Background Leveraging previously identified viral interactions with human host proteins, we apply a machine learning-based approach to connect SARS-CoV-2 viral proteins to relevant host biological functions, diseases, and pathways in a large-scale knowledge graph derived from the biomedical literature. Our goal is to explore how SARS-CoV-2 could interfere with various host cell functions, and to identify drug targets amongst the host genes that could potentially be modulated against COVID-19 by repurposing existing drugs. The machine learning model employed here involves gene embeddings that leverage causal gene expression signatures curated from literature. In contrast to other network-based approaches for drug repurposing, our approach explicitly takes the direction of effects into account, distinguishing between activation and inhibition. Results We have constructed 70 networks connecting SARS-CoV-2 viral proteins to various biological functions, diseases, and pathways reflecting viral biology, clinical observations, and co-morbidities in the context of COVID-19. Results are presented in the form of interactive network visualizations through a web interface, the Coronavirus Network Explorer (CNE), that allows exploration of underlying experimental evidence. We find that existing drugs targeting genes in those networks are strongly enriched in the set of drugs that are already in clinical trials against COVID-19. Conclusions The approach presented here can identify biologically plausible hypotheses for COVID-19 pathogenesis, explicitly connected to the immunological, virological and pathological observations seen in SARS-CoV-2 infected patients. The discovery of repurposable drugs is driven by prior knowledge of relevant functional endpoints that reflect known viral biology or clinical observations, therefore suggesting potential mechanisms of action. We believe that the CNE offers relevant insights that go beyond more conventional network approaches, and can be a valuable tool for drug repurposing. The CNE is available at https://digitalinsights.qiagen.com/coronavirus-network-explorer . Supplementary Information The online version contains supplementary material available at 10.1186/s12859-021-04148-x.
【저자키워드】 COVID-19, Drug repurposing, network biology, Knowledge graph, 【초록키워드】 Biological functions, SARS-CoV-2, clinical trial, Diseases, knowledge, drugs, Proteins, drug, Protein, COVID-19 pathogenesis, pathway, co-morbidity, drug target, network, clinical observations, Interaction, host cell, observation, Activation, Virological, Endpoint, supplementary material, potential mechanism, SARS-CoV-2 infected patients, approaches, human host, functions, gene expression signature, offer, experimental evidence, Host, Effect, approach, immunological, SARS-CoV-2 viral, Result, identify, functional, interfere, driven by, host gene, hypothese, drugs targeting, modulated, curated, 【제목키워드】 SARS-CoV-2, knowledge, network, host cell, Effect,