Here we show how to do drug repurposing using pretrained knowledge graph embedding of DRKG.
COVID-19_drug_repurposing.ipynb shows how to do drug repurposing for Covid-19 by predicting links between the disease entities and the drug entitites in the DRKG. The target disease entities are listed in the notebook and the candidate drug entities are listed in infer_drug.tsv. The drugs are all from Drugbank and we exclude drugs with molecule weight less than 250 daltons which results in 8104 candidates. Two edge types are chosen here: Hetionet::CtD::Compound:Disease' and 'GNBR::T::Compound:Disease, which represent the treatment relationship between a certain drug for a disease. To evaluate the repurposed drugs, we compare them with the clinical drugs as there is no treatment for Covid-19 right now. The list of clinical drugs are shown in COVID19_clinical_trial_drugs.tsv which is collected from http://www.covid19-trials.com/.
COVID-19_drug_repurposing_via_genes.ipynb shows how to do drug repurposing for Covid-19 by predicting links between the disease related host gene entities and the drug entities in the DRKG. The target host gene entities are listed in covid19-host-genes.tsv and coronavirus-related-host-genes.tsv. The drugs are all from Drugbank and we exclude drugs with molecule weight less than 250 daltons which results in 8104 candidates. The edge type used here is GNBR::N::Compound:Gene. One can also use DRUGBANK::target::Compound:Gene, DGIDB::INHIBITOR::Gene:Compound or combination of them. To evaluate the repurposed drugs, we also compare them with the clinical drugs.