{"id":"W4390012038","doi":"10.1080/07391102.2023.2291165","title":"Inhibition potential of natural flavonoids against selected omicron (B.1.19) mutations in the spike receptor binding domain of SARS-CoV-2: a molecular modeling approach","year":2023,"lang":"en","type":"article","venue":"Journal of Biomolecular Structure and Dynamics","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Canadian Armed Forces; Dalhousie University","funders":"Research Nova Scotia; Canadian Institutes of Health Research; Dalhousie University; Genome Canada; Dalhousie Medical Research Foundation","keywords":"Molecular dynamics; Chemistry; Docking (animal); Virtual screening; Stereochemistry; Hyperoside; Computational biology; Biochemistry; Quercetin; Biology; Computational chemistry; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007042417,0.0001561767,0.0002843724,0.0006630365,0.00006992691,0.0000783143,0.0003865576,0.00009632911,1.879856e-7],"category_scores_gemma":[0.00009977273,0.0001241138,0.0001405486,0.001787473,0.0000742319,0.0002732478,0.0001181626,0.0003084347,1.558255e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008040967,"about_ca_system_score_gemma":0.0001802285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000128943,"about_ca_topic_score_gemma":0.000005357649,"domain_scores_codex":[0.9981581,0.0003489397,0.0006182607,0.0002056769,0.0004797935,0.0001892509],"domain_scores_gemma":[0.9989979,0.00007475734,0.0004349276,0.0001845565,0.0002739753,0.00003388048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002868627,0.00002882043,0.00002628622,0.00004552107,0.0000427905,0.00004884147,0.0008906791,0.1849916,0.8096503,0.002622231,0.000006458211,0.001617723],"study_design_scores_gemma":[0.0006181798,0.00007785287,0.0002893145,0.00005656328,0.00002425799,0.0001552856,0.0003576278,0.9312012,0.05714345,0.009950365,0.000001130739,0.0001247959],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5275472,0.00007785711,0.4720383,0.0001287778,0.00009291664,0.00008400226,0.00001866434,0.000006052919,0.000006199144],"genre_scores_gemma":[0.8739807,0.00001602913,0.1258318,0.00006689569,0.00002252046,0.000001016453,0.00007034844,0.00001033529,3.830417e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7525069,"threshold_uncertainty_score":0.5061214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01112473303369938,"score_gpt":0.272537657031099,"score_spread":0.2614129239973996,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}