ArticleFrontiers in bioinformatics2026
Network pharmacology and molecular modelling analysis of
Article in Frontiers in bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Valproic acid (VPA) is an antiepileptic drug commonly employed to treat epilepsy. Despite this, the clinical application of VPA is often hindered by adverse reactions. This study aims to investigate the therapeutic potential of phytochemicals obtained from Methods: Network pharmacology and molecular modelling techniques were employed. HR-LCMS-QTOF was conducted to identify the phytoconstituents. ADMET and toxicity screening were then performed. Ligand-based prediction and toxicity gene analysis were employed to determine the potential targets. Protein-protein interaction analysis and function enrichment analysis were conducted to understand the potential mechanisms. Molecular docking and molecular dynamics studies were conducted to determine the protein-ligand interaction potential. Results: A total of 111 metabolites were identified, out of which 22 compounds passed the ADMET and toxicity screening. Using ligand-based prediction and toxicity analysis, 18 potential target genes were identified. These include MAPK8, NLRP3, TNF-α, and MCL-1. These are involved in various functions, including inflammation, apoptosis, and metabolic regulation. Molecular docking analysis revealed high protein-ligand interaction potential. This was evident by the high binding affinity of the phytoconstituents to the potential targets. Among all the compounds, 4-Hydroxy-3-methoxy-2,10-bisaboladien-9-one showed the highest potential. Molecular dynamics analysis revealed high protein-ligand complex stability, especially with MCL-1 and NLRP3. Function enrichment and Metascape analysis revealed the involvement of the potential targets in oxidative stress, inflammation, and xenobiotic metabolism. Conclusion: The results suggest that phytoconstituents from
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