A network pharmacology-based approach to decipher the pharmacological mechanisms of Salvia officinalis in neurodegenerative disorders.

Abstract

The present study aimed to assess the pharmacological mechanism of Salvia officinalis in Neurodegenerative disorders using a network pharmacology approach followed by molecular docking analysis. Phytoconstituents of S.officinalis were obtained from various databases, followed by the screening of active ingredients using the Swiss ADME web tool. Potential targets of active ingredients were identified using PubChem & SwissTargetPrediction. Genes related to Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD) were gathered using online databases. Besides, the correlation between active ingredient targets and disease-associated genes was linked. Networks were constructed, visualized, and analyzed using Cytoscape. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analysis were performed using DAVID database. Decisively, Autodock was used for molecular docking. The results of network analysis identified 9 key active ingredients based on topological analysis of the active ingredient-candidate targets network. Also, the analysis revealed a shared target of 9 key active ingredients of S. officinalis that interacted with 133 AD-related targets whereas only 6 active ingredients interacted with 85 and 58 targets of PD and HD respectively. The core genes from the network were AKT1, BACE1, CASP3, MAPK1, TNF, and IL6. Furthermore, GO and KEGG enrichment analysis showed that FOXO, TNF, MAPK, PI3K-Akt, Rap 1, and neurotrophin signalling pathways as enriched, which were further evaluated by molecular docking suggesting the protective role of S. officinalis in neurodegenerative diseases. Our research reveals the therapeutic benefits of S. officinalis, which might play a crucial role in modulating neurodegenerative diseases.