A Computational Framework of Host-Based Drug Repositioning for Broad-Spectrum Antivirals against RNA Viruses


RNA viruses are responsible for many types of zoonotic diseases that post great challenges for public health system. Effective therapeutics against these viral infections remains limited. Here we deployed a computational framework for host-based drug repositioning to predict potential antiviral drug candidates from 2352 approved drugs and 1062 natural compounds embedded in Traditional Chinese Medicine herbs. By systematically interrogating public genetic screening data, we comprehensively catalogued human-specific host dependency genes that are indispensable for the successful viral infection corresponding to 10 families and 29 species of RNA viruses. In addition, we utilized these host dependency genes as potential drug targets, and interrogated extensive drug-target interactions through multiple ways such as database retrieval, literature mining and de novo prediction using artificial intelligence-based algorithms. Repurposed drugs or natural compounds were proposed for combating many viral pathogens such as coronaviruses (e.g., SARS-CoV-2), flaviviruses (e.g., Zika virus) and influenza viruses. This study helps to prioritize promising drug candidates for further therapeutic evaluation against these viral-related diseases.


Supplementary material

Table S1. Compendium of host dependency genes for multiple RNA viruses
Table S2. Sequence sources for phylogenetic analysis
Table S3. Re-analysis of CRISPR screening data
Table S4. Functional gene enrichment analysis of host dependency genes
Table S5. List of drug-target interactions and repurposed drug candidates