Network pharmacology and molecular docking to explore mechanisms of clozapine-induced cardiac arrest
Bibliographic record
Abstract
BACKGROUND: Clozapine is superior to all other antipsychotics in treating schizophrenia in terms of its curative efficacy; however, this drug is prescribed only as a last resort in the treatment of schizophrenia, given its potential to induce cardiac arrest. The mechanism of clozapine-induced cardiac arrest remains unclear, so we aimed to elucidate the potential mechanisms of clozapine-induced cardiac arrest using network pharmacology and molecular docking. METHODS: We identified and analyzed the overlap between potential cardiac arrest-related target genes and clozapine target genes. We conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. We then constructed a protein-protein interaction (PPI) network and screened the core targets. We used molecular docking to evaluate the binding energy between clozapine and core targets. RESULTS: We identified a total of 2405 target genes related to cardiac arrest and 107 target genes for clozapine. Among these, we found 41 overlapping target genes. The main enriched GO biological processes included the upregulation of the mitogen-activated protein kinase (MAPK) cascade and the adenylate cyclase-activating adrenergic receptor signalling pathway. The KEGG enrichment analysis showed that the neuroactive ligand-receptor interaction and the forkhead box O (FoxO) signalling pathway seemed to be the key signalling pathways involved in clozapine-induced cardiac arrest. The 7 core targets identified in the established PPI network were G-protein-coupled receptor kinase 2, 5-hydroxytryptamine 2A receptor, dopamine D2 receptor, glycogen synthase kinase 3β, cyclin-dependent kinase 2, CREB-binding protein, and signal transducer and activator of transcription 3. The molecular docking results indicated a high affinity between clozapine and all of these core targets. LIMITATIONS: The relatively small scope of the predictive and modelling methods, which predominantly comprised network pharmacology and molecular docking strategies, is a limitation of this study. CONCLUSION: Network pharmacology and molecular docking approaches unveiled target genes for clozapine and potential mechanisms by which it may cause cardiac arrest, including the MAPK cascade, neuroactive ligand-receptor interactions, and the FoxO signalling pathway.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".