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

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