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LitCovid-PubTator

LitCovid-PD-FMA-UBERON

{"project":"LitCovid-PD-FMA-UBERON","denotations":[{"id":"T76","span":{"begin":143,"end":151},"obj":"Body_part"},{"id":"T77","span":{"begin":397,"end":405},"obj":"Body_part"},{"id":"T78","span":{"begin":497,"end":504},"obj":"Body_part"},{"id":"T79","span":{"begin":505,"end":512},"obj":"Body_part"},{"id":"T80","span":{"begin":995,"end":1002},"obj":"Body_part"},{"id":"T81","span":{"begin":1105,"end":1112},"obj":"Body_part"},{"id":"T82","span":{"begin":1872,"end":1880},"obj":"Body_part"},{"id":"T83","span":{"begin":2006,"end":2014},"obj":"Body_part"},{"id":"T84","span":{"begin":2155,"end":2163},"obj":"Body_part"},{"id":"T85","span":{"begin":2820,"end":2828},"obj":"Body_part"},{"id":"T86","span":{"begin":3168,"end":3176},"obj":"Body_part"}],"attributes":[{"id":"A76","pred":"fma_id","subj":"T76","obj":"http://purl.org/sig/ont/fma/fma67257"},{"id":"A77","pred":"fma_id","subj":"T77","obj":"http://purl.org/sig/ont/fma/fma67257"},{"id":"A78","pred":"fma_id","subj":"T78","obj":"http://purl.org/sig/ont/fma/fma67257"},{"id":"A79","pred":"fma_id","subj":"T79","obj":"http://purl.org/sig/ont/fma/fma67257"},{"id":"A80","pred":"fma_id","subj":"T80","obj":"http://purl.org/sig/ont/fma/fma67257"},{"id":"A81","pred":"fma_id","subj":"T81","obj":"http://purl.org/sig/ont/fma/fma67257"},{"id":"A82","pred":"fma_id","subj":"T82","obj":"http://purl.org/sig/ont/fma/fma67257"},{"id":"A83","pred":"fma_id","subj":"T83","obj":"http://purl.org/sig/ont/fma/fma67257"},{"id":"A84","pred":"fma_id","subj":"T84","obj":"http://purl.org/sig/ont/fma/fma67257"},{"id":"A85","pred":"fma_id","subj":"T85","obj":"http://purl.org/sig/ont/fma/fma67257"},{"id":"A86","pred":"fma_id","subj":"T86","obj":"http://purl.org/sig/ont/fma/fma67257"}],"text":"Network-based drug repurposing for HCoVs\nThe basis for the proposed network-based drug repurposing methodologies rests on the notions that the proteins that associate with and functionally govern viral infection are localized in the corresponding subnetwork (Fig. 1a) within the comprehensive human interactome network. For a drug with multiple targets to be effective against an HCoV, its target proteins should be within or in the immediate vicinity of the corresponding subnetwork in the human protein–protein interactome (Fig. 1), as we demonstrated in multiple diseases13,22,23,28 using this network-based strategy. We used a state-of-the-art network proximity measure to quantify the relationship between HCoV-specific subnetwork (Fig. 3a) and drug targets in the human interactome. We constructed a drug–target network by assembling target information for more than 2000 FDA-approved or experimental drugs (see Materials and methods). To improve the quality and completeness of the human protein interactome network, we integrated PPIs with five types of experimental data: (1) binary PPIs from 3D protein structures; (2) binary PPIs from unbiased high-throughput yeast-two-hybrid assays; (3) experimentally identified kinase-substrate interactions; (4) signaling networks derived from experimental data; and (5) literature-derived PPIs with various experimental evidence (see Materials and methods). We used a Z-score (Z) measure and permutation test to reduce the study bias in network proximity analyses (including hub nodes in the human interactome network by literature-derived PPI data bias) as described in our recent studies13,28.\nIn total, we computationally identified 135 drugs that were associated (Z \u003c −1.5 and P \u003c 0.05, permutation test) with the HCoV–host interactome (Fig. 4a, Supplementary Tables S4 and 5). To validate bias of the pooled cellular proteins from six CoVs, we further calculated the network proximities of all the drugs for four CoVs with a large number of know host proteins, including SARS-CoV, MERS-CoV, IBV, and MHV, separately. We found that the Z-scores showed consistency among the pooled 119 HCoV-associated proteins and other four individual CoVs (Fig. 4b). The Pearson correlation coefficients of the proximities of all the drugs for the pooled HCoV are 0.926 vs. SARS-CoV (P \u003c 0.001, t distribution), 0.503 vs. MERS-CoV (P \u003c 0.001), 0.694 vs. IBV (P \u003c 0.001), and 0.829 vs. MHV (P \u003c 0.001). These network proximity analyses offer putative repurposable candidates for potential prevention and treatment of HCoVs.\nFig. 4 A discovered drug-HCoV network.\na A subnetwork highlighting network-predicted drug-HCoV associations connecting 135 drugs and HCoVs. From the 2938 drugs evaluated, 135 ones achieved significant proximities between drug targets and the HCoV-associated proteins in the human interactome network. Drugs are colored by their first-level of the Anatomical Therapeutic Chemical (ATC) classification system code. b A heatmap highlighting network proximity values for SARS-CoV, MERS-CoV, IBV, and MHV, respectively. Color key denotes network proximity (Z-score) between drug targets and the HCoV-associated proteins in the human interactome network. P value was computed by permutation test."}

LitCovid-PD-MONDO

{"project":"LitCovid-PD-MONDO","denotations":[{"id":"T64","span":{"begin":196,"end":211},"obj":"Disease"},{"id":"T65","span":{"begin":202,"end":211},"obj":"Disease"},{"id":"T66","span":{"begin":2026,"end":2034},"obj":"Disease"},{"id":"T67","span":{"begin":2313,"end":2321},"obj":"Disease"},{"id":"T68","span":{"begin":3029,"end":3037},"obj":"Disease"}],"attributes":[{"id":"A64","pred":"mondo_id","subj":"T64","obj":"http://purl.obolibrary.org/obo/MONDO_0005108"},{"id":"A65","pred":"mondo_id","subj":"T65","obj":"http://purl.obolibrary.org/obo/MONDO_0005550"},{"id":"A66","pred":"mondo_id","subj":"T66","obj":"http://purl.obolibrary.org/obo/MONDO_0005091"},{"id":"A67","pred":"mondo_id","subj":"T67","obj":"http://purl.obolibrary.org/obo/MONDO_0005091"},{"id":"A68","pred":"mondo_id","subj":"T68","obj":"http://purl.obolibrary.org/obo/MONDO_0005091"}],"text":"Network-based drug repurposing for HCoVs\nThe basis for the proposed network-based drug repurposing methodologies rests on the notions that the proteins that associate with and functionally govern viral infection are localized in the corresponding subnetwork (Fig. 1a) within the comprehensive human interactome network. For a drug with multiple targets to be effective against an HCoV, its target proteins should be within or in the immediate vicinity of the corresponding subnetwork in the human protein–protein interactome (Fig. 1), as we demonstrated in multiple diseases13,22,23,28 using this network-based strategy. We used a state-of-the-art network proximity measure to quantify the relationship between HCoV-specific subnetwork (Fig. 3a) and drug targets in the human interactome. We constructed a drug–target network by assembling target information for more than 2000 FDA-approved or experimental drugs (see Materials and methods). To improve the quality and completeness of the human protein interactome network, we integrated PPIs with five types of experimental data: (1) binary PPIs from 3D protein structures; (2) binary PPIs from unbiased high-throughput yeast-two-hybrid assays; (3) experimentally identified kinase-substrate interactions; (4) signaling networks derived from experimental data; and (5) literature-derived PPIs with various experimental evidence (see Materials and methods). We used a Z-score (Z) measure and permutation test to reduce the study bias in network proximity analyses (including hub nodes in the human interactome network by literature-derived PPI data bias) as described in our recent studies13,28.\nIn total, we computationally identified 135 drugs that were associated (Z \u003c −1.5 and P \u003c 0.05, permutation test) with the HCoV–host interactome (Fig. 4a, Supplementary Tables S4 and 5). To validate bias of the pooled cellular proteins from six CoVs, we further calculated the network proximities of all the drugs for four CoVs with a large number of know host proteins, including SARS-CoV, MERS-CoV, IBV, and MHV, separately. We found that the Z-scores showed consistency among the pooled 119 HCoV-associated proteins and other four individual CoVs (Fig. 4b). The Pearson correlation coefficients of the proximities of all the drugs for the pooled HCoV are 0.926 vs. SARS-CoV (P \u003c 0.001, t distribution), 0.503 vs. MERS-CoV (P \u003c 0.001), 0.694 vs. IBV (P \u003c 0.001), and 0.829 vs. MHV (P \u003c 0.001). These network proximity analyses offer putative repurposable candidates for potential prevention and treatment of HCoVs.\nFig. 4 A discovered drug-HCoV network.\na A subnetwork highlighting network-predicted drug-HCoV associations connecting 135 drugs and HCoVs. From the 2938 drugs evaluated, 135 ones achieved significant proximities between drug targets and the HCoV-associated proteins in the human interactome network. Drugs are colored by their first-level of the Anatomical Therapeutic Chemical (ATC) classification system code. b A heatmap highlighting network proximity values for SARS-CoV, MERS-CoV, IBV, and MHV, respectively. Color key denotes network proximity (Z-score) between drug targets and the HCoV-associated proteins in the human interactome network. P value was computed by permutation test."}

LitCovid-PD-CLO

LitCovid-PD-CHEBI

LitCovid-PD-GO-BP

{"project":"LitCovid-PD-GO-BP","denotations":[{"id":"T21","span":{"begin":196,"end":211},"obj":"http://purl.obolibrary.org/obo/GO_0016032"},{"id":"T22","span":{"begin":1261,"end":1270},"obj":"http://purl.obolibrary.org/obo/GO_0023052"}],"text":"Network-based drug repurposing for HCoVs\nThe basis for the proposed network-based drug repurposing methodologies rests on the notions that the proteins that associate with and functionally govern viral infection are localized in the corresponding subnetwork (Fig. 1a) within the comprehensive human interactome network. For a drug with multiple targets to be effective against an HCoV, its target proteins should be within or in the immediate vicinity of the corresponding subnetwork in the human protein–protein interactome (Fig. 1), as we demonstrated in multiple diseases13,22,23,28 using this network-based strategy. We used a state-of-the-art network proximity measure to quantify the relationship between HCoV-specific subnetwork (Fig. 3a) and drug targets in the human interactome. We constructed a drug–target network by assembling target information for more than 2000 FDA-approved or experimental drugs (see Materials and methods). To improve the quality and completeness of the human protein interactome network, we integrated PPIs with five types of experimental data: (1) binary PPIs from 3D protein structures; (2) binary PPIs from unbiased high-throughput yeast-two-hybrid assays; (3) experimentally identified kinase-substrate interactions; (4) signaling networks derived from experimental data; and (5) literature-derived PPIs with various experimental evidence (see Materials and methods). We used a Z-score (Z) measure and permutation test to reduce the study bias in network proximity analyses (including hub nodes in the human interactome network by literature-derived PPI data bias) as described in our recent studies13,28.\nIn total, we computationally identified 135 drugs that were associated (Z \u003c −1.5 and P \u003c 0.05, permutation test) with the HCoV–host interactome (Fig. 4a, Supplementary Tables S4 and 5). To validate bias of the pooled cellular proteins from six CoVs, we further calculated the network proximities of all the drugs for four CoVs with a large number of know host proteins, including SARS-CoV, MERS-CoV, IBV, and MHV, separately. We found that the Z-scores showed consistency among the pooled 119 HCoV-associated proteins and other four individual CoVs (Fig. 4b). The Pearson correlation coefficients of the proximities of all the drugs for the pooled HCoV are 0.926 vs. SARS-CoV (P \u003c 0.001, t distribution), 0.503 vs. MERS-CoV (P \u003c 0.001), 0.694 vs. IBV (P \u003c 0.001), and 0.829 vs. MHV (P \u003c 0.001). These network proximity analyses offer putative repurposable candidates for potential prevention and treatment of HCoVs.\nFig. 4 A discovered drug-HCoV network.\na A subnetwork highlighting network-predicted drug-HCoV associations connecting 135 drugs and HCoVs. From the 2938 drugs evaluated, 135 ones achieved significant proximities between drug targets and the HCoV-associated proteins in the human interactome network. Drugs are colored by their first-level of the Anatomical Therapeutic Chemical (ATC) classification system code. b A heatmap highlighting network proximity values for SARS-CoV, MERS-CoV, IBV, and MHV, respectively. Color key denotes network proximity (Z-score) between drug targets and the HCoV-associated proteins in the human interactome network. P value was computed by permutation test."}

LitCovid-sentences

{"project":"LitCovid-sentences","denotations":[{"id":"T91","span":{"begin":0,"end":40},"obj":"Sentence"},{"id":"T92","span":{"begin":41,"end":319},"obj":"Sentence"},{"id":"T93","span":{"begin":320,"end":620},"obj":"Sentence"},{"id":"T94","span":{"begin":621,"end":788},"obj":"Sentence"},{"id":"T95","span":{"begin":789,"end":941},"obj":"Sentence"},{"id":"T96","span":{"begin":942,"end":1407},"obj":"Sentence"},{"id":"T97","span":{"begin":1408,"end":1645},"obj":"Sentence"},{"id":"T98","span":{"begin":1646,"end":1831},"obj":"Sentence"},{"id":"T99","span":{"begin":1832,"end":2071},"obj":"Sentence"},{"id":"T100","span":{"begin":2072,"end":2205},"obj":"Sentence"},{"id":"T101","span":{"begin":2206,"end":2440},"obj":"Sentence"},{"id":"T102","span":{"begin":2441,"end":2561},"obj":"Sentence"},{"id":"T103","span":{"begin":2562,"end":2600},"obj":"Sentence"},{"id":"T104","span":{"begin":2601,"end":2701},"obj":"Sentence"},{"id":"T105","span":{"begin":2702,"end":2862},"obj":"Sentence"},{"id":"T106","span":{"begin":2863,"end":3076},"obj":"Sentence"},{"id":"T107","span":{"begin":3077,"end":3210},"obj":"Sentence"},{"id":"T108","span":{"begin":3211,"end":3252},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"Network-based drug repurposing for HCoVs\nThe basis for the proposed network-based drug repurposing methodologies rests on the notions that the proteins that associate with and functionally govern viral infection are localized in the corresponding subnetwork (Fig. 1a) within the comprehensive human interactome network. For a drug with multiple targets to be effective against an HCoV, its target proteins should be within or in the immediate vicinity of the corresponding subnetwork in the human protein–protein interactome (Fig. 1), as we demonstrated in multiple diseases13,22,23,28 using this network-based strategy. We used a state-of-the-art network proximity measure to quantify the relationship between HCoV-specific subnetwork (Fig. 3a) and drug targets in the human interactome. We constructed a drug–target network by assembling target information for more than 2000 FDA-approved or experimental drugs (see Materials and methods). To improve the quality and completeness of the human protein interactome network, we integrated PPIs with five types of experimental data: (1) binary PPIs from 3D protein structures; (2) binary PPIs from unbiased high-throughput yeast-two-hybrid assays; (3) experimentally identified kinase-substrate interactions; (4) signaling networks derived from experimental data; and (5) literature-derived PPIs with various experimental evidence (see Materials and methods). We used a Z-score (Z) measure and permutation test to reduce the study bias in network proximity analyses (including hub nodes in the human interactome network by literature-derived PPI data bias) as described in our recent studies13,28.\nIn total, we computationally identified 135 drugs that were associated (Z \u003c −1.5 and P \u003c 0.05, permutation test) with the HCoV–host interactome (Fig. 4a, Supplementary Tables S4 and 5). To validate bias of the pooled cellular proteins from six CoVs, we further calculated the network proximities of all the drugs for four CoVs with a large number of know host proteins, including SARS-CoV, MERS-CoV, IBV, and MHV, separately. We found that the Z-scores showed consistency among the pooled 119 HCoV-associated proteins and other four individual CoVs (Fig. 4b). The Pearson correlation coefficients of the proximities of all the drugs for the pooled HCoV are 0.926 vs. SARS-CoV (P \u003c 0.001, t distribution), 0.503 vs. MERS-CoV (P \u003c 0.001), 0.694 vs. IBV (P \u003c 0.001), and 0.829 vs. MHV (P \u003c 0.001). These network proximity analyses offer putative repurposable candidates for potential prevention and treatment of HCoVs.\nFig. 4 A discovered drug-HCoV network.\na A subnetwork highlighting network-predicted drug-HCoV associations connecting 135 drugs and HCoVs. From the 2938 drugs evaluated, 135 ones achieved significant proximities between drug targets and the HCoV-associated proteins in the human interactome network. Drugs are colored by their first-level of the Anatomical Therapeutic Chemical (ATC) classification system code. b A heatmap highlighting network proximity values for SARS-CoV, MERS-CoV, IBV, and MHV, respectively. Color key denotes network proximity (Z-score) between drug targets and the HCoV-associated proteins in the human interactome network. P value was computed by permutation test."}

2_test

{"project":"2_test","denotations":[{"id":"32194980-30002366-19614179","span":{"begin":574,"end":576},"obj":"30002366"},{"id":"32194980-22589709-19614180","span":{"begin":577,"end":579},"obj":"22589709"},{"id":"32194980-31375661-19614181","span":{"begin":580,"end":582},"obj":"31375661"},{"id":"32194980-30867426-19614182","span":{"begin":583,"end":585},"obj":"30867426"},{"id":"32194980-30002366-19614183","span":{"begin":1639,"end":1641},"obj":"30002366"},{"id":"32194980-30867426-19614184","span":{"begin":1642,"end":1644},"obj":"30867426"}],"text":"Network-based drug repurposing for HCoVs\nThe basis for the proposed network-based drug repurposing methodologies rests on the notions that the proteins that associate with and functionally govern viral infection are localized in the corresponding subnetwork (Fig. 1a) within the comprehensive human interactome network. For a drug with multiple targets to be effective against an HCoV, its target proteins should be within or in the immediate vicinity of the corresponding subnetwork in the human protein–protein interactome (Fig. 1), as we demonstrated in multiple diseases13,22,23,28 using this network-based strategy. We used a state-of-the-art network proximity measure to quantify the relationship between HCoV-specific subnetwork (Fig. 3a) and drug targets in the human interactome. We constructed a drug–target network by assembling target information for more than 2000 FDA-approved or experimental drugs (see Materials and methods). To improve the quality and completeness of the human protein interactome network, we integrated PPIs with five types of experimental data: (1) binary PPIs from 3D protein structures; (2) binary PPIs from unbiased high-throughput yeast-two-hybrid assays; (3) experimentally identified kinase-substrate interactions; (4) signaling networks derived from experimental data; and (5) literature-derived PPIs with various experimental evidence (see Materials and methods). We used a Z-score (Z) measure and permutation test to reduce the study bias in network proximity analyses (including hub nodes in the human interactome network by literature-derived PPI data bias) as described in our recent studies13,28.\nIn total, we computationally identified 135 drugs that were associated (Z \u003c −1.5 and P \u003c 0.05, permutation test) with the HCoV–host interactome (Fig. 4a, Supplementary Tables S4 and 5). To validate bias of the pooled cellular proteins from six CoVs, we further calculated the network proximities of all the drugs for four CoVs with a large number of know host proteins, including SARS-CoV, MERS-CoV, IBV, and MHV, separately. We found that the Z-scores showed consistency among the pooled 119 HCoV-associated proteins and other four individual CoVs (Fig. 4b). The Pearson correlation coefficients of the proximities of all the drugs for the pooled HCoV are 0.926 vs. SARS-CoV (P \u003c 0.001, t distribution), 0.503 vs. MERS-CoV (P \u003c 0.001), 0.694 vs. IBV (P \u003c 0.001), and 0.829 vs. MHV (P \u003c 0.001). These network proximity analyses offer putative repurposable candidates for potential prevention and treatment of HCoVs.\nFig. 4 A discovered drug-HCoV network.\na A subnetwork highlighting network-predicted drug-HCoV associations connecting 135 drugs and HCoVs. From the 2938 drugs evaluated, 135 ones achieved significant proximities between drug targets and the HCoV-associated proteins in the human interactome network. Drugs are colored by their first-level of the Anatomical Therapeutic Chemical (ATC) classification system code. b A heatmap highlighting network proximity values for SARS-CoV, MERS-CoV, IBV, and MHV, respectively. Color key denotes network proximity (Z-score) between drug targets and the HCoV-associated proteins in the human interactome network. P value was computed by permutation test."}

PMC:7073332 / 14737-17989 JSONTXT

Annnotations TAB JSON ListView MergeView

PMC:7073332 / 14737-17989 JSON TXT