PMC:7299399 / 47145-47404 JSONTXT

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T428","span":{"begin":136,"end":137},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T429","span":{"begin":230,"end":236},"obj":"http://purl.obolibrary.org/obo/CLO_0001658"}],"text":"Combining in silico tools such as molecular docking, molecular dynamics, and computational chemistry with large drug databases provides a great advantage in selecting “possible candidates” from among thousands of pharmaceutically active substances (Figure 3)."}

{"project":"LitCovid-PD-CHEBI","denotations":[{"id":"T396","span":{"begin":112,"end":116},"obj":"Chemical"}],"attributes":[{"id":"A396","pred":"chebi_id","subj":"T396","obj":"http://purl.obolibrary.org/obo/CHEBI_23888"}],"text":"Combining in silico tools such as molecular docking, molecular dynamics, and computational chemistry with large drug databases provides a great advantage in selecting “possible candidates” from among thousands of pharmaceutically active substances (Figure 3)."}

{"project":"LitCovid-sentences","denotations":[{"id":"T182","span":{"begin":0,"end":259},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"Combining in silico tools such as molecular docking, molecular dynamics, and computational chemistry with large drug databases provides a great advantage in selecting “possible candidates” from among thousands of pharmaceutically active substances (Figure 3)."}