Structural Biology Inspired Development of a Series of Human Peroxisome Proliferator-Activated Receptor Gamma (PPARγ) Ligands: From Agonist to Antagonist

Recent advances and therapeutic applications of PPARγ-targeted ligands based on the inhibition mechanism of Ser273 phosphorylation

PPARγ functions as a master ligand-dependent transcription factor that regulates the expressions of a variety of key genes related to metabolic homeostasis and inflammatory immunity. It has been recognized as a popular and druggable target in modern drug discovery. Similar to other nuclear receptors, PPARγ is a phosphoprotein, and its biological functions are regulated by phosphorylation, especially at Ser273 site which is mediated by CDK5 or ERK. In the past decade, the excessive level of PPARγ-Ser273 phosphorylation has been confirmed to be a crucial factor in promoting the occurrence and development of some major diseases. Ligands capable of inhibiting PPARγ-Ser273 phosphorylation have shown great potentials for treatment. Despite these achievements, to our knowledge, no related review focusing on this topic has been conducted so far. Therefore, we herein summarize the basic knowledge of PPARγ and CDK5/ERK-mediated PPARγ-Ser273 phosphorylation as well as its physiopathological role in representative diseases. We also review the developments and therapeutic applications of PPARγ-targeted ligands based on this mechanism. Finally, we suggest several directions for future investigations. We expect that this review can evoke more inspiration of scientific communities, ultimately facilitating the promotion of the PPARγ-Ser273 phosphorylation-involved mechanism as a promising breakthrough point for addressing the clinical treatment of human diseases.

Yanghe Decoction promotes ferroptosis through PPARγ-dependent autophagy to inhibit the malignant progression of triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a heterogeneous subtype of breast cancer that displays highly aggressive with poor prognosis. Yanghe Decoction (YHD) has been used in the treatment of breast cancer for many years. We aimed to explore the effects of YHD on the malignant phenotypes of MDA-MB-231 cells and the potential mechanism related to PPARγ, autophagy and ferroptosis. The serum of rat containing different concentrations of YHD were collected to culture MDA-MB-231 cells. Cell viability and proliferation were assessed by the CCK-8 assay and EDU staining. Wound healing- and transwell assays were used to detect the capacities of MDA-MB-231 cell migration and invasion. Additionally, the levels of lipid peroxidation, Fe2+ and the expression of ferroptosis-related proteins were evaluated. The expression of PPARγ and autophagy-related proteins was assessed using immunofluorescence staining or western blot assay. Then, the PPARγ inhibitor (GW9662), autophagy inhibitor (3-MA) and autophagy inducer (rapamycin; Rap) were used to further study the potential mechanism of YHD on TNBC. Results indicated that contained-YHD serum significantly decreased the viability, proliferation, migration and invasion of TNBC cells. Moreover, YHD promoted lipid peroxidation level, elevated Fe2+ content and downregulated GPX4, SLC7A11 and SLC3A2 expression. Besides, autophagy was induced and PPARγ was upregulated by YHD in MDA-MB-231 cells. Furthermore, GW9662 alleviated the impacts of YHD on autophagy of MDA-MB-231 cells. Rap reversed the effects of GW9662 on lipid peroxidation, ferroptosis, proliferation, migration and invasion of MDA-MB-231 cells. 3-MA had the similar effects to GW9662. Collectively, YHD suppressed the malignant progression of MDA-MB-231 cells by inducing ferroptosis through PPARγ-dependent autophagy.

Clustering Molecules at a Large Scale: Integrating Spectral Geometry with Deep Learning

This study conducts an in-depth analysis of clustering small molecules using spectral geometry and deep learning techniques. We applied a spectral geometric approach to convert molecular structures into triangulated meshes and used the Laplace-Beltrami operator to derive significant geometric features. By examining the eigenvectors of these operators, we captured the intrinsic geometric properties of the molecules, aiding their classification and clustering. The research utilized four deep learning methods: Deep Belief Network, Convolutional Autoencoder, Variational Autoencoder, and Adversarial Autoencoder, each paired with k-means clustering at different cluster sizes. Clustering quality was evaluated using the Calinski-Harabasz and Davies-Bouldin indices, Silhouette Score, and standard deviation. Nonparametric tests were used to assess the impact of topological descriptors on clustering outcomes. Our results show that the DBN + k-means combination is the most effective, particularly at lower cluster counts, demonstrating significant sensitivity to structural variations. This study highlights the potential of integrating spectral geometry with deep learning for precise and efficient molecular clustering.

PPARγ Agonist Rosiglitazone and Antagonist GW9662: Antihypertensive Effects on Chronic Intermittent Hypoxia-Induced Hypertension in Rats

The increased incidence of hypertension associated with obstructive sleep apnea (OSA) presents significant physical, psychological, and economic challenges. Peroxisome proliferator-activated receptor gamma (PPARγ) plays a role in both OSA and hypertension, yet the therapeutic potential of PPARγ agonists and antagonists for OSA-related hypertension remains unexplored. Therefore, we constructed a chronic intermittent hypoxia (CIH)-induced hypertension rat model that mimics the pathogenesis of OSA-related hypertension in humans. The model involved administering PPARγ agonist rosiglitazone (RSG), PPARγ antagonist GW9662, or normal saline, followed by regular monitoring of blood pressure and thoracic aorta analysis using staining and electron microscopy. Intriguingly, our results indicated that both RSG and GW9662 appeared to potently counteract CIH-induced hypertension. In silico study suggested that GW9662's antihypertensive effect might mediated through angiotensin II receptor type 1 (AGTR1). Our findings provide insights into the mechanisms of OSA-related hypertension and propose novel therapeutic targets.

VSP-2 attenuates secretion of inflammatory cytokines induced by LPS in BV2 cells by mediating the PPARγ/NF-κB signaling pathway

Neuroinflammation, characterized by microglial activation and the subsequent secretion of inflammatory cytokines, plays a pivotal role in neurodegenerative diseases and brain injuries, often leading to neuronal damage and death. Alleviating neuroinflammation has thus emerged as a promising strategy to protect neurons and ameliorate neurodegenerative disorders. While peroxisome proliferator-activated receptor gamma (PPARγ) agonists have demonstrated potential therapeutic actions on neuroinflammation, their prolonged use, such as with rosiglitazone, can lead to cardiac risks and lipid differentiation disorders. In this study, we investigated the effects of a newly synthesized PPARγ agonist, VSP-2, on secretion of inflammatory cytokines in BV2 cells. Treatment with VSP-2 significantly reduced the mRNA and protein levels of proinflammatory cytokines such as interleukin-1β (IL-1β), IL-6, and tumor necrosis factor-α (TNF-α). Furthermore, VSP-2 attenuated the phosphorylation of nuclear factor kappa B (NF-κB) (65 kD) and IκBα, as well as the nuclear translocation of NF-κB (65 kD). Additionally, the use of PPARγ small interfering RNA was able to attenuate the effects of VSP-2 on proinflammatory cytokines and the NF-κB pathway. In conclusion, our findings suggest that VSP-2 effectively suppressed the expressions of IL-1β, IL-6, and TNF-α via the PPARγ/NF-κB signaling pathway. Given its potential therapeutic benefits, VSP-2 may emerge as a promising candidate for the treatment of neurodegenerative diseases or brain injuries associated with neuroinflammation.

Targeting PPARs for therapy of atherosclerosis: A review

Atherosclerosis, a chief pathogenic factor of cardiovascular disease, is associated with many factors including inflammation, dyslipidemia, and oxidative stress. Peroxisome proliferator-activated receptors (PPARs) are nuclear receptors and are widely expressed with tissue- and cell-specificity. They control multiple genes that are involved in lipid metabolism, inflammatory response, and redox homeostasis. Given the diverse biological functions of PPARs, they have been extensively studied since their discovery in 1990s. Although controversies exist, accumulating evidence have demonstrated that PPAR activation attenuates atherosclerosis. Recent advances are valuable for understanding the mechanisms of action of PPAR activation. This article reviews the recent findings, mainly from the year of 2018 to present, including endogenous molecules in regulation of PPARs, roles of PPARs in atherosclerosis by focusing on lipid metabolism, inflammation, and oxidative stress, and synthesized PPAR modulators. This article provides information valuable for researchers in the field of basic cardiovascular research, for pharmacologists that are interested in developing novel PPAR agonists and antagonists with lower side effects as well as for clinicians.