Integrated network pharmacology analysis and experimental validation to investigate the mechanism of Flavan-3-ols and aromatic resins in depression.

The present investigation delved into the pharmacological mechanisms underlying the management of depression through Flavan-3-ols and Aromatic Resins, employing in silico and in vivo methodologies. Network pharmacology was utilized to identify targets associated with the antidepressant activity of Flavan-3-ols and Aromatic Resins. Protein-protein interaction and KEGG analyses were conducted to enrich and explore key pathways. Molecular docking and simulation studies were executed to assess the targets. The antidepressant effects were studied using the Forced Swim Test and Tail Suspension Test on both unstressed mice and those subjected to the chronic unpredictable mild stress (CUMS) paradigm. The Compound-Target network analysis revealed a substantial impact of the components on numerous targets, with 332 nodes and 491 edges. Protein-protein interaction analysis indicated significant interactions with targets implicated in depression. KEGG analysis highlighted major pathways, including neuroactive ligand-receptor interaction, dopaminergic synapse, and long-term depression. Docking studies on EGCG demonstrated binding energies of -7.2 kcal/mol for serotonin 1 A (5-HT1A), -7.9 kcal/mol for D2, and - 9.6 kcal/mol for MOA-A. Molecular dynamics simulation indicated minute fluctuation, hence suggesting stable complexes formed between small molecules and proteins. The combination of Flavan-3-ols and Aromatic Resins significantly increased mobility time (p < 0.05) in the Forced Swim Test and Tail Suspension Test, while significantly decreasing immobility time and time freezing (p < 0.05) in both unstressed and CUMS mice. This study demonstrated the antidepressant characteristics of Flavan-3-ols and Aromatic Resins, underscoring the need for further research to develop a novel antidepressant medication.

Network pharmacology combined with molecular docking and experimental verification to elucidate the effect of flavan-3-ols and aromatic resin on anxiety.

This study investigated the potential anxiolytic properties of flavan-3-ols and aromatic resins through a combined computational and experimental approach. Network pharmacology techniques were utilized to identify potential anxiolytic targets and compounds by analyzing protein-protein interactions and KEGG pathway data. Molecular docking and simulation studies were conducted to evaluate the binding interactions and stability of the identified targets. Behavioral tests, including the elevated plus maze test, open field test, light-dark test, actophotometer, and holeboard test, were used to assess anxiolytic activity. The compound-target network analysis revealed complex interactions involving 306 nodes and 526 edges, with significant interactions observed and an average node degree of 1.94. KEGG pathway analysis highlighted pathways such as neuroactive ligand-receptor interactions, dopaminergic synapses, and serotonergic synapses as being involved in anxiety modulation. Docking studies on EGCG (Epigallocatechin gallate) showed binding energies of -9.5 kcal/mol for MAOA, -9.2 kcal/mol for SLC6A4, and -7.4 kcal/mol for COMT. Molecular dynamic simulations indicated minimal fluctuations, suggesting the formation of stable complexes between small molecules and proteins. Behavioral tests demonstrated a significant reduction in anxiety-like behavior, as evidenced by an increased number of entries into and time spent in the open arm of the elevated plus maze test, light-dark test, open field center activity, hole board head dips, and actophotometer beam interruptions (p < 0.05 or p < 0.01). This research provides a comprehensive understanding of the multi-component, multi-target, and multi-pathway intervention mechanisms of flavan-3-ols and aromatic resins in anxiety treatment. Integrated network and behavioral analyses collectively support the anxiolytic potential of these compounds and offer valuable insights for future research in this area.

Integrative network pharmacology, molecular docking, and dynamic simulation analysis of a polyherbal formulation for potential therapeutic impact on prostate cancer.

Background: Prostate cancer (PCa) remains a significant health concern globally, prompting a continual search for novel therapeutic strategies. In this study, we employed a comprehensive approach combining network pharmacology, molecular docking and dynamic simulation to explore the potential impact of a polyherbal formulation on PCa. Methods: Utilizing comprehensive network pharmacology approaches, we elucidated the complex interactions between the bioactive compounds within the polyherbal formulation and key targets associated with PCa progression, highlighting their multitarget mechanisms through integrated protein‒protein interaction and KEGG pathway analyses. Molecular docking simulation studies were performed to predict the binding affinities and modes of interaction between the identified bioactive compounds and their respective protein targets. Results: Complex connections comprising 486 nodes and 845 edges were found by the compound-target network analysis. Significant interactions were observed, and the average node degree was 4.23. KEGG research revealed that PCa and the PI3K-Akt signalling pathway are implicated in modulating prostate cancer. The Quercetin docking investigations revealed that the binding energies for AR and PIK3R1 were -9 and -9.5 kcal/mol, respectively. Based on the results of the MD simulations, it appears that tiny molecules and proteins have formed stable complexes with low fluctuations. Conclusion: In conclusion, this comprehensive method emphasises the value of network pharmacology in conjunction with molecular docking and dynamic simulation in revealing the anti-PCa therapeutic potential of polyherbal formulations, opening up new possibilities for the creation of efficient anti-cancer medicines.