Identification of selective 5-LOX and FLAP inhibitors as novel anti-inflammatory agents by ligand-based virtual screening

Targeted lipidomic reveals dietary LA/n-3 PUFAs regulate inflammation and redox status via oxylipins in bivalves

Oxylipins are bioactive lipid mediators derived from fatty acids; however, a comprehensive investigation of oxylipin profiles is absent in bivalves. Moreover, the physiological functions and bioactivities of PUFA-derived oxylipins warrant further exploration. In this study, we found that appropriate dietary linoleic acid (LA)/n-3 PUFAs enhanced the growth of the clam Sinonovacula constricta and improved its survival under hydrogen peroxide (H2O2) stress. Targeted lipidomic showed that the high-LA diet increased accumulation of LA and LA-derived oxylipins. Interestingly, a similar pattern was observed for α-linolenic acid (ALA) and ALA-derived oxylipins, potentially contributing to the anti-inflammatory and antioxidant effects of this dietary pattern. However, dietary n-3 PUFAs provided greater protection against H2O2-induced damage. Dietary n-3 PUFAs significantly increased the levels of oxylipins derived from docosahexaenoic acid and eicosapentaenoic acid, particularly 14(S)-hydroxydocosahexaenoic acid (14(S)-HDHA) and 12-hydroxyeicosapentaenoic acid (12-HEPE). Furthermore, 14(S)-HDHA and 12-HEPE restored cell viability in hydrogen peroxide (H2O2)-treated RAW264.7 cells. Mechanistically, 12-HEPE inhibited nuclear factor kappa B (NF-κB) nuclear translocation while promoting nuclear translocation of nuclear factor erythroid 2-related factor 2 (Nrf2), thereby reducing inflammatory responses and enhancing antioxidant capacity. Additionally, 12-HEPE increased antioxidant activity and suppressed inflammatory gene expression in clam hemolymph cells. This study represents the first comprehensive evaluation of the oxylipin profile in bivalves, further emphasizing the importance of dietary n-3 PUFAs intake in shaping n-3 PUFA-derived oxylipins and consequently influencing inflammation and redox status. Additionally, our study revealed that 12-HEPE alleviates cell damage induced by H2O2, with NF-κB and Nrf2 being key pathways.

Research progress on the role of lipoxygenase and its inhibitors in prostate cancer

Prostate cancer (PCa) has become a common disease among middle-aged and elderly men. The lipoxygenase (LOX) pathway plays a crucial role in the occurrence, development, invasion and metastasis of PCa and is therefore considered a new target for the prevention and treatment of PCa. 5-LOX and 12-LOX have a promoting effect on the occurrence, development, invasion and metastasis of PCa. 15-LOX-2 has an inhibitory effect on PCa. LOX inhibitors can effectively inhibit the metabolic activity of LOX. The research aims to review the mechanism of action and inhibitors of LOX in PCa, in order to provide relevant references for the prevention and treatment of PCa.

Identification of novel RANKL inhibitors through in silico analysis

Receptor activator of nuclear factor-κB ligand (RANKL) is considered the principal regulator of osteoclast differentiation. Therefore, strategies interfering with the RANKL-RANK signaling pathway may effectively inhibit osteoclast differentiation and mitigate bone resorption. Consequently, RANKL has become a promising target for new drug design strategies. Despite extensive research on specific drugs and antibodies, only a few have shown efficacy in treating osteoporosis. To address this challenge, we aimed to explore new approaches for designing drugs for osteoporosis. In this study, a 3D quantitative structure-activity relationship (QSAR) pharmacophore model was built for RANKL with reference to known inhibitor IC50 values. The optimal pharmacophore model was then employed as a 3D query to screen databases for novel lead compounds. The obtained compounds were subjected to ADMET and TOPKAT analyses to predict drug pharmacokinetics and toxicity. Molecular docking and de novo evolution approaches were applied to verify the docking binding affinities of the compounds. Five candidate compounds were subjected to further in vitro analyses to assess their anti-osteoporotic effects, among which compound 4 demonstrated significant inhibitory activity, achieving an inhibitory rate of 92.6 % on osteoclastogenesis at a concentration of 10 μM. Subsequent molecular dynamics (MD) simulations to assess the stability and behavior of compound 4 and its evolved variant, ZINC00059014397_Evo, within the RANKL binding site revealed that the variant is a potential therapeutic agent for targeting osteoclasts. This study offers valuable insights for developing next generation RANKL inhibitors for osteoporosis treatments.

Clinical potential of serum prostaglandin A2 as a novel diagnostic biomarker for hepatocellular cancer

BACKGROUND

Hepatocellular cancer (HCC) is one of the most harmful tumors to human health. Currently, there is still a lack of highly sensitive and specific HCC biomarkers in clinical practice. In this study, we aimed to explore the diagnostic performance of prostaglandin A2 (PGA2) for the early detection of HCC.

METHODS

Untargeted metabolomic analyses on normal control (NC) and HCC participants in the discovery cohort were performed, and PGA2 was identified to be dysregulated in HCC. A liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for detecting serum PGA2 was established and applied to validate the dysregulation of PGA2 in another independent validation cohort. Receiver operating characteristic (ROC), decision curve analysis (DCA) and some other statistical analyses were performed to evaluate the diagnostic performance of PGA2 for HCC.

RESULTS

At first, PGA2 was found to be dysregulated in HCC in untargeted metabolomic analyses. Then a precise quantitative LC-MS/MS method for PGA2 has been established and has passed rigorous method validation. Targeted PGA2 analyses confirmed that serum PGA2 was decreased in HCC compared to normal-risk NC and high-risk cirrhosis group. Subsequently, PGA2 was identified as a novel biomarker for the diagnosis of HCC, with an area under the ROC curve (AUC) of 0.911 for differentiating HCC from the combined NC + cirrhosis groups. In addition, PGA2 exhibited high performance for differentiating small-size (AUC = 0.924), early-stage (AUC = 0.917) and AFP (-) HCC (AUC = 0.909) from the control groups. The combination of PGA2 and AFP might be useful in the surveillance of risk population for HCC and early diagnosis of HCC.

CONCLUSION

This study establishes that PGA2 might be a novel diagnostic biomarker for HCC.

Machine Learning Uncovers Natural Product Modulators of the 5-Lipoxygenase Pathway and Facilitates the Elucidation of Their Biological Mechanisms

Machine learning (ML) models have made inroads into chemical sciences, with optimization of chemical reactions and prediction of biologically active molecules being prime examples thereof. These models excel where physical experiments are expensive or time-consuming, for example, due to large scales or the need for materials that are difficult to obtain. Studies of natural products suffer from these issues─this class of small molecules is known for its wealth of structural diversity and wide-ranging biological activities, but their investigation is hindered by poor synthetic accessibility and lack of scalability. To facilitate the evaluation of these molecules, we designed ML models that predict which natural products can interact with a particular target or a relevant pathway. Here, we focused on discovering natural products that are capable of modulating the 5-lipoxygenase (5-LO) pathway that plays key roles in lipid signaling and inflammation. These computational approaches led to the identification of nine natural products that either directly inhibit the activity of the 5-LO enzyme or affect the cellular 5-LO pathway. Further investigation of one of these molecules, deltonin, led us to discover a new cell-type-selective mechanism of action. Our ML approach helped deorphanize natural products as well as shed light on their mechanisms and can be broadly applied to other use cases in chemical biology.