Indazole-based ligands for estrogen-related receptor α as potential anti-diabetic agents

In Silico Prediction of ERRα Agonists Based on Combined Features and Stacking Ensemble Method

Estrogen-related receptor α (ERRα) is considered a very promising target for treating metabolic diseases such as type 2 diabetes. Development of a prediction model to quickly identify potential ERRα agonists can significantly reduce the time spent on virtual screening. In this study, 298 ERRα agonists and numerous nonagonists were collected from various sources to build a new dataset of ERRα agonists. Then a total of 90 models were built using a combination of different algorithms, molecular characterization methods, and data sampling techniques. The consensus model with optimal performance was also validated on the test set (AUC=0.876, BA=0.816) and external validation set (AUC=0.867, BA=0.777) based on five selected baseline models. Furthermore, the model's applicability domain and privileged substructures were examined, and the feature importance was analyzed using the SHAP method to help interpret the model. Based on the above, it's hoped that our publicly accessible data, models, codes, and analytical techniques will prove valuable in quick screening and rational designing more novel and potent ERRα agonists.

Crosstalk interactions between transcription factors ERRα and PPARα assist PPARα-mediated gene expression

OBJECTIVE

The peroxisome proliferator-activated receptor α (PPARα) is a transcription factor driving target genes involved in fatty acid β-oxidation. To what extent various PPARα interacting proteins may assist its function as a transcription factor is incompletely understood. An ORFeome-wide unbiased mammalian protein-protein interaction trap (MAPPIT) using PPARα as bait revealed a PPARα-ligand-dependent interaction with the orphan nuclear receptor estrogen-related receptor α (ERRα). The goal of this study was to characterize the nature of the interaction in depth and to explore whether it was of physiological relevance.

METHODS

We used orthogonal protein-protein interaction assays and pharmacological inhibitors of ERRα in various systems to confirm a functional interaction and study the impact of crosstalk mechanisms. To characterize the interaction surfaces and contact points we applied a random mutagenesis screen and structural overlays. We pinpointed the extent of reciprocal ligand effects of both nuclear receptors via coregulator peptide recruitment assays. On PPARα targets revealed from a genome-wide transcriptome analysis, we performed an ERRα chromatin immunoprecipitation analysis on both fast and fed mouse livers.

RESULTS

Random mutagenesis scanning of PPARα's ligand-binding domain and coregulator profiling experiments supported the involvement of (a) bridging coregulator(s), while recapitulation of the interaction in vitro indicated the possibility of a trimeric interaction with RXRα. The PPARα·ERRα interaction depends on 3 C-terminal residues within helix 12 of ERRα and is strengthened by both PGC1α and serum deprivation. Pharmacological inhibition of ERRα decreased the interaction of ERRα to ligand-activated PPARα and revealed a transcriptome in line with enhanced mRNA expression of prototypical PPARα target genes, suggesting a role for ERRα as a transcriptional repressor. Strikingly, on other PPARα targets, including the isolated PDK4 enhancer, ERRα behaved oppositely. Chromatin immunoprecipitation analyses demonstrate a PPARα ligand-dependent ERRα recruitment onto chromatin at PPARα-binding regions, which is lost following ERRα inhibition in fed mouse livers.

CONCLUSIONS

Our data support the coexistence of multiple layers of transcriptional crosstalk mechanisms between PPARα and ERRα, which may serve to finetune the activity of PPARα as a nutrient-sensing transcription factor.

A reduced proteomic signature in critically ill Covid-19 patients determined with plasma antibody micro-array and machine learning

BACKGROUND

COVID-19 is a complex, multi-system disease with varying severity and symptoms. Identifying changes in critically ill COVID-19 patients' proteomes enables a better understanding of markers associated with susceptibility, symptoms, and treatment. We performed plasma antibody microarray and machine learning analyses to identify novel proteins of COVID-19.

METHODS

A case-control study comparing the concentration of 2000 plasma proteins in age- and sex-matched COVID-19 inpatients, non-COVID-19 sepsis controls, and healthy control subjects. Machine learning was used to identify a unique proteome signature in COVID-19 patients. Protein expression was correlated with clinically relevant variables and analyzed for temporal changes over hospitalization days 1, 3, 7, and 10. Expert-curated protein expression information was analyzed with Natural language processing (NLP) to determine organ- and cell-specific expression.

RESULTS

Machine learning identified a 28-protein model that accurately differentiated COVID-19 patients from ICU non-COVID-19 patients (accuracy = 0.89, AUC = 1.00, F1 = 0.89) and healthy controls (accuracy = 0.89, AUC = 1.00, F1 = 0.88). An optimal nine-protein model (PF4V1, NUCB1, CrkL, SerpinD1, Fen1, GATA-4, ProSAAS, PARK7, and NET1) maintained high classification ability. Specific proteins correlated with hemoglobin, coagulation factors, hypertension, and high-flow nasal cannula intervention (P < 0.01). Time-course analysis of the 28 leading proteins demonstrated no significant temporal changes within the COVID-19 cohort. NLP analysis identified multi-system expression of the key proteins, with the digestive and nervous systems being the leading systems.

CONCLUSIONS

The plasma proteome of critically ill COVID-19 patients was distinguishable from that of non-COVID-19 sepsis controls and healthy control subjects. The leading 28 proteins and their subset of 9 proteins yielded accurate classification models and are expressed in multiple organ systems. The identified COVID-19 proteomic signature helps elucidate COVID-19 pathophysiology and may guide future COVID-19 treatment development.

A Synthetic ERR Agonist Alleviates Metabolic Syndrome

Physical exercise induces physiologic adaptations and is effective at reducing the risk of premature death from all causes. Pharmacological exercise mimetics may be effective in the treatment of a range of diseases including obesity and metabolic syndrome. Previously, we described the development of SLU-PP-332, an agonist for the estrogen-related receptor (ERR)α, β, and γ nuclear receptors that activates an acute aerobic exercise program. Here we examine the effects of this exercise mimetic in mouse models of obesity and metabolic syndrome. Diet-induced obese or ob/ob mice were administered SLU-PP-332, and the effects on a range of metabolic parameters were assessed. SLU-PP-332 administration mimics exercise-induced benefits on whole-body metabolism in mice including increased energy expenditure and fatty acid oxidation. These effects were accompanied by decreased fat mass accumulation. Additionally, the ERR agonist effectively reduced obesity and improved insulin sensitivity in models of metabolic syndrome. Pharmacological activation of ERR may be an effective method to treat metabolic syndrome and obesity. SIGNIFICANCE STATEMENT: An estrogen receptor-related orphan receptor agonist, SLU-PP-332, with exercise mimetic activity, holds promise as a therapeutic to treat metabolic diseases by decreasing fat mass in mouse models of obesity.

Hepatocyte FBXW7-dependent activity of nutrient-sensing nuclear receptors controls systemic energy homeostasis and NASH progression in male mice

Nonalcoholic steatohepatitis (NASH) is epidemiologically associated with obesity and diabetes and can lead to liver cirrhosis and hepatocellular carcinoma if left untreated. The intricate signaling pathways that orchestrate hepatocyte energy metabolism and cellular stress, intrahepatic cell crosstalk, as well as interplay between peripheral tissues remain elusive and are crucial for the development of anti-NASH therapies. Herein, we reveal E3 ligase FBXW7 as a key factor regulating hepatic catabolism, stress responses, systemic energy homeostasis, and NASH pathogenesis with attenuated FBXW7 expression as a feature of advanced NASH. Multiomics and pharmacological intervention showed that FBXW7 loss-of-function in hepatocytes disrupts a metabolic transcriptional axis conjointly controlled by the nutrient-sensing nuclear receptors ERRα and PPARα, resulting in suppression of fatty acid oxidation, elevated ER stress, apoptosis, immune infiltration, fibrogenesis, and ultimately NASH progression in male mice. These results provide the foundation for developing alternative strategies co-targeting ERRα and PPARα for the treatment of NASH.

Synthetic ERRα/β/γ Agonist Induces an ERRα-Dependent Acute Aerobic Exercise Response and Enhances Exercise Capacity

Repetitive physical exercise induces physiological adaptations in skeletal muscle that improves exercise performance and is effective for the prevention and treatment of several diseases. Genetic evidence indicates that the orphan nuclear receptors estrogen receptor-related receptors (ERRs) play an important role in skeletal muscle exercise capacity. Three ERR subtypes exist (ERRα, β, and γ), and although ERRβ/γ agonists have been designed, there have been significant difficulties in designing compounds with ERRα agonist activity. Additionally, there are limited synthetic agonists that can be used to target ERRs in vivo. Here, we report the identification of a synthetic ERR pan agonist, SLU-PP-332, that targets all three ERRs but has the highest potency for ERRα. Additionally, SLU-PP-332 has sufficient pharmacokinetic properties to be used as an in vivo chemical tool. SLU-PP-332 increases mitochondrial function and cellular respiration in a skeletal muscle cell line. When administered to mice, SLU-PP-332 increased the type IIa oxidative skeletal muscle fibers and enhanced exercise endurance. We also observed that SLU-PP-332 induced an ERRα-specific acute aerobic exercise genetic program, and the ERRα activation was critical for enhancing exercise endurance in mice. These data indicate the feasibility of targeting ERRα for the development of compounds that act as exercise mimetics that may be effective in the treatment of numerous metabolic disorders and to improve muscle function in the aging.

Synthesis, α-amylase and α-glucosidase inhibition and molecular docking studies of indazole derivatives

Herein, we report the synthesis and inhibitory potential of indazole (Methyl 1H-indazole-4-carboxylate) derivatives (1-13) against α-amylase and α-glucosidase enzymes. The described derivatives demonstrated good inhibitory potential with IC₅₀ values, ranging between 15.04 ± 0.05 to 76.70 ± 0.06 µM ± SEM for α-amylase and 16.99 ± 0.19 to 77.97 ± 0.19 µM ± SEM for α-glucosidase, respectively. In particular, compounds (8-10 and 12) displayed significant inhibitory activities against both the screened enzymes, with their inhibitory potential comparable to the standard acarbose (12.98 ± 0.03 and 12.79 ± 0.17 µM ± SEM, respectively). Additionally, the influence of different substituents on enzyme inhibition activities was assessed to study the structure activity relationships. Molecular docking simulations were performed to rationalize the binding of derivatives/compounds with enzymes. All the synthesized derivatives (1-13) were characterized with the aid of spectroscopic instruments such as ¹H-NMR, ¹³C-NMR, HR-MS, elemental analysis and FTIR.Communicated by Ramaswamy H. Sarma.

The discovery of a novel series of potential ERRα inverse agonists based on p-nitrobenzenesulfonamide template for triple-negative breast cancer in vivo

Oestrogen related receptor α participated in the regulation of oxidative metabolism and mitochondrial biogenesis, and was overexpressed in many cancers including triple-negative breast cancer. A set of new ERRα inverse agonists based on p-nitrobenzenesulfonamide template were discovered and compound 11 with high potent activity (IC50 = 0.80 μM) could significantly inhibit the transcription of ERRα-regulated target genes. By regulating the downstream signalling pathway, compound 11 could suppress the migration and invasion of the ER-negative MDA-MB-231 cell line. Furthermore, compound 11 demonstrated a significant growth suppression of breast cancer xenograft tumours in vivo (inhibition rate 23.58%). The docking results showed that compound 11 could form hydrogen bonds with Glu331 and Arg372 in addition to its hydrophobic interaction with ligand-binding domain. Our data implied that compound 11 represented a novel and effective ERRα inverse agonist, which had broad application prospects in the treatment of triple-negative breast cancer.

Role of HIF-1α/ERRα in Enhancing Cancer Cell Metabolism and Promoting Resistance of Endometrial Cancer Cells to Pyroptosis

Oxygen is critical to energy metabolism, and tumors are often characterized by a hypoxic microenvironment. Owing to the high metabolic energy demand of malignant tumor cells, their survival is promoted by metabolic reprogramming in the hypoxic microenvironment, which can confer tumor cell resistance to pyroptosis. Pyroptosis resistance can inhibit anti-tumor immunity and promote the development of malignant tumors. Hypoxia inducible factor-1α (HIF-1α) is a key regulator of metabolic reprogramming in tumor cells, and estrogen-related receptor α (ERRα) plays a key role in regulating cellular energy metabolism. Therefore, the close interaction between HIF-1α and ERRα influences the metabolic and functional changes in cancer cells. In this review, we summarize the reprogramming of tumor metabolism involving HIF-1α/ERRα. We review our understanding of the role of HIF-1α/ERRα in promoting tumor growth adaptation and pyroptosis resistance, emphasize its key role in energy homeostasis, and explore the regulation of HIF-1α/ERRα in preventing and/or treating endometrial carcinoma patients. This review provides a new perspective for the study of the molecular mechanisms of metabolic changes in tumor progression.

Emerging Role of Nuclear Receptors for the Treatment of NAFLD and NASH

Non-alcoholic fatty liver (NAFLD) over the past years has become a metabolic pandemic linked to a collection of metabolic diseases. The nuclear receptors ERRs, REV-ERBs, RORs, FXR, PPARs, and LXR are master regulators of metabolism and liver physiology. The characterization of these nuclear receptors and their biology has promoted the development of synthetic ligands. The possibility of targeting these receptors to treat NAFLD is promising, as several compounds including Cilofexor, thiazolidinediones, and Saroglitazar are currently undergoing clinical trials. This review focuses on the latest development of the pharmacology of these metabolic nuclear receptors and how they may be utilized to treat NAFLD and subsequent comorbidities.

Nuclear Mechanisms Involved in Endocrine Resistance

Endocrine therapy is a standard treatment offered to patients with ERα (estrogen receptor α)-positive breast cancer. In endocrine therapy, ERα is either directly targeted by anti-estrogens or indirectly by aromatase inhibitors which cause estrogen deficiency. Resistance to these drugs (endocrine resistance) compromises the efficiency of this treatment and requires additional measures. Endocrine resistance is often caused by deregulation of the PI3K/AKT/mTOR pathway and/or cyclin-dependent kinase 4 and 6 activities allowing inhibitors of these factors to be used clinically to counteract endocrine resistance. The nuclear mechanisms involved in endocrine resistance are beginning to emerge. Exploring these mechanisms may reveal additional druggable targets, which could help to further improve patients' outcome in an endocrine resistance setting. This review intends to summarize our current knowledge on the nuclear mechanisms linked to endocrine resistance.

Molecular Dynamics Simulations Based on 1-Phenyl-4-Benzoyl-1-Hydro-Triazole ERRα Inverse Agonists

Estrogen-related receptor α (ERRα), which is overexpressed in a variety of cancers has been considered as an effective target for anticancer therapy. ERRα inverse agonists have been proven to effectively inhibit the migration and invasion of cancer cells. As few crystalline complexes have been reported, molecular dynamics (MD) simulations were carried out in this study to deepen the understanding of the interaction mechanism between inverse agonists and ERRα. The binding free energy was analyzed by the MM-GBSA method. The results show that the total binding free energy was positively correlated with the biological activity of an inverse agonist. The interaction of the inverse agonist with the hydrophobic interlayer composed of Phe328 and Phe495 had an important impact on the biological activity of inverse agonists, which was confirmed by the decomposition of energy on residues. As Glu331 flipped and formed a hydrogen bond with Arg372 in the MD simulation process, the formation of hydrogen bond interaction with Glu331 was not a necessary condition for the compound to act as an inverse agonist. These rules provide guidance for the design of new inverse agonists.

Insights into the interaction mechanisms of estrogen-related receptor alpha (ERRα) with ligands via molecular dynamics simulations

Estrogen-related receptor alpha (ERRα), a member of nuclear receptors (NRs), participates in energy metabolism. Recent experiments identified that several agonists to increase the activity of ERRα, which have a therapeutic effect in improving insulin sensitivity and lowering blood glucose levels. However, the detailed molecular mechanism about how the ligands affect the structure of ERRα remains elusive. To better understand the conformational change of ERRα complexed with agonists and inverse agonists, unbiased molecular dynamics (MD) simulations were performed on the ligand binding domain of ERRα (ERRα-LBD) bound with different ligands. According to the results, the ERRα-agonist interactions were more stable in the presence of the peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α). More importantly, we observed that the binding of inverse agonists would decrease the stability of helix 12 (H12) of ERRα. Moreover, we suggested that Phe232 and Phe414 should be key residues in the interaction pathway from ligands to H12, which provided a possible explanation about how ligands impact the structure of ERRα. These results would provide insights into the design of novel and efficient agonists of ERRα to treat metabolic diabetes.Communicated by Ramaswamy H. Sarma.

Estrogen-Related Receptor Alpha: An Under-Appreciated Potential Target for the Treatment of Metabolic Diseases

The estrogen-related receptor alpha (ESRRA) is an orphan nuclear receptor (NR) that significantly influences cellular metabolism. ESRRA is predominantly expressed in metabolically-active tissues and regulates the transcription of metabolic genes, including those involved in mitochondrial turnover and autophagy. Although ESRRA activity is well-characterized in several types of cancer, recent reports suggest that it also has an important role in metabolic diseases. This minireview focuses on the regulation of cellular metabolism and function by ESRRA and its potential as a target for the treatment of metabolic disorders.

Identification of New Small-Molecule Inducers of Estrogen-related Receptor α (ERRα) Degradation

A series of (E)-3-(4-((2,4-bis(trifluoromethyl)benzyl)oxy)-3-methoxyphenyl)-2-cyanoacrylamide derivatives were designed and synthesized as new estrogen-related receptor α (ERRα) degraders based on the proteolysis targeting chimera (PROTAC) concept. One of the representative compounds 6c is capable of specifically degrading ERRα protein by >80% at a relatively low concentration of 30 nM, becoming one of the most potent and selective ERRα degraders to date. Compound 6c could be utilized as a new powerful research tool for further biological investigation of ERRα.

ERRα as a Bridge Between Transcription and Function: Role in Liver Metabolism and Disease

As transcriptional factors, nuclear receptors (NRs) function as major regulators of gene expression. In particular, dysregulation of NR activity has been shown to significantly alter metabolic homeostasis in various contexts leading to metabolic disorders and cancers. The orphan estrogen-related receptor (ERR) subfamily of NRs, comprised of ERRα, ERRβ, and ERRγ, for which a natural ligand has yet to be identified, are known as central regulators of energy metabolism. If AMP-activated protein kinase (AMPK) and mechanistic target of rapamycin (mTOR) can be viewed as sensors of the metabolic needs of a cell and responding acutely via post-translational control of proteins, then the ERRs can be regarded as downstream effectors of metabolism via transcriptional regulation of genes for a long-term and sustained adaptive response. In this review, we will focus on recent findings centered on the transcriptional roles played by ERRα in hepatocytes. Modulation of ERRα activity in both in vitro and in vivo models via genetic or pharmacological manipulation coupled with chromatin-immunoprecipitation (ChIP)-on-chip and ChIP-sequencing (ChIP-seq) studies have been fundamental in delineating the direct roles of ERRα in the control of hepatic gene expression. These studies have identified crucial roles for ERRα in lipid and carbohydrate metabolism as well as in mitochondrial function under both physiological and pathological conditions. The regulation of ERRα expression and activity via ligand-independent modes of action including coregulator binding, post-translational modifications (PTMs) and control of protein stability will be discussed in the context that may serve as valuable tools to modulate ERRα function as new therapeutic avenues for the treatment of hepatic metabolic dysfunction and related diseases.

Emerging Roles of Estrogen-Related Receptors in the Brain: Potential Interactions with Estrogen Signaling

In addition to their well-known role in the female reproductive system, estrogens can act in the brain to regulate a wide range of behaviors and physiological functions in both sexes. Over the past few decades, genetically modified animal models have greatly increased our knowledge about the roles of estrogen receptor (ER) signaling in the brain in behavioral and physiological regulations. However, less attention has been paid to the estrogen-related receptors (ERRs), the members of orphan nuclear receptors whose sequences are homologous to ERs but lack estrogen-binding ability. While endogenous ligands of ERRs remain to be determined, they seemingly share transcriptional targets with ERs and their expression can be directly regulated by ERs through the estrogen-response element embedded within the regulatory region of the genes encoding ERRs. Despite the broad expression of ERRs in the brain, we have just begun to understand the fundamental roles they play at molecular, cellular, and circuit levels. Here, we review recent research advancement in understanding the roles of ERs and ERRs in the brain, with particular emphasis on ERRs, and discuss possible cross-talk between ERs and ERRs in behavioral and physiological regulations.