incidence Over Time (in Days)

Conclusion

To aid early detection, we have developed and validated an AS risk prediction model with an easy to implement scoring system using demographics, medication use and diagnosis data that is routinely collected in clinical practice.

References:

[1]Youden WJ. Index for rating diagnostic tests. Cancer. 1950;3(1):32-35.

[2]Feldtkeller E, Rudwaleit M, Zeidler H. Easy probability estimation of the diagnosis of early axial spondyloarthritis by summing up scores. Rheumatology (Oxford, England). 2013;52(9):1648-1650

[3]Rudwaleit M, Feldtkeller E, Sieper J. Easy assessment of axial spondyloarthritis (early ankylosing spondylitis) at the bedside. Ann Rheum Dis 2006;65:1251-2.

Disclosure of Interests

Aniket Kawatkar Grant/research support from: Novartis, Medac, Esther Yi Employee of: Novartis, Erika Estrada Grant/research support from: Novartis, Jose Pio Grant/research support from: Novartis, Cecilia Portugal Grant/research support from: Novartis, David Yi Grant/research support from: Novartis, Talar Habeshian Grant/research support from: Novartis, David Wei Employee of: Novartis, Steven Lee Grant/research support from: Novartis

CETSA beyond Soluble Targets: a Broad Application to Multipass Transmembrane Proteins

Demonstration of target binding is a key requirement for understanding the mode of action of new therapeutics. The cellular thermal shift assay (CETSA) has been introduced as a powerful label-free method to assess target engagement in physiological environments. Here, we present the application of live-cell CETSA to different classes of integral multipass transmembrane proteins using three case studies, the first showing a large and robust stabilization of the outer mitochondrial five-pass transmembrane protein TSPO, the second being a modest stabilization of SERCA2, and the last describing an atypical compound-driven stabilization of the GPCR PAR2. Our data demonstrated that using modified protocols with detergent extraction after the heating step, CETSA can reliably be applied to several membrane proteins of different complexity. By showing examples with distinct CETSA behaviors, we aim to provide the scientific community with an overview of different scenarios to expect during CETSA experiments, especially for challenging, membrane bound targets.

CETSA beyond Soluble Targets: a Broad Application to Multipass Transmembrane Proteins

Demonstration of target binding is a key requirement for understanding the mode of action of new therapeutics. The cellular thermal shift assay (CETSA) has been introduced as a powerful label-free method to assess target engagement in physiological environments. Here, we present the application of live-cell CETSA to different classes of integral multipass transmembrane proteins using three case studies, the first showing a large and robust stabilization of the outer mitochondrial five-pass transmembrane protein TSPO, the second being a modest stabilization of SERCA2, and the last describing an atypical compound-driven stabilization of the GPCR PAR2. Our data demonstrated that using modified protocols with detergent extraction after the heating step, CETSA can reliably be applied to several membrane proteins of different complexity. By showing examples with distinct CETSA behaviors, we aim to provide the scientific community with an overview of different scenarios to expect during CETSA experiments, especially for challenging, membrane bound targets.

Target Deconvolution Efforts on Wnt Pathway Screen Reveal Dual Modulation of Oxidative Phosphorylation and SERCA2

Wnt signaling is critical for development, cell proliferation and differentiation, and mutations in this pathway resulting in constitutive signaling have been implicated in various cancers. A pathway screen using a Wnt-dependent reporter identified a chemical series based on a 1,2,3-thiadiazole-5-carboxamide (TDZ) core with sub-micromolar potency. Herein we report a comprehensive mechanism-of-action deconvolution study toward identifying the efficacy target(s) and biological implication of this chemical series involving bottom-up quantitative chemoproteomics, cell biology, and biochemical methods. Through observing the effects of our probes on metabolism and performing confirmatory cellular and biochemical assays, we found that this chemical series inhibits ATP synthesis by uncoupling the mitochondrial potential. Affinity chemoproteomics experiments identified sarco(endo)plasmic reticulum Ca²⁺ -dependent ATPase (SERCA2) as a binding partner of the TDZ series, and subsequent validation studies suggest that the TDZ series can act as ionophores through SERCA2 toward Wnt pathway inhibition.

Identification of azabenzimidazoles as potent JAK1 selective inhibitors

We have identified a class of azabenzimidazoles as potent and selective JAK1 inhibitors. Investigations into the SAR are presented along with the structural features required to achieve selectivity for JAK1 versus other JAK family members. An example from the series demonstrated highly selective inhibition of JAK1 versus JAK2 and JAK3, along with inhibition of pSTAT3 in vivo, enabling it to serve as a JAK1 selective tool compound to further probe the biology of JAK1 selective inhibitors.