ArticleSchizophrenia (Heidelberg, Germany)2024
Exploring the potential pharmacological mechanism of aripiprazole against hyperprolactinemia based on network pharmacology and molecular docking.
Article in Schizophrenia (Heidelberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Identifying key molecular interactions and pathways linking DEHP and its metabolite MEHP to allergic rhinitis: a network toxicology and molecular dynamics study.BMC pharmacology & toxicology · 2026Article
- Review of Autism Spectrum Disorder (ASD): Epidemiology, Aetiology, Pathology, and Pharmacological Treatment.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Sexual reactivation under aripiprazole in schizophrenia: a note for prescribers.Journal of psychiatry & neuroscience : JPN · 2025Article
- Article
- Systems pharmacology identifies ajugol-mediated NF-κB/caspase-3 inhibition and isoacteoside-driven p62/mTOR-mediated autophagy as key mechanisms of Rehmanniae Radix and its processed form in Alzheimer's treatment.Frontiers in pharmacology · 2025Article
- The Potential Mechanism ofNutrients · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
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Abstract
The current primary therapeutic approach for schizophrenia is antipsychotic medication, and antipsychotic-induced hyperprolactinemia occurs in 40-80% of patients with schizophrenia. Aripiprazole, an atypical antipsychotic belonging to the quinolinone derivative class, can reduce the likelihood of developing hyperprolactinemia, but the pharmacological mechanisms of this reduction are unknown. This study aimed to explore the molecular mechanism of action of aripiprazole in treating hyperprolactinemia based on network pharmacology and molecular docking techniques. This study identified a total of 151 potential targets for aripiprazole from the DrugBank, TCMSP, BATMAN-TCM, TargetNet, and SwissTargetPrediction databases. Additionally, 71 hyperprolactinemia targets were obtained from the PharmGKB, DrugBank, TTD, GeneCards, OMIM, and DisGENET databases. Utilizing Venny 2.1.0 software, an intersection of 27 genes was identified between aripiprazole and hyperprolactinemia. To construct a common target protein-protein interaction (PPI) network, the common targets obtained from both sources were input into the STRING database. The resulting PPI network was then imported into Cytoscape 3.7.2 software, which identified eight core targets associated with aripiprazole's treatment of hyperprolactinemia. Subsequently, a PPI network was established for these targets. Enrichment analysis of the key targets was conducted using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes in the DAVID database. Additionally, molecular docking verification of the interaction between aripiprazole and the core targets was performed using AutoDock Vina software. Aripiprazole's intervention in hyperprolactinemia primarily targets the following core proteins: Solute Carrier Family 6 Member 3 (SLC6A3), monoamine oxidase (MAO-B), Dopamine D2 receptor (DRD2), 5-hydroxytryptamine (serotonin) receptor 2A (HTR2A), 5-hydroxytryptamine (serotonin) receptor 2C (HTR2C), cytochrome P450 2D6 (CYP2D6), Dopamine D1 receptor (DRD1), Dopamine D4 receptor (DRD4). These targets are predominantly involved in biological processes such as the adenylate cyclase-activating adrenergic receptor signaling pathway, G-protein coupled receptor signaling pathway coupled to cyclic nucleotide second messenger, phospholipase C-activating G-protein coupled receptor signaling pathway, chemical synaptic transmission, and response to xenobiotic stimulus. Primary enrichment occurs in signaling pathways such as the neuroactive ligand-receptor interaction and serotonergic synapse pathways. Molecular docking results demonstrate a favorable affinity between aripiprazole and the core target proteins MAO-B, DRD2, SLC6A3, HTR2C, HTR2A, CYP2D6, DRD4, and DRD1. Network pharmacology predicted potential targets and signaling pathways for aripiprazole's intervention in hyperprolactinemia, offering theoretical support and a reference basis for optimizing clinical strategies and drug development involving aripiprazole.
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Registered trials
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