A functional medicine and food homology composition discovery based on disease-related target and data mining against cardiac remodeling
Xiao, D.; Li, R.; Qin, X.; Feng, J.; Baranenko, D.; Natdochii, L.; Liu, J.; Zhou, Y.; Lin, Y.
Show abstract
BackgroundMedicine and food homological (MFH) products exhibit enhanced safety and tolerability, minimizing notable side effects, making them pivotal for prolonged use in cardiovascular diseases. This study aims to identify functional compounds in MFH based on cardiac remodeling-related target, employing reliable, comprehensive, and high-throughput methods. MethodsBy bioinformatics and in vivo verifications, we initially investigated the key target in the progression of cardiac remodeling. Subsequently, we performed molecular docking among medical homology compound database (MHCD), and then performed drug-likeness evaluations to recognize functional component based on disease-related target. Pharmacological verifications and data mining including cardiac and medullary transcriptomics, neurotransmitter metabolomics, resting-state functional magnetic resonance imaging (rs-fMRI), and correlationship analysis were utilized to define the benefical effects of MFH functional components, as well as its in-depth mechanims. ResultsThe critical roles of oxidative stress and the key target of NRF2 in cardiac remodeling were discovered, and {beta}-ecdysterone was screened as the most promising NRF2 enhancer in MHCD. Dose-dependent efficacy of {beta}-ecdysterone in countering oxidative stress and ameliorating cardiac remodeling were then verfied by in vivo and ex vivo experiments. By data mining, the crosstalk mechanism between cardiac remodeling and neuromodulation was identified, and further unveiled Slc41a3 as a potential key factor influenced by {beta}-ecdysterone. Additionally, {beta}-ecdysterone mitigated increases in norepinephrine (NE) and its metabolites DHPG in the sympathetic nerve center hypothalamic paraventricular (PVN), as indicated by rs-fMRI. Cardiac and medullary transcriptomes revealed central-peripheral regulation signaling pathways during cardiac remodeling with the involvement of core gene of Dhx37. ConclusionsOur study identified {beta}-ecdysterone as a natural MFH functional compound countering cardiac remodeling by targeting NRF2 elevation. It elucidates crosstalk between cardiac remodeling and neuromodulation, facilitating precise drug screening and mechanistic insights, providing substantial evidence for {beta}-ecdysterone application and molecular mechanisms in cardiovascular diseases.
Matching journals
The top 11 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Virtual drug screen reveals context-dependent inhibition of cardiomyocyte hypertrophy 93%
- Artesunate interacts with Vitamin D receptor to reverse mouse model of sepsis-induced immunosuppression via enhancing autophagy 93%
- Niclosamide Prodrug Enhances Oral Bioavailability and Targets Vasorin-TGFβ Signaling in Hepatocellular Carcinoma 91%
Similar papers in this journal
- From atoms to cells: bridging the gap between potency, efficacy, and safety of small molecules directed at a membrane protein 93%
- Targeting PFKFB3 alleviates cerebral ischemia-reperfusion injury in mice 93%
- SGLT2 inhibitors attenuate endothelial to mesenchymal transition and cardiac fibroblast activation 93%
Similar papers in this journal
- Primulagenin A is a potent inverse agonist of the nuclear receptor RAR-related orphan receptor gamma (RORγ) 93%
- An optimized derivative of an endogenous CXCR4 antagonist prevents atopic dermatitis and airway inflammation 91%
- Transfer Learning Enhanced Graph Neural Network for Aldehyde Oxidase Metabolism Prediction and Its Experimental Application 91%
Similar papers in this journal
Similar papers in this journal
- RvD1 and LXA4 inhibitory effects on cardiac voltage-gated potassium channels 91%
- NRF2 upregulation by CDDO-Me protects AC16 human cardiomyocytes against doxorubicin-induced toxicity. 90%
- Novel assays monitoring direct glucocorticoid receptor protein activity exhibit high predictive power for ligand activity on endogenous gene targets 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.