Exploring the mechanism of Toddalia asiatica (L.) Lam. in the treatment of osteoarthritis through bioinformatics and network pharmacology

doi:10.5246/jcps.2025.09.063

Abstract

Abstract:

This study employed an integrated approach combining bioinformatics and network pharmacology to elucidate the potential active compounds and mechanisms of action of Toddalia asiatica (L.) Lam. (T. asiatica) in treating osteoarthritis (OA). Initially, the components of T. asiatica were extracted from the literature, and their ADMF properties were assessed using SwissADME. Subsequently, the corresponding targets for the effective components were predicted through the SwissTargetPrediction database. A drug-component-target network was then constructed using Cytoscape, which facilitated the identification of the primary active components based on their degree values within the network. In parallel, differentially expressed genes related to OA were comprehensively analyzed utilizing GEO data. The intersection of the targets from T. asiatica and those associated with OA was determined, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, as well as the construction of a protein-protein interaction (PPI) network through the String platform. The topological network was visualized using Cytoscape, and core genes were identified via the Cytohubba plugin. In total, 54 effective components and 694 corresponding targets of T. asiatica were predicted. Based on the degree values from the drug-component-target network, 22 principal active components were ultimately identified. From the GEO database, 493 OA-related targets were retrieved, revealing 46 shared targets between T. asiatica and OA. The enrichment analysis of these intersecting genes suggested that T. asiatica may exert anti-OA effects through multiple components, targets, and pathways. Notably, the PPI network analysis highlighted MCL1 as a core target. The diagnostic potential of this gene was further evaluated using an external validation set for OA. Additionally, the binding affinity of the 22 main active components of T. asiatica to MCL1 was elucidated through molecular docking studies. This research enhanced our understanding of the pharmacological effects of T. asiatica against OA and its active components, providing valuable insights and evidence for future studies.

Key words: Toddalia asiatica (L.) Lam., Osteoarthritis, Bioinformatics, Network pharmacology, Molecular docking, Mechanism

Supporting:

Qian Deng, Zining Peng, Danning Mao, Yuanbo Huang, Nian Liu, Weitian Yan, Jiangyun Peng. Exploring the mechanism of Toddalia asiatica (L.) Lam. in the treatment of osteoarthritis through bioinformatics and network pharmacology[J]. Journal of Chinese Pharmaceutical Sciences, 2025, 34(9): 860-872.

Figures/Tables 9

Table 1. The 22 core components of T. asiatica.

Table 2. Fundamental information and classification of the GEO data set.

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