The molecular mechanisms through which psilocybin prevents suicide: evidence from network pharmacology and molecular docking analyses

Abstract

Psilocybin is among the most extensively studied psychedelics, with previous research suggesting its potential therapeutic role in suicide prevention. However, the precise mechanisms through which psilocybin may aid in suicide prevention remain unclear. This study thus employed network pharmacology and molecular docking tools to explore the mechanisms by which psilocybin may contribute to suicide prevention. Relevant drug- and disease-related targets were identified. Overlapping drug- and disease-related targets were extracted from the bioinformatics platform and imported into the STRING database to construct a protein-protein interaction (PPI) network. Key targets were selected based on topological parameters derived from network analyses conducted using Cytoscape 3.10.1. These key targets were further analyzed using GO and KEGG enrichment approaches conducted with the DAVID tool. A drug-disease-target-pathway network was subsequently constructed in Cytoscape 3.10.1. Finally, molecular docking analyses were performed to assess psilocybin's potential to interact with key targets using AutoDock Vina and the PyMOL software. A total of 46 potential targets associated with psilocybin and relevant to suicide treatment were identified, of which 13 were imported into the DAVID tool for enrichment analyses. Network analyses identified four targets-HTR2A, HTR2C, HTR7, and PRKACA-that may serve as therapeutic targets for psilocybin in suicide prevention. Enrichment analysis outcomes suggested that psilocybin may prevent suicide by modulating the serotonergic synapse and calcium signaling pathways. Molecular docking analyses revealed that HTR2A, HTR2C, HTR7, and PRKACA strongly bind to psilocybin. This study provides insights into the molecular mechanisms underlying the potential role of psilocybin in suicide prevention, offering a novel basis for further research.

Fig. 1

Flowchart for the network pharmacology-based analysis of the mechanisms through which psilocybin can help prevent suicide.

Fig. 2. Targets of psilocybin and suicide.

A A Venn diagram representing the common targets overlapping between psilocybin and suicide. B The established PPI network containing the overlapping targets from (A). C, D An overview of the topological screening analysis of the PPI network. Thirteen essential targets were obtained after 46 intersecting targets were filtered using degree centrality (DC), betweenness centrality (BC), and closeness centrality (CC).

Fig. 3. GO and KEGG pathway enrichment analyses.

A GO enrichment analysis results showing the top 10 functions. B KEGG pathway enrichment analysis results showing the top 10 pathways. C The overlapping targets associated with the serotonergic synapse and calcium signaling pathway were selected as the top four core targets. D A network illustrating the interactions between drugs, diseases, and pathways. The green and red octagons represent drugs and diseases, respectively. Purple “V” shapes denote pathways, while dark purple “V” shapes indicate key pathways. Yellow and orange hexagons denote the targets, with yellow representing the four core targets.

Fig. 4. Distribution of common targets in the main signaling pathways.

A, B Network maps of the serotonergic synapse pathway (A) and the calcium signaling pathway (B). Red parks represent potential targets of psilocybin related to its ability to help prevent suicide.

Fig. 5. Molecular docking of psilocybin with core targets.

A–D Molecular docking analyses of the interaction between psilocybin and (A) 7WC4, (B) 8DPF, (C) 7XTC, and (D) 7Y1G (encoded by HTR2A, HTR2C, HRT7, and PRKACA, respectively).