PMC:7796052 / 13123-13953 JSONTXT

{"project":"LitCovid-sentences","denotations":[{"id":"T85","span":{"begin":0,"end":4},"obj":"Sentence"},{"id":"T86","span":{"begin":5,"end":26},"obj":"Sentence"},{"id":"T87","span":{"begin":27,"end":258},"obj":"Sentence"},{"id":"T88","span":{"begin":259,"end":422},"obj":"Sentence"},{"id":"T89","span":{"begin":423,"end":554},"obj":"Sentence"},{"id":"T90","span":{"begin":555,"end":830},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"3.1. Computational Methods\nVitual screening on the DrugBank [23] was carried out using the Molecular Operating Environment (MOE) program [28], using four common points of the BK B1 and B2 pharmacophores described previously [25,26] that were used as a query. Previously, a 3D DrugBank database containing the 3D structure, together with a set of conformations of each molecule, was constructed as explained elsewhere [24]. Virtual screening was carried out on the subset of molecules with molecular weight between 200 and 600 (a total of 1703 molecules). Hits identified in the screening process were docked in the 3D models of the B1 and B2 bradykinin receptors, using a set of unique conformations resulting from thorough conformational searches for the diverse ligands studied and rank ordered by means of the MOE program [28]."}