Acceleration of infectious disease drug discovery and development using a humanized model of drug metabolism.

A key step in drug discovery, common to many disease areas, is preclinical demonstration of efficacy in a mouse model of disease. However, this demonstration and its translation to the clinic can be impeded by mouse-specific pathways of drug metabolism. Here, we show that a mouse line extensively humanized for the cytochrome P450 gene superfamily ("8HUM") can circumvent these problems. The pharmacokinetics, metabolite profiles, and magnitude of drug-drug interactions of a test set of approved medicines were in much closer alignment with clinical observations than in wild-type mice. Infection with Mycobacterium tuberculosis, Leishmania donovani, and Trypanosoma cruzi was well tolerated in 8HUM, permitting efficacy assessment. During such assessments, mouse-specific metabolic liabilities were bypassed while the impact of clinically relevant active metabolites and DDI on efficacy were well captured. Removal of species differences in metabolism by replacement of wild-type mice with 8HUM therefore reduces compound attrition while improving clinical translation, accelerating drug discovery.

Leveraging multi-omics data to empower quantitative systems pharmacology in immuno-oncology.

Understanding the intricate interactions of cancer cells with the tumor microenvironment (TME) is a pre-requisite for the optimization of immunotherapy. Mechanistic models such as quantitative systems pharmacology (QSP) provide insights into the TME dynamics and predict the efficacy of immunotherapy in virtual patient populations/digital twins but require vast amounts of multimodal data for parameterization. Large-scale datasets characterizing the TME are available due to recent advances in bioinformatics for multi-omics data. Here, we discuss the perspectives of leveraging omics-derived bioinformatics estimates to inform QSP models and circumvent the challenges of model calibration and validation in immuno-oncology.

Integrating network pharmacology and in silico analysis deciphers Withaferin-A's anti-breast cancer potential via hedgehog pathway and target network interplay.

This study examines the remarkable effectiveness of Withaferin-A (WA), a withanolide obtained from Withania somnifera (Ashwagandha), in encountering the mortiferous breast malignancy, a global peril. The predominant objective is to investigate WA's intrinsic target proteins and hedgehog (Hh) pathway proteins in breast cancer targeting through the application of in silico computational techniques and network pharmacology predictions. The databases and webtools like Swiss target prediction, GeneCards, DisGeNet and Online Mendelian Inheritance in Man were exploited to identify the common target proteins. The culmination of the WA network and protein-protein interaction network were devised using Stitch and String web tools, through which the drug-target network of 30 common proteins was constructed employing Cytoscape-version 3.9. Enrichment analysis was performed by incorporating Gprofiler, Metascape and Cytoscape plugins. David compounded the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, and enrichment was computed through bioinformatics tools. The 20 pivotal proteins were docked harnessing Glide, Schrodinger Suite 2023-2. The investigation was governed by docking scores and affinity. The shared target proteins underscored the precise Hh and WA network roles with the affirmation enrichment P-value of <0.025. The implications for hedgehog and cancer pathways were profound with enrichment (P < 0.01). Further, the ADMET and drug-likeness assessments assisted the claim. Robust interactions were noticed with docking studies, authenticated through molecular dynamics, molecular mechanics generalized born surface area scores and bonds. The computational investigation emphasized WA's credible anti-breast activity, specifically with Hh proteins, implying stem-cell-level checkpoint restraints. Rigorous testament is imperative through in vitro and in vivo studies.

Dual-channel hypergraph convolutional network for predicting herb-disease associations.

Herbs applicability in disease treatment has been verified through experiences over thousands of years. The understanding of herb-disease associations (HDAs) is yet far from complete due to the complicated mechanism inherent in multi-target and multi-component (MTMC) botanical therapeutics. Most of the existing prediction models fail to incorporate the MTMC mechanism. To overcome this problem, we propose a novel dual-channel hypergraph convolutional network, namely HGHDA, for HDA prediction. Technically, HGHDA first adopts an autoencoder to project components and target protein onto a low-dimensional latent space so as to obtain their embeddings by preserving similarity characteristics in their original feature spaces. To model the high-order relations between herbs and their components, we design a channel in HGHDA to encode a hypergraph that describes the high-order patterns of herb-component relations via hypergraph convolution. The other channel in HGHDA is also established in the same way to model the high-order relations between diseases and target proteins. The embeddings of drugs and diseases are then aggregated through our dual-channel network to obtain the prediction results with a scoring function. To evaluate the performance of HGHDA, a series of extensive experiments have been conducted on two benchmark datasets, and the results demonstrate the superiority of HGHDA over the state-of-the-art algorithms proposed for HDA prediction. Besides, our case study on Chuan Xiong and Astragalus membranaceus is a strong indicator to verify the effectiveness of HGHDA, as seven and eight out of the top 10 diseases predicted by HGHDA for Chuan-Xiong and Astragalus-membranaceus, respectively, have been reported in literature.

Pharmacological Management of Cardiac Arrhythmias in the Fetal and Neonatal Periods: A Scientific Statement From the American Heart Association: Endorsed by the Pediatric & Congenital Electrophysiology Society (PACES).

Disorders of the cardiac rhythm may occur in both the fetus and neonate. Because of the immature myocardium, the hemodynamic consequences of either bradyarrhythmias or tachyarrhythmias may be far more significant than in mature physiological states. Treatment options are limited in the fetus and neonate because of limited vascular access, patient size, and the significant risk/benefit ratio of any intervention. In addition, exposure of the fetus or neonate to either persistent arrhythmias or antiarrhythmic medications may have yet-to-be-determined long-term developmental consequences. This scientific statement discusses the mechanism of arrhythmias, pharmacological treatment options, and distinct aspects of pharmacokinetics for the fetus and neonate. From the available current data, subjects of apparent consistency/consensus are presented, as well as future directions for research in terms of aspects of care for which evidence has not been established.

Network pharmacology: towards the artificial intelligence-based precision traditional Chinese medicine.

Network pharmacology (NP) provides a new methodological perspective for understanding traditional medicine from a holistic perspective, giving rise to frontiers such as traditional Chinese medicine network pharmacology (TCM-NP). With the development of artificial intelligence (AI) technology, it is key for NP to develop network-based AI methods to reveal the treatment mechanism of complex diseases from massive omics data. In this review, focusing on the TCM-NP, we summarize involved AI methods into three categories: network relationship mining, network target positioning and network target navigating, and present the typical application of TCM-NP in uncovering biological basis and clinical value of Cold/Hot syndromes. Collectively, our review provides researchers with an innovative overview of the methodological progress of NP and its application in TCM from the AI perspective.

Targeting metaplasticity mechanisms to promote sustained antidepressant actions.

The discovery that subanesthetic doses of (R, S)-ketamine (ketamine) and (S)-ketamine (esketamine) rapidly induce antidepressant effects and promote sustained actions following drug clearance in depressed patients who are treatment-resistant to other therapies has resulted in a paradigm shift in the conceptualization of how rapidly and effectively depression can be treated. Consequently, the mechanism(s) that next generation antidepressants may engage to improve pathophysiology and resultant symptomology are being reconceptualized. Impaired excitatory glutamatergic synapses in mood-regulating circuits are likely a substantial contributor to the pathophysiology of depression. Metaplasticity is the process of regulating future capacity for plasticity by priming neurons with a stimulation that alters later neuronal plasticity responses. Accordingly, the development of treatment modalities that specifically modulate the duration, direction, or magnitude of glutamatergic synaptic plasticity events such as long-term potentiation (LTP), defined here as metaplastogens, may be an effective approach to reverse the pathophysiology underlying depression and improve depression symptoms. We review evidence that the initiating mechanisms of pharmacologically diverse rapid-acting antidepressants (i.e., ketamine mimetics) converge on consistent downstream molecular mediators that facilitate the expression/maintenance of increased synaptic strength and resultant persisting antidepressant effects. Specifically, while the initiating mechanisms of these therapies may differ (e.g., cell type-specificity, N-methyl-D-aspartate receptor (NMDAR) subtype-selective inhibition vs activation, metabotropic glutamate receptor 2/3 antagonism, AMPA receptor potentiation, 5-HT receptor-activating psychedelics, etc.), the sustained therapeutic mechanisms of putative rapid-acting antidepressants will be mediated, in part, by metaplastic effects that converge on consistent molecular mediators to enhance excitatory neurotransmission and altered capacity for synaptic plasticity. We conclude that the convergence of these therapeutic mechanisms provides the opportunity for metaplasticity processes to be harnessed as a druggable plasticity mechanism by next-generation therapeutics. Further, targeting metaplastic mechanisms presents therapeutic advantages including decreased dosing frequency and associated diminished adverse responses by eliminating the requirement for the drug to be continuously present.

Use of Genomics to Develop Novel Therapeutics and Personalize Hypertension Therapy.

Hypertension is a prevalent public health problem, contributing to >10 million deaths annually. Though multiple therapeutics exist, many patients suffer from treatment-resistant hypertension or try several medications before achieving blood pressure control. Genomic advances offer mechanistic understanding of blood pressure variability, therapeutic targets, therapeutic response, and promise a stratified approach to treatment of primary hypertension. Cyclic guanosine monophosphate augmentation, aldosterone synthase inhibitors, and angiotensinogen blockade with silencing RNA and antisense therapies are among the promising novel approaches. Pharmacogenomic studies have also been done to explore the genetic bases underpinning interindividual variability in response to existing therapeutics. A polygenic approach using risk scores is likely to be the next frontier in stratifying responses to existing therapeutics.

Emulation of Quantitative Systems Pharmacology models to accelerate virtual population inference in immuno-oncology.

Quantitative Systems Pharmacology (QSP) models are increasingly being applied for target discovery and dose selection in immuno-oncology (IO). Typical application involves virtual trial, a simulation of a virtual population of hundreds of model instances with model inputs reflecting individual variability. While the structure of the model and initial parameterisation are based on literature describing the underlying biology, calibration of the virtual population by existing clinical data is frequently required to create tumour and patient population specific model instances. Since comparison of a virtual trial with clinical output requires hundreds of large-scale, non-linear model evaluations, the inference of a virtual population is computationally expensive, frequently becoming a bottleneck. Here, we present novel approach to virtual population inference in IO using emulation of the QSP model and an objective function based on Kolmogorov-Smirnov statistics to maximise congruence of simulated and observed clinical tumour size distributions. We sample the parameter space of a QSP IO model to collect a set of tumour growth time profiles. We evaluate performance of several machine learning approaches in interpolating these time profiles and create a surrogate model, which computes tumor growth profiles faster than the original model and allows examination of tens of millions of virtual patients. We use the surrogate model to infer a virtual population maximising congruence with the waterfall plot of a pembrolizumab clinical trial. We believe that our approach is applicable not only in QSP IO, but also in other applications where virtual populations need to be inferred for computationally expensive mechanistic models.

Morbidity and mortality risks associated with valproate withdrawal in young men and women with epilepsy.

Valproate is the most effective treatment for idiopathic generalised epilepsy. Current guidance precludes its use in women of childbearing potential, unless other treatments are ineffective or not tolerated, because of high teratogenicity. This risk was recently extended to men. New guidance will limit use both in men and women aged <55 years, resulting in withdrawal of valproate from men already taking it, as occurs for women. Whether there are risks of personal harm (including injury or death) associated with valproate withdrawal has not yet been quantified for men or women on valproate, meaning clinicians cannot reliably counsel either sex when discussing valproate withdrawal with them, despite that this concern may be at the forefront of patients' and clinicians' minds. We assessed whether there are any morbidity or mortality risks associated with valproate withdrawal in young men and women. We performed a retrospective cohort study of internationally derived electronic health data within the TriNetX Global Collaborative Network. Included were men and women aged 16-54 years with ≥1 epilepsy disease or symptom code between 01/12/2017-01/12/2018 and ≥2 valproate prescriptions over the preceding two years (01/01/2015-30/11/2017). 5-year propensity-matched risks of mortality and a range of morbidity outcomes were compared between those remaining on vs. withdrawn from valproate during the 01/12/2017-01/12/2018 recruitment period, regardless of whether switched to another antiseizure medication. Survival analysis was undertaken using Cox-proportional hazard models, generating hazard ratios (HRs) with 95% confidence intervals (CIs). 8,991 men and 5,243 women taking valproate were recruited. 28% of men and 36% of women were subsequently withdrawn from valproate. Valproate withdrawal was associated with significantly increased risks of emergency department attendance (HRs overall: 1.236 (CI 1.159-1.319), men: 1.181 (CI 1.083-1.288), women: 1.242 (CI 1.125-1.371)), hospital admission (HRs overall: 1.160 (CI 1.081-1.246), men: 1.132 (CI 1.027-1.249), women: 1.147 (CI 1.033-1.274)), falls (HRs overall: 1.179 (CI 1.041-1.336), men: 1.298 (CI 1.090-1.546)), injuries (HRs overall: 1.095 (CI 1.021-1.174), men: 1.129 (CI 1.029-1.239)), burns (HRs overall: 1.592 (CI 1.084-2.337)), and new-onset depression (HRs overall 1.323 (CI 1.119-1.565), women: 1.359 (CI 1.074-1.720)). The risk of these outcomes occurring was 1-7% higher in those withdrawn from valproate than in those remaining on valproate. Overall, valproate withdrawal was not associated with increased mortality. These results may help patients and clinicians have a more informed discussion about personal safety when considering valproate withdrawal.

Naringenin inhibits APAP-induced acute liver injury through activating PPARA-dependent signaling pathway.

Acute liver injury (ALI) refers to the damage to the liver cells of patients due to drugs, food, and diseases. In this work, we used a network pharmacology approach to analyze the relevant targets and pathways of the active ingredients in Citri Reticulatae Pericarpium (CRP) for the treatment of ALI and conducted systematic validation through in vivo and in vitro experiments. The network pharmacologic results predicted that naringenin (NIN) was the main active component of CRP in the treatment of ALI. GO functional annotation and KEGG pathway enrichment showed that its mechanism may be related to the regulation of PPARA signaling pathway, PPARG signaling pathway, AKT1 signaling pathway, MAPK3 signaling pathway and other signaling pathways. The results of in vivo experiments showed that (NIN) could reduce the liver lesions, liver adipose lesions, hepatocyte injury and apoptosis in mice with APAP-induced ALI, and reduce the oxidative stress damage of mouse liver cells and the inflammation-related factors to regulate ALI. In vitro experiments showed that NIN could inhibit the proliferation, oxidative stress and inflammation of APAP-induced LO2 cells, promote APAP-induced apoptosis of LO2 cells, and regulate the expression of apoptotic genes in acute liver injury. Further studies showed that NIN inhibited APAP-induced ALI mainly by regulating the PPARA-dependent signaling pathway. In conclusion, this study provides a preliminary theoretical basis for the screening of active compounds in CRP for the prevention and treatment of ALI.

Disease-associated nonsense and frame-shift variants resulting in the truncation of the GluN2A or GluN2B C-terminal domain decrease NMDAR surface expression and reduce potentiating effects of neurosteroids.

N-methyl-D-aspartate receptors (NMDARs) play a critical role in normal brain function, and variants in genes encoding NMDAR subunits have been described in individuals with various neuropsychiatric disorders. We have used whole-cell patch-clamp electrophysiology, fluorescence microscopy and in-silico modeling to explore the functional consequences of disease-associated nonsense and frame-shift variants resulting in the truncation of GluN2A or GluN2B C-terminal domain (CTD). This study characterizes variant NMDARs and shows their reduced surface expression and synaptic localization, altered agonist affinity, increased desensitization, and reduced probability of channel opening. We also show that naturally occurring and synthetic steroids pregnenolone sulfate and epipregnanolone butanoic acid, respectively, enhance NMDAR function in a way that is dependent on the length of the truncated CTD and, further, is steroid-specific, GluN2A/B subunit-specific, and GluN1 splice variant-specific. Adding to the previously described effects of disease-associated NMDAR variants on the receptor biogenesis and function, our results improve the understanding of the molecular consequences of NMDAR CTD truncations and provide an opportunity for the development of new therapeutic neurosteroid-based ligands.

Pharmacokinetics and Safety of Remdesivir in Pregnant and Non-Pregnant Women with COVID-19: Results from IMPAACT 2032.

BACKGROUND: Pregnant people with COVID-19 experience higher risk for severe disease and adverse pregnancy outcomes, but no pharmacokinetic (PK) data exist to support dosing of COVID-19 therapeutics during pregnancy. We report PK and safety data for intravenous remdesivir in pregnancy. METHODS: IMPAACT 2032 was a phase IV prospective, open-label, non-randomized opportunistic study of hospitalized pregnant and non-pregnant women receiving intravenous remdesivir as part of clinical care. Intensive PK sampling was performed on infusion days 3, 4, or 5 with collection of plasma and peripheral blood mononuclear cells (PBMCs). Safety data were recorded from first infusion through 4 weeks post-last infusion and at delivery. Geometric mean ratios (GMR) (90% confidence intervals [CI]) of PK parameters between pregnant and non-pregnant women were calculated. RESULTS: Fifty-three participants initiated remdesivir (25 pregnant; median (IQR) gestational age 27.6 (24.9, 31.0) weeks). Plasma exposures of remdesivir, its two major metabolites (GS-704277 and GS-441524), and the free remdesivir fraction were similar between pregnant and non-pregnant participants. Concentrations of the active triphosphate (GS-443902) in PBMCs increased 2.04-fold (90% CI 1.35, 3.03) with each additional infusion in non-pregnant versus pregnant participants. Three adverse events in non-pregnant participants were related to treatment (one Grade 3; two Grade 2 resulting in treatment discontinuation). There were no treatment-related adverse pregnancy outcomes or congenital anomalies detected. CONCLUSIONS: Plasma remdesivir PK parameters were comparable between pregnant and non-pregnant women, and no safety concerns were identified based on our limited data. These findings suggest no dose adjustments are indicated for intravenous remdesivir during pregnancy.

Pharmacological characterization of allosteric modulators: A case for chemokine receptors.

Chemokine receptors are relevant targets for a multitude of immunological diseases, but drug attrition for these receptors is remarkably high. While many drug discovery programs have been pursued, most prospective drugs failed in the follow-up studies due to clinical inefficacy, and hence there is a clear need for alternative approaches. Allosteric modulators of receptor function represent an excellent opportunity for novel drugs, as they modulate receptor activation in a controlled manner and display increased selectivity, and their pharmacological profile can be insurmountable. Here, we discuss allosteric ligands and their pharmacological characterization for modulation of chemokine receptors. Ligands are included if (1) they show clear signs of allosteric modulation in vitro and (2) display evidence of binding in a topologically distinct manner compared to endogenous chemokines. We discuss how allosteric ligands affect binding of orthosteric (endogenous) ligands in terms of affinity as well as binding kinetics in radioligand binding assays. Moreover, their effects on signaling events in functional assays and how their binding site can be elucidated are specified. We substantiate this with examples of published allosteric ligands targeting chemokine receptors and hypothetical graphs of pharmacological behavior. This review should serve as an effective starting point for setting up assays for characterizing allosteric ligands to develop safer and more efficacious drugs for chemokine receptors and, ultimately, other G protein-coupled receptors.

Amentoflavone reverses epithelial-mesenchymal transition in hepatocellular carcinoma cells by targeting p53 signalling pathway axis.

Epithelial-mesenchymal transition (EMT) and its reversal process are important potential mechanisms in the development of HCC. Selaginella doederleinii Hieron is widely used in Traditional Chinese Medicine for the treatment of various tumours and Amentoflavone is its main active ingredient. This study investigates the mechanism of action of Amentoflavone on EMT in hepatocellular carcinoma from the perspective of bioinformatics and network pharmacology. Bioinformatics was used to screen Amentoflavone-regulated EMT genes that are closely related to the prognosis of HCC, and a molecular prediction model was established to assess the prognosis of HCC. The network pharmacology was used to predict the pathway axis regulated by Amentoflavone. Molecular docking of Amentoflavone with corresponding targets was performed. Detection and evaluation of the effects of Amentoflavone on cell proliferation, migration, invasion and apoptosis by CCK-8 kit, wound healing assay, Transwell assay and annexin V-FITC/propidium iodide staining. Eventually three core genes were screened, inculding NR1I2, CDK1 and CHEK1. A total of 590 GO enrichment entries were obtained, and five enrichment results were obtained by KEGG pathway analysis. Genes were mainly enriched in the p53 signalling pathway. The outcomes derived from both the wound healing assay and Transwell assay demonstrated significant inhibition of migration and invasion in HCC cells upon exposure to different concentrations of Amentoflavone. The results of Annexin V-FITC/PI staining assay showed that different concentrations of Amentoflavone induces apoptosis in HCC cells. This study revealed that the mechanism of Amentoflavone reverses EMT in hepatocellular carcinoma, possibly by inhibiting the expression of core genes and blocking the p53 signalling pathway axis to inhibit the migration and invasion of HCC cells.

Exploring the pharmacological mechanism of Glycyrrhiza uralensis against KOA through integrating network pharmacology and experimental assessment.

Knee osteoarthritis (KOA), a major health and economic problem facing older adults worldwide, is a degenerative joint disease. Glycyrrhiza uralensis Fisch. (GC) plays an integral role in many classic Chinese medicine prescriptions for treating knee osteoarthritis. Still, the role of GC in treating KOA is unclear. To explore the pharmacological mechanism of GC against KOA, UPLC-Q-TOF/MS was conducted to detect the main compounds in GC. The therapeutic effect of GC on DMM-induced osteoarthritic mice was assessed by histomorphology, µCT, behavioural tests, and immunohistochemical staining. Network pharmacology and molecular docking were used to predict the potential targets of GC against KOA. The predicted results were verified by immunohistochemical staining Animal experiments showed that GC had a protective effect on DMM-induced KOA, mainly in the improvement of movement disorders, subchondral bone sclerosis and cartilage damage. A variety of flavonoids and triterpenoids were detected in GC via UPLC-Q-TOF/MS, such as Naringenin. Seven core targets (JUN, MAPK3, MAPK1, AKT1, TP53, RELA and STAT3) and three main pathways (IL-17, NF-κB and TNF signalling pathways) were discovered through network pharmacology analysis that closely related to inflammatory response. Interestingly, molecular docking results showed that the active ingredient Naringenin had a good binding effect on anti-inflammatory-related proteins. In the verification experiment, after the intervention of GC, the expression levels of pp65 and F4/80 inflammatory indicators in the knee joint of KOA model mice were significantly downregulated. GC could improve the inflammatory environment in DMM-induced osteoarthritic mice thus alleviating the physiological structure and dysfunction of the knee joint. GC might play an important role in the treatment of knee osteoarthritis.

Mechanism of Astragalus membranaceus (Huangqi, HQ) for treatment of heart failure based on network pharmacology and molecular docking.

Heart failure is a leading cause of death in the elderly. Traditional Chinese medicine, a verified alternative therapeutic regimen, has been used to treat heart failure, which is less expensive and has fewer adverse effects. In this study, a total of 15 active ingredients of Astragalus membranaceus (Huangqi, HQ) were obtained; among them, Isorhamnetin, Quercetin, Calycosin, Formononetin, and Kaempferol were found to be linked to heart failure. Ang II significantly enlarged the cell size of cardiomyocytes, which could be partially reduced by Quercetin, Isorhamnetin, Calycosin, Kaempferol, or Formononetin. Ang II significantly up-regulated ANP, BNP, ß-MHC, and CTGF expressions, whereas Quercetin, Isorhamnetin, Calycosin, Kaempferol or Formononetin treatment partially downregulated ANP, BNP, ß-MHC and CTGF expressions. Five active ingredients of HQ attenuated inflammation in Ang II-induced cardiomyocytes by inhibiting the levels of TNF-α, IL-1ß, IL-18 and IL-6. Molecular docking shows Isorhamnetin, Quercetin, Calycosin, Formononetin and Kaempferol can bind with its target protein ESR1 in a good bond by intermolecular force. Quercetin, Calycosin, Kaempferol or Formononetin treatment promoted the expression levels of ESR1 and phosphorylated ESR1 in Ang II-stimulated cardiomyocytes; however, Isorhamnetin treatment had no effect on ESR1 and phosphorylated ESR1 expression levels. In conclusion, our results comprehensively illustrated the bioactives, potential targets, and molecular mechanism of HQ against heart failure. Isorhamnetin, Quercetin, Calycosin, Formononetin and Kaempferol might be the primary active ingredients of HQ, dominating its cardioprotective effects against heart failure through regulating ESR1 expression, which provided a basis for the clinical application of HQ to regulate cardiac hypertrophy and heart failure.

Identification of Key Hypolipidemic Components and Exploration of the Potential Mechanism of Total Flavonoids from Rosa sterilis Based on Network Pharmacology, Molecular Docking, and Zebrafish Experiment.

Hyperlipidemia is a prevalent chronic metabolic disease that severely affects human health. Currently, commonly used clinical therapeutic drugs are prone to drug dependence and toxic side effects. Dietary intervention for treating chronic metabolic diseases has received widespread attention. Rosa sterilis is a characteristic fruit tree in China whose fruits are rich in flavonoids, which have been shown to have a therapeutic effect on hyperlipidemia; however, their exact molecular mechanism of action remains unclear. Therefore, this study aimed to investigate the therapeutic effects of R. sterilis total flavonoid extract (RS) on hyperlipidemia and its possible mechanisms. A hyperlipidemic zebrafish model was established using egg yolk powder and then treated with RS to observe changes in the integral optical density in the tail vessels. Network pharmacology and molecular docking were used to investigate the potential mechanism of action of RS for the treatment of hyperlipidemia. The results showed that RS exhibited favorable hypolipidemic effects on zebrafish in the concentration range of 3.0-30.0 µg/mL in a dose-dependent manner. Topological and molecular docking analyses identified HSP90AA1, PPARA, and MMP9 as key targets for hypolipidemic effects, which were exerted mainly through lipolytic regulation of adipocytes and lipids; pathway analysis revealed enrichment in atherosclerosis, chemical carcinogenic-receptor activation pathways in cancers, and proteoglycans in prostate cancer and other cancers. Mover, chinensinaphthol possessed higher content and better target binding ability, which suggested that chinensinaphthol might be an important component of RS with hypolipidemic active function. These findings provide a direction for further research on RS interventions for the treatment of hyperlipidemia.

Norcantharidin Enhances the Antitumor Effect of 5-Fluorouracil by Inducing Apoptosis of Cervical Cancer Cells: Network Pharmacology, Molecular Docking, and Experimental Validation.

The high recurrence rate of cervical cancer is a leading cause of cancer deaths in women. 5-Fluorouracil (5-FU) is an antitumor drug used to treat many types of cancer, but its diminishing effectiveness and side effects limit its use. Norcantharidin (NCTD), a demethylated derivative of cantharidin, exhibits various biological activities. Here, we investigated whether NCTD could potentiate 5-FU to induce cervical cancer cell death. To assess the cell viability and synergistic effects of the drugs, cell counting kit-8 and colony formation assays were performed using HR-HPV-positive cervical cancer cell lines. Annexin V-FITC/PI staining and TUNEL assays were performed to confirm the induction of apoptosis. The synergistic effect of NCTD on the antitumor activity of 5-FU was analyzed using network pharmacology, molecular docking, and molecular dynamics simulations. Apoptosis-related proteins were examined using immunoblotting. The combination of NCTD and 5-FU was synergistic in cervical cancer cell lines. Network pharmacological analysis identified 10 common targets of NCTD and 5-FU for cervical cancer treatment. Molecular docking showed the strong binding affinity of both compounds with CA12, CASP9, and PTGS1. Molecular dynamics simulations showed that the complex system of both drugs with caspase-9 could be in a stable state. NCTD enhanced 5-FU-mediated cytotoxicity by activating apoptosis-related proteins. NCTD acts synergistically with 5-FU to inhibit cervical cancer cell proliferation. NCTD enhances 5-FU-induced apoptosis in cervical cancer cell lines via the caspase-dependent pathway.

Network Pharmacology Analysis, Molecular Docking Integrated Experimental Verification Reveal the Mechanism of Gynostemma pentaphyllum in the Treatment of Type II Diabetes by Regulating the IRS1/PI3K/Akt Signaling Pathway.

Gynostemma pentaphyllum (Thunb.) Makino (GP), a plant with homology of medicine and food, as a traditional Chinese medicine, possesses promising biological activities in the prevention and treatment of type 2 diabetes mellitus (T2DM). However, the material basis and the mechanism of action of GP in the treatment of T2DM have not been fully elucidated. This study aimed to clarify the active components, potential targets and signaling pathways of GP in treating T2DM. The chemical ingredients of GP were collected by combining UPLC-HRMS analysis and literature research. Network pharmacology revealed that GP had 32 components and 326 potential targets in treating T2DM. The results showed that GP affected T2DM by mediating the insulin resistance signaling pathway, PI3K/Akt signaling pathway and FoxO1 signaling pathway, which had a close relationship with T2DM. Molecular docking results showed that STAT3, PIK3CA, AKT1, EGFR, VEGFA and INSR had high affinity with the active compounds of GP. In vitro, GP extracts obviously increased the glucose uptake and glucose consumption in IR-HepG2 cells. GP extracts increased the levels of PI3K, p-AKT, p-GSK3ß and p-FoxO1 and decreased the expression of p-IRS1, p-GS, PEPCK and G6Pase, which indicated that GP could promote glycogen synthesis and inhibit gluconeogenesis by regulating the IRS1/PI3K/Akt signaling pathway. The results demonstrated that GP could improve insulin resistance by promoting glucose uptake and glycogen synthesis and inhibiting gluconeogenesis through regulating the IRS1/PI3K/Akt signaling pathway, which might be a potential alternative therapy for T2DM.