ArticleScientific reports2023
Bioinformatics and computational chemistry approaches to explore the mechanism of the anti-depressive effect of ligustilide.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- Elucidating the Mechanism of the Liqi Yangyin Formula in Treating Depression-Constipation Comorbidity: An Integrative Approach Using Network Pharmacology and Experimental Validation.Pharmaceuticals (Basel, Switzerland) · 2026Article
- A classic traditional chinese medicine formula for depression: mechanistic insights from phytochemical constituents and multitarget pathways.Psychopharmacology · 2025Article
- Insights into Hepatic, Neuronal, and hERG Channel Safety of Plant-Derived Active Compounds.Journal of xenobiotics · 2025Article
- Effect of rhizosphere soil microbial communities and environmental factors on growth and the active ingredients of Angelica sinensis in Gansu Province, China.Folia microbiologica · 2025Article
- Chemical Investigations inMolecules (Basel, Switzerland) · 2023Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Depression affects people with multiple adverse outcomes, and the side effects of antidepressants are troubling for depression sufferers. Aromatic drugs have been widely used to relieve symptoms of depression with fewer side effects. Ligustilide (LIG) is the main component of volatile oil in angelica sinensis, exhibiting an excellent anti-depressive effect. However, the mechanisms of the anti-depressive effect of LIG remain unclear. Therefore, this study aimed to explore the mechanisms of LIG exerting an anti-depressive effect. We obtained 12,969 depression-related genes and 204 LIG targets by a network pharmacology approach, which were intersected to get 150 LIG anti-depressive targets. Then, we identified core targets by MCODE, including MAPK3, EGF, MAPK14, CCND1, IL6, CASP3, IL2, MYC, TLR4, AKT1, ESR1, TP53, HIF1A, SRC, STAT3, AR, IL1B, and CREBBP. Functional enrichment analysis of core targets showed a significant association with PI3K/AKT and MAPK signaling pathways. Molecular docking showed strong affinities of LIG with AKT1, MAPK14, and ESR1. Finally, we validated the interactions between these proteins and LIG by molecular dynamics (MD) simulations. In conclusion, this study successfully predicted that LIG exerted an anti-depressive effect through multiple targets, including AKT1, MAPK14, and ESR1, and the pathways of PI3K/AKT and MAPK. The study provides a new strategy to explore the molecular mechanisms of LIG in treating depression.
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