Search bioRxiv⌕ Search

bioRxiv · 10.1101/2024.09.21.614279

Explore the mechanism of Zigui Yichong Formula in reducing the apoptosis of ovarian granulosa cells in premature ovarian insufficiency based on network pharmacology, molecular docking and cell experiments

Abstract

ObjectiveThis research is conducted with the objective of exploring the underlying mechanism by which the Zigui Yichong Formula (ZGYCF) diminishes granulosa cell apoptosis in the context of premature ovarian insufficiency (POI), utilizing network pharmacology, molecular docking, and cellular experimentation approaches. MethodsThe active constituents and potential therapeutic targets of the 12 medicinal herbs in ZGYCF, which include Rehmannia glutinosa, Cervus nippon, Cornus officinalis, Ligustrum lucidum, Lycium barbarum, Paeonia lactiflora, Astragalus membranaceus, Codonopsis pilosula, Atractylodes macrocephala, Angelica sinensis, Cyperus rotundus, and Glycyrrhiza uralensis, were identified through searches in the TCMSP, BATMAN, HERB, and ETCM databases. Targets associated with the POI condition were gathered from the OpenTargets, DrugBank, and GeneCards databases. Subsequently, a Venn diagram illustrating the compound-target-disease interaction was generated to derive a set of common targets that bridge the gap between pharmacological and pathological targets. A drug-component-target-disease network diagram was created using Cytoscape 3.9.1. Additionally, protein-protein interaction (PPI) networks were built utilizing the STRING database and visualized with Cytoscape to pinpoint key targets within the overlapping target set. Functional annotation and pathway enrichment analyses, including GO and KEGG pathway analyses, were performed using the clusterProfiler package in R 4.2.1 to investigate the underlying mechanisms by which the drug may influence the disease state. The molecular docking of pivotal active constituents with central targets was carried out using AutoDock Tools. Following this, in vitro studies were executed to corroborate the anticipated mechanisms of action of ZGYCF on POI that were inferred from the network pharmacology analysis. ResultsThe selected active components include quercetin, kaempferol, and {beta}-sitosterol. The core targets identified are Tp53, Bcl-2, and Caspase-3. GO functional and KEGG enrichment analyses indicate that these core targets are primarily enriched in the p53 signaling pathway. Molecular docking results show that quercetin, kaempferol, and {beta}-sitosterol have good binding affinity with TP53, Bcl-2, and Caspase-3. Additionally, in vitro experiments demonstrate that ZGYCF medicated serum can reduce ACR-induced apoptosis in KGN cells, increase Bcl-2 expression, and decrease the expression of p53, Bax, Caspase-3, and the Bcl-2/Bax ratio. ConclusionZGYCF exerts therapeutic effects on POI through multiple targets and pathways, and it may reduce ACR-induced apoptosis in KGN cells by modulating the p53 signaling pathway. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=130 HEIGHT=200 SRC="FIGDIR/small/614279v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@1e55e2forg.highwire.dtl.DTLVardef@18a67d0org.highwire.dtl.DTLVardef@1a596d0org.highwire.dtl.DTLVardef@503fde_HPS_FORMAT_FIGEXP M_FIG C_FIG

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Zhang, X., Zhang, X.-M., Xi, H.-Y., Gao, T.-Y., Liu, S.-P., Li, R.-X., Hongyan Xi Co-first authorRongxoa Li Corresponding author Tianyu Gao Second auther Shupeng Liu Thi,. 2024-09-24. Explore the mechanism of Zigui Yichong Formula in reducing the apoptosis of ovarian granulosa cells in premature ovarian insufficiency based on network pharmacology, molecular docking and cell experiments. https://doi.org/10.1101/2024.09.21.614279

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Translational Pharmacokinetics and Pharmacodynamics of a Cationic mRNA-Lipid Nanoparticle from Mice to Non-Human Primates

Cationic lipid nanoparticles have demonstrated unique potential for extrahepatic mRNA delivery, particularly enabling selective targeting of the pulmonary endothelium. However, their translational development has been hampered by reports of infusion-related immune reactions and innate immune system activation, most notably transient complement activation. Here, we present a case study illustrating the discovery and translational advancement of a selected cationic LNP into non-human primates (NHPs) for initial pharmacokinetic assessment and evaluation of potential immunostimulatory side effects. We show surface charge dependent organ-selective expression of reporter mRNAs from different LNPs in vivo. An mRNA encoding the Tie2 agonist COMP-Angl, was formulated with LNP002, and respective pharmacokinetic and pharmacodynamic readouts were analyzed in two independent non-human primate studies. Notably, dose-dependent transient complement activation could be abrogated by extending the infusion time. Finally, we identified the blood-borne pharmacodynamic biomarker PDGFB for LNP002/mRNA-76 treatment reflecting activated Tie2-signalling in healthy pulmonary endothelium in vivo supported by single cell sequencing and cluster-alignment of downstream effector genes with the same spatial profile as the delivered mRNA.

pharmacology and toxicology↗

Cytotoxic Effects of Multiple Pesticides and their Mixtures on Caco-2 Cells Evaluated by Using MTT and Trypan Blue Assays

BACKGROUND: Pesticides are extensively used in agriculture, raising concerns about their potential impact on human health through dietary and environmental exposure. OBJECTIVES: This study evaluated the in vitro cytotoxicity of ten commonly used pesticides and their mixtures (lambda-cyhalothrin, cypermethrin, deltamethrin, tebuconazole, glyphosate, acetamiprid, cyprodinil, piperonyl butoxide, fluopyram, and imazalil) on human intestinal Caco-2 cells. METHODS: Cytotoxicity was assessed using the MTT assay, as a measure of metabolic activity, and the trypan blue exclusion test, as an indicator of cell membrane integrity. FINDINGS: Results showed that high concentrations (100 mg/L) of all pesticides significantly reduced cell viability and vitality. Notably, glyphosate and tebuconazole exhibited significant toxicity even at lower concentrations, respectively 0.1 mg/L and 10 mg/L. Combination treatments (Top 3 and Top 8 pesticide mixtures) retained the cytotoxic effects observed for individual compounds, showing additive (non-synergistic) effects. CONCLUSIONS: Overall, these findings indicate that certain pesticides-based herbicides can exert cytotoxic effects on intestinal cells even at relatively low concentrations and highlight the importance of using the component-based approach in mixture risk assessment for humans. This study was performed as part of the EU SPRINT (Sustainable Plant Protection Transition: A Global Health Approach) project.

pharmacology and toxicology↗

Assessing chemical toxicity across Eukaryota using multimodal transformers

Biodiversity is globally threatened by chemical pollution, yet toxicity data remain unavailable for millions of species and tens of thousands of chemicals, severely limiting our ability to assess ecological impacts. Here we present TRIDENT-2, a multimodal artificial intelligence model for predicting chemical toxicity across evolutionarily diverse eukaryotic species. Trained on 560,780 toxicity assays spanning 82,775 chemicals, 6,793 species, and multiple exposure scenarios, TRIDENT-2 accurately predicts toxicity across Eukaryota with an average median absolute error ranging from 1.76 to 3.80. By jointly learning from chemical, biological, and experimental information, it remains accurate across broad chemical and taxonomic distances, allowing for toxicity assessment for species and chemicals beyond the current experimental evidence. Our findings demonstrate that artificial intelligence can help overcome longstanding data limitations in ecotoxicology, paving the way for improved decision-making and reducing chemical impacts on biodiversity and ecosystems.

pharmacology and toxicology↗