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<p>Psychiatric disorders severely challenge the public health, but the development of new psychotropic medications cannot keep pace with clinical needs. The rapid accumulation of single-cell RNA data provides opportunities to develop new computational approaches of drug repurposing. However, there is a lack of dedicated computational tools for psychiatric disorders in this field. In this work, we developed a cell-type specific interaction based computational pipeline scPsyDrug to prioritize the drugs for psychiatric disorders. This tool integrated the single-cell transcriptomics, protein-protein interactions, drug-target interactions and psychiatric risk genes to construct cell type-specific interactions and seed genes for drug prioritization. We first evaluated the scPsyDrug performance using the publicly available single cell RNA datasets derived from the clinical patients, including Major Depressive Disorder, Schizophrenia and Parkinson’s disease, in which scPsyDrug covered lots of approved drugs and clinical-trial compounds in the top recommended candidates. We next applied scPsyDrug to <i>Zbtb18</i><sup>+/−</sup> mice, an anxiety-like mouse model, to screen the potential drugs. The scPsyDrug prioritized Forskolin and Chlorpropamide as the top candidates, while the following drug treatment demonstrated that these two compounds could respectively rescue the anxiety-like behaviors in <i>Zbtb18</i><sup>+/−</sup> mice. We also used scPsyDrug to screen herb ingredients, and validated the efficacy of Osthole in rescuing the anxiety-like behaviors in the mouse model. Collectively, the scPsyDrug can be applied to different kinds of psychiatric disorders for drug repurposing, and we also provided experimental evidence for the potential roles of Forskolin, Chlorpropamide and Osthole in anxiety intervention.</p>

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The cell-type specific interaction based drug repurposing for psychiatric disorders

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月30日

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  • Yiyuli Tang,
  • Yuzhuo Zhou,
  • Zhenning Wei,
  • Yan Wen,
  • Cheng Peng

摘要

Psychiatric disorders severely challenge the public health, but the development of new psychotropic medications cannot keep pace with clinical needs. The rapid accumulation of single-cell RNA data provides opportunities to develop new computational approaches of drug repurposing. However, there is a lack of dedicated computational tools for psychiatric disorders in this field. In this work, we developed a cell-type specific interaction based computational pipeline scPsyDrug to prioritize the drugs for psychiatric disorders. This tool integrated the single-cell transcriptomics, protein-protein interactions, drug-target interactions and psychiatric risk genes to construct cell type-specific interactions and seed genes for drug prioritization. We first evaluated the scPsyDrug performance using the publicly available single cell RNA datasets derived from the clinical patients, including Major Depressive Disorder, Schizophrenia and Parkinson’s disease, in which scPsyDrug covered lots of approved drugs and clinical-trial compounds in the top recommended candidates. We next applied scPsyDrug to Zbtb18+/− mice, an anxiety-like mouse model, to screen the potential drugs. The scPsyDrug prioritized Forskolin and Chlorpropamide as the top candidates, while the following drug treatment demonstrated that these two compounds could respectively rescue the anxiety-like behaviors in Zbtb18+/− mice. We also used scPsyDrug to screen herb ingredients, and validated the efficacy of Osthole in rescuing the anxiety-like behaviors in the mouse model. Collectively, the scPsyDrug can be applied to different kinds of psychiatric disorders for drug repurposing, and we also provided experimental evidence for the potential roles of Forskolin, Chlorpropamide and Osthole in anxiety intervention.