Molecular mechanisms of amisulpride- and risperidone-induced hPRL in patients with psychiatric disorders: an integrated approach combining network pharmacology and molecular docking.

Authors

Chen Chen, Qing Liu, Xi Su, Wen-Qiang Li

Published in

Progress in neuro-psychopharmacology & biological psychiatry. Pages 111974. Oct 12, 2026. Epub Oct 12, 2026.

Abstract

Hyperprolactinemia (hPRL) is a frequent and clinically important adverse effect of antipsychotic treatment, particularly with amisulpride and risperidone, which are among the most potent prolactin-raising agents. Clinical observations show a high incidence of antipsychotic-induced hPRL in patients treated with these drugs, with prolactin elevations emerging early and often persisting during therapy. However, the molecular mechanisms by which amisulpride or risperidone, used either alone or in combination, induce hPRL remain incompletely understood. In this study, clinical data were first used to characterize prolactin changes in psychiatric patients receiving combined amisulpride-risperidone therapy. To refine current mechanistic understanding, a network pharmacology strategy was applied to integrate predicted and validated targets of amisulpride, risperidone, and hPRL. Intersection targets were used to construct a protein-protein interaction network and were subsequently subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The enriched pathways were mainly associated with prolactin-related signaling, including the prolactin signaling pathway, the PI3K/AKT pathway, and the dopaminergic synapse pathway. Key hub proteins, including DRD2, GSK3B, HTR2A, IGF1R, JAK2, and MAOA, were then subjected to molecular docking with amisulpride and risperidone. Both drugs showed low docking energies, suggesting strong binding affinities for these core targets. These findings indicate that amisulpride- and risperidone-induced hPRL is mediated by a convergent set of core targets and signaling pathways, thereby providing a systems-level framework for understanding, predicting, and potentially mitigating this adverse effect in clinical practice.

PMID:
42863806
Bibliographic data and abstract were imported from PubMed on 13 Oct 2026.

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