An integrative drug repositioning framework discovered a potential therapeutic agent targeting COVID-19

Yiyue Ge,Xiaolong Feng,Ligong Chen,Ying Cheng ,Shuya Li,Dan Zhao,Lunbiao Cui,Nian Wu,Ziyuan Jiang,Xiling Guo,Ze‐Hong Miao ,Lixiang Hong,Jingxin Li,Fengcai Zhu,Fangping Wan,Ying Luo ,Lili Cheng,Hui Yang,Zeng Li,Liang Xiao,Yunfu Wu,Tingzhong Tian,Suling Huang,Chunhao Yang,Chengliang Hu,Xiaoxia Shen ,Yipin Lei,Hantao Shu,Xiaoting Wang,Hainian Zeng,Enming Yuan,Haitao Li,Jianyang Zeng

doi:10.1038/s41392-021-00568-6

Abstract

The global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires an urgent need to find effective therapeutics for the treatment of coronavirus disease 2019 (COVID-19). In this study, we developed an integrative drug repositioning framework, which fully takes advantage of machine learning and statistical analysis approaches to systematically integrate and mine large-scale knowledge graph, literature and transcriptome data to discover the potential drug candidates against SARS-CoV-2. Our in silico screening followed by wet-lab validation indicated that a poly-ADP-ribose polymerase 1 (PARP1) inhibitor, CVL218, currently in Phase I clinical trial, may be repurposed to treat COVID-19. Our in vitro assays revealed that CVL218 can exhibit effective inhibitory activity against SARS-CoV-2 replication without obvious cytopathic effect. In addition, we showed that CVL218 can interact with the nucleocapsid (N) protein of SARS-CoV-2 and is able to suppress the LPS-induced production of several inflammatory cytokines that are highly relevant to the prevention of immunopathology induced by SARS-CoV-2 infection.

Highlights

INTRODUCTION The global COVID19 pandemic caused by the novel coronavirus SARS-CoV-2 (2019-nCoV) has brought a huge number of infections and deaths worldwide according to the World Health Organization
After (Fig. 1b) using cross-validation and a retrospective study on the checking the clinical status of PJ-34, we found that it only reached past data of the two coronaviruses that are closely related to the preclinical trial stage (DrugBank ID: DB08348,19) which may SARS-CoV-2 and had been relatively well studied in the literature, i.e., SARS-CoV and MERS-CoV
Over 50% of the drugs known to act on a virus CVL218 exhibits in vitro inhibitory activity against SARS-CoV-2 target can be accurately predicted by CoV-drug–target interactions (DTIs) from the top 200 replication drug candidates, with a better performance compared to DTINet

Summary

Introduction

INTRODUCTION The global COVID19 pandemic caused by the novel coronavirus SARS-CoV-2 (2019-nCoV) has brought a huge number of infections and deaths worldwide according to the World Health Organization. ROC (AUROC) score of 0.8273, which was 8% higher than that of DTINet. In addition, over 50% of the drugs known to act on a virus CVL218 exhibits in vitro inhibitory activity against SARS-CoV-2 target can be accurately predicted by CoV-DTI from the top 200 replication drug candidates, with a better performance compared to DTINet. We first conducted a pilot experimental test in vitro (Methods) on

Results

Conclusion