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LitCovid-PubTator

LitCovid-PD-FMA-UBERON

LitCovid-PD-MONDO

LitCovid-PD-CLO

LitCovid-PD-CHEBI

LitCovid-PD-GO-BP

{"project":"LitCovid-PD-GO-BP","denotations":[{"id":"T23","span":{"begin":299,"end":314},"obj":"http://purl.obolibrary.org/obo/GO_0010467"},{"id":"T24","span":{"begin":2789,"end":2805},"obj":"http://purl.obolibrary.org/obo/GO_0007623"},{"id":"T25","span":{"begin":2799,"end":2805},"obj":"http://purl.obolibrary.org/obo/GO_0048511"},{"id":"T26","span":{"begin":2806,"end":2811},"obj":"http://purl.obolibrary.org/obo/GO_0030431"}],"text":"To further validate the 135 repurposable drugs against HCoVs, we first performed gene set enrichment analysis (GSEA) using transcriptome data of MERS-CoV and SARS-CoV infected host cells (see Methods). These transcriptome data were used as gene signatures for HCoVs. Additionally, we downloaded the gene expression data of drug-treated human cell lines from the Connectivity Map (CMAP) database36 to obtain drug–gene signatures. We calculated a GSEA score (see Methods) for each drug and used this score as an indication of bioinformatics validation of the 135 drugs. Specifically, an enrichment score (ES) was calculated for each HCoV data set, and ES \u003e 0 and P \u003c 0.05 (permutation test) was used as cut-off for a significant association of gene signatures between a drug and a specific HCoV data set. The GSEA score, ranging from 0 to 3, is the number of data sets that met these criteria for a specific drug. Mesalazine (an approved drug for inflammatory bowel disease), sirolimus (an approved immunosuppressive drug), and equilin (an approved agonist of the estrogen receptor for menopausal symptoms) achieved the highest GSEA scores of 3, followed by paroxetine and melatonin with GSEA scores of 2. We next selected 16 high-confidence repurposable drugs (Fig. 5a and Table 1) against HCoVs using subject matter expertise based on a combination of factors: (i) strength of the network-predicted associations (a smaller network proximity score in Supplementary Table S4); (ii) validation by GSEA analyses; (iii) literature-reported antiviral evidence, and (iv) fewer clinically reported side effects. Specifically, we showcased several selected repurposable drugs with literature-reported antiviral evidence as below.\nFig. 5 A discovered drug-protein-HCoV network for 16 candidate repurposable drugs.\na Network-predicted evidence and gene set enrichment analysis (GSEA) scores for 16 potential repurposable drugs for HCoVs. The overall connectivity of the top drug candidates to the HCoV-associated proteins was examined. Most of these drugs indirectly target HCoV-associated proteins via the human protein–protein interaction networks. All the drug–target-HCoV-associated protein connections were examined, and those proteins with at least five connections are shown. The box heights for the proteins indicate the number of connections. GSEA scores for eight drugs were not available (NA) due to the lack of transcriptome profiles for the drugs. b–e Inferred mechanism-of-action networks for four selected drugs: b toremifene (first-generation nonsteroidal-selective estrogen receptor modulator), c irbesartan (an angiotensin receptor blocker), d mercaptopurine (an antimetabolite antineoplastic agent with immunosuppressant properties), and e melatonin (a biogenic amine for treating circadian rhythm sleep disorders).\nTable 1 Top 16 network-predicted repurposable drugs with literature-derived antiviral evidence.\nHBV hepatitis B virus, HCV hepatitis C virus, HDV hepatitis delta virus, EBOV Ebola viruses, ZEBOV-GP Zaire Ebola virus glycoprotein, HIV human immunodeficiency virus, EBV Epstein-Barr virus, ANDV Andes orthohantavirus, EMCV encephalomyocarditis virus, FECV feline enteric coronavirus, RSV respiratory syncytial virus, EV71 enterovirus 71, HSV-1 and -2 herpes simplex viruses, CVB4 Coxsackievirus B4."}

LitCovid-PD-HP

{"project":"LitCovid-PD-HP","denotations":[{"id":"T2","span":{"begin":945,"end":971},"obj":"Phenotype"},{"id":"T3","span":{"begin":2924,"end":2933},"obj":"Phenotype"},{"id":"T4","span":{"begin":2947,"end":2956},"obj":"Phenotype"},{"id":"T5","span":{"begin":2970,"end":2979},"obj":"Phenotype"},{"id":"T6","span":{"begin":3064,"end":3080},"obj":"Phenotype"}],"attributes":[{"id":"A2","pred":"hp_id","subj":"T2","obj":"http://purl.obolibrary.org/obo/HP_0002037"},{"id":"A3","pred":"hp_id","subj":"T3","obj":"http://purl.obolibrary.org/obo/HP_0012115"},{"id":"A4","pred":"hp_id","subj":"T4","obj":"http://purl.obolibrary.org/obo/HP_0012115"},{"id":"A5","pred":"hp_id","subj":"T5","obj":"http://purl.obolibrary.org/obo/HP_0012115"},{"id":"A6","pred":"hp_id","subj":"T6","obj":"http://purl.obolibrary.org/obo/HP_0002721"}],"text":"To further validate the 135 repurposable drugs against HCoVs, we first performed gene set enrichment analysis (GSEA) using transcriptome data of MERS-CoV and SARS-CoV infected host cells (see Methods). These transcriptome data were used as gene signatures for HCoVs. Additionally, we downloaded the gene expression data of drug-treated human cell lines from the Connectivity Map (CMAP) database36 to obtain drug–gene signatures. We calculated a GSEA score (see Methods) for each drug and used this score as an indication of bioinformatics validation of the 135 drugs. Specifically, an enrichment score (ES) was calculated for each HCoV data set, and ES \u003e 0 and P \u003c 0.05 (permutation test) was used as cut-off for a significant association of gene signatures between a drug and a specific HCoV data set. The GSEA score, ranging from 0 to 3, is the number of data sets that met these criteria for a specific drug. Mesalazine (an approved drug for inflammatory bowel disease), sirolimus (an approved immunosuppressive drug), and equilin (an approved agonist of the estrogen receptor for menopausal symptoms) achieved the highest GSEA scores of 3, followed by paroxetine and melatonin with GSEA scores of 2. We next selected 16 high-confidence repurposable drugs (Fig. 5a and Table 1) against HCoVs using subject matter expertise based on a combination of factors: (i) strength of the network-predicted associations (a smaller network proximity score in Supplementary Table S4); (ii) validation by GSEA analyses; (iii) literature-reported antiviral evidence, and (iv) fewer clinically reported side effects. Specifically, we showcased several selected repurposable drugs with literature-reported antiviral evidence as below.\nFig. 5 A discovered drug-protein-HCoV network for 16 candidate repurposable drugs.\na Network-predicted evidence and gene set enrichment analysis (GSEA) scores for 16 potential repurposable drugs for HCoVs. The overall connectivity of the top drug candidates to the HCoV-associated proteins was examined. Most of these drugs indirectly target HCoV-associated proteins via the human protein–protein interaction networks. All the drug–target-HCoV-associated protein connections were examined, and those proteins with at least five connections are shown. The box heights for the proteins indicate the number of connections. GSEA scores for eight drugs were not available (NA) due to the lack of transcriptome profiles for the drugs. b–e Inferred mechanism-of-action networks for four selected drugs: b toremifene (first-generation nonsteroidal-selective estrogen receptor modulator), c irbesartan (an angiotensin receptor blocker), d mercaptopurine (an antimetabolite antineoplastic agent with immunosuppressant properties), and e melatonin (a biogenic amine for treating circadian rhythm sleep disorders).\nTable 1 Top 16 network-predicted repurposable drugs with literature-derived antiviral evidence.\nHBV hepatitis B virus, HCV hepatitis C virus, HDV hepatitis delta virus, EBOV Ebola viruses, ZEBOV-GP Zaire Ebola virus glycoprotein, HIV human immunodeficiency virus, EBV Epstein-Barr virus, ANDV Andes orthohantavirus, EMCV encephalomyocarditis virus, FECV feline enteric coronavirus, RSV respiratory syncytial virus, EV71 enterovirus 71, HSV-1 and -2 herpes simplex viruses, CVB4 Coxsackievirus B4."}

LitCovid-sentences

{"project":"LitCovid-sentences","denotations":[{"id":"T110","span":{"begin":0,"end":201},"obj":"Sentence"},{"id":"T111","span":{"begin":202,"end":266},"obj":"Sentence"},{"id":"T112","span":{"begin":267,"end":428},"obj":"Sentence"},{"id":"T113","span":{"begin":429,"end":567},"obj":"Sentence"},{"id":"T114","span":{"begin":568,"end":802},"obj":"Sentence"},{"id":"T115","span":{"begin":803,"end":911},"obj":"Sentence"},{"id":"T116","span":{"begin":912,"end":1203},"obj":"Sentence"},{"id":"T117","span":{"begin":1204,"end":1603},"obj":"Sentence"},{"id":"T118","span":{"begin":1604,"end":1720},"obj":"Sentence"},{"id":"T119","span":{"begin":1721,"end":1803},"obj":"Sentence"},{"id":"T120","span":{"begin":1804,"end":1926},"obj":"Sentence"},{"id":"T121","span":{"begin":1927,"end":2024},"obj":"Sentence"},{"id":"T122","span":{"begin":2025,"end":2139},"obj":"Sentence"},{"id":"T123","span":{"begin":2140,"end":2271},"obj":"Sentence"},{"id":"T124","span":{"begin":2272,"end":2340},"obj":"Sentence"},{"id":"T125","span":{"begin":2341,"end":2823},"obj":"Sentence"},{"id":"T126","span":{"begin":2824,"end":2919},"obj":"Sentence"},{"id":"T127","span":{"begin":2920,"end":3320},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"To further validate the 135 repurposable drugs against HCoVs, we first performed gene set enrichment analysis (GSEA) using transcriptome data of MERS-CoV and SARS-CoV infected host cells (see Methods). These transcriptome data were used as gene signatures for HCoVs. Additionally, we downloaded the gene expression data of drug-treated human cell lines from the Connectivity Map (CMAP) database36 to obtain drug–gene signatures. We calculated a GSEA score (see Methods) for each drug and used this score as an indication of bioinformatics validation of the 135 drugs. Specifically, an enrichment score (ES) was calculated for each HCoV data set, and ES \u003e 0 and P \u003c 0.05 (permutation test) was used as cut-off for a significant association of gene signatures between a drug and a specific HCoV data set. The GSEA score, ranging from 0 to 3, is the number of data sets that met these criteria for a specific drug. Mesalazine (an approved drug for inflammatory bowel disease), sirolimus (an approved immunosuppressive drug), and equilin (an approved agonist of the estrogen receptor for menopausal symptoms) achieved the highest GSEA scores of 3, followed by paroxetine and melatonin with GSEA scores of 2. We next selected 16 high-confidence repurposable drugs (Fig. 5a and Table 1) against HCoVs using subject matter expertise based on a combination of factors: (i) strength of the network-predicted associations (a smaller network proximity score in Supplementary Table S4); (ii) validation by GSEA analyses; (iii) literature-reported antiviral evidence, and (iv) fewer clinically reported side effects. Specifically, we showcased several selected repurposable drugs with literature-reported antiviral evidence as below.\nFig. 5 A discovered drug-protein-HCoV network for 16 candidate repurposable drugs.\na Network-predicted evidence and gene set enrichment analysis (GSEA) scores for 16 potential repurposable drugs for HCoVs. The overall connectivity of the top drug candidates to the HCoV-associated proteins was examined. Most of these drugs indirectly target HCoV-associated proteins via the human protein–protein interaction networks. All the drug–target-HCoV-associated protein connections were examined, and those proteins with at least five connections are shown. The box heights for the proteins indicate the number of connections. GSEA scores for eight drugs were not available (NA) due to the lack of transcriptome profiles for the drugs. b–e Inferred mechanism-of-action networks for four selected drugs: b toremifene (first-generation nonsteroidal-selective estrogen receptor modulator), c irbesartan (an angiotensin receptor blocker), d mercaptopurine (an antimetabolite antineoplastic agent with immunosuppressant properties), and e melatonin (a biogenic amine for treating circadian rhythm sleep disorders).\nTable 1 Top 16 network-predicted repurposable drugs with literature-derived antiviral evidence.\nHBV hepatitis B virus, HCV hepatitis C virus, HDV hepatitis delta virus, EBOV Ebola viruses, ZEBOV-GP Zaire Ebola virus glycoprotein, HIV human immunodeficiency virus, EBV Epstein-Barr virus, ANDV Andes orthohantavirus, EMCV encephalomyocarditis virus, FECV feline enteric coronavirus, RSV respiratory syncytial virus, EV71 enterovirus 71, HSV-1 and -2 herpes simplex viruses, CVB4 Coxsackievirus B4."}

2_test

{"project":"2_test","denotations":[{"id":"32194980-17008526-19614185","span":{"begin":394,"end":396},"obj":"17008526"}],"text":"To further validate the 135 repurposable drugs against HCoVs, we first performed gene set enrichment analysis (GSEA) using transcriptome data of MERS-CoV and SARS-CoV infected host cells (see Methods). These transcriptome data were used as gene signatures for HCoVs. Additionally, we downloaded the gene expression data of drug-treated human cell lines from the Connectivity Map (CMAP) database36 to obtain drug–gene signatures. We calculated a GSEA score (see Methods) for each drug and used this score as an indication of bioinformatics validation of the 135 drugs. Specifically, an enrichment score (ES) was calculated for each HCoV data set, and ES \u003e 0 and P \u003c 0.05 (permutation test) was used as cut-off for a significant association of gene signatures between a drug and a specific HCoV data set. The GSEA score, ranging from 0 to 3, is the number of data sets that met these criteria for a specific drug. Mesalazine (an approved drug for inflammatory bowel disease), sirolimus (an approved immunosuppressive drug), and equilin (an approved agonist of the estrogen receptor for menopausal symptoms) achieved the highest GSEA scores of 3, followed by paroxetine and melatonin with GSEA scores of 2. We next selected 16 high-confidence repurposable drugs (Fig. 5a and Table 1) against HCoVs using subject matter expertise based on a combination of factors: (i) strength of the network-predicted associations (a smaller network proximity score in Supplementary Table S4); (ii) validation by GSEA analyses; (iii) literature-reported antiviral evidence, and (iv) fewer clinically reported side effects. Specifically, we showcased several selected repurposable drugs with literature-reported antiviral evidence as below.\nFig. 5 A discovered drug-protein-HCoV network for 16 candidate repurposable drugs.\na Network-predicted evidence and gene set enrichment analysis (GSEA) scores for 16 potential repurposable drugs for HCoVs. The overall connectivity of the top drug candidates to the HCoV-associated proteins was examined. Most of these drugs indirectly target HCoV-associated proteins via the human protein–protein interaction networks. All the drug–target-HCoV-associated protein connections were examined, and those proteins with at least five connections are shown. The box heights for the proteins indicate the number of connections. GSEA scores for eight drugs were not available (NA) due to the lack of transcriptome profiles for the drugs. b–e Inferred mechanism-of-action networks for four selected drugs: b toremifene (first-generation nonsteroidal-selective estrogen receptor modulator), c irbesartan (an angiotensin receptor blocker), d mercaptopurine (an antimetabolite antineoplastic agent with immunosuppressant properties), and e melatonin (a biogenic amine for treating circadian rhythm sleep disorders).\nTable 1 Top 16 network-predicted repurposable drugs with literature-derived antiviral evidence.\nHBV hepatitis B virus, HCV hepatitis C virus, HDV hepatitis delta virus, EBOV Ebola viruses, ZEBOV-GP Zaire Ebola virus glycoprotein, HIV human immunodeficiency virus, EBV Epstein-Barr virus, ANDV Andes orthohantavirus, EMCV encephalomyocarditis virus, FECV feline enteric coronavirus, RSV respiratory syncytial virus, EV71 enterovirus 71, HSV-1 and -2 herpes simplex viruses, CVB4 Coxsackievirus B4."}

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PMC:7073332 / 18032-21352 JSON TXT