{"id":"W1965912206","doi":"10.6000/1927-5951.2015.05.01.7","title":"In Silico Design &amp; Development of Some Selected Flavonols Against Beta–Glucuronidase Inhibitory Activity","year":2015,"lang":"en","type":"article","venue":"Journal of Pharmacy and Nutrition Sciences","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Chemistry; Docking (animal); In silico; Naringenin; Flavonols; Enzyme; Ligand (biochemistry); Biochemistry; Binding site; Active site; Stereochemistry; Glucuronidase; Hydrogen bond; Quercetin; Flavonoid; Receptor; Organic chemistry; Medicine; Antioxidant; Molecule","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003085486,0.0006069717,0.0006650786,0.0003821203,0.0002233297,0.0005049784,0.0005158411,0.0004069574,0.00390628],"category_scores_gemma":[0.000342904,0.0002421728,0.0008292585,0.0002222635,0.0001225155,0.0001741691,0.0001831662,0.0002794655,0.0006178604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003314198,"about_ca_system_score_gemma":0.0007102391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001686003,"about_ca_topic_score_gemma":0.00263187,"domain_scores_codex":[0.9998969,0.00002933213,0.000005713189,0.00002243339,0.00002676491,0.0000188414],"domain_scores_gemma":[0.9999157,0.00003411294,0.00001599154,0.000005076251,0.00001874844,0.0000103682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001561256,0.001324388,0.009552794,0.002423357,0.0005499421,0.0009948141,0.0001039122,0.5530751,0.2857742,0.005221082,0.004975752,0.1344435],"study_design_scores_gemma":[0.0005269538,0.002817979,0.002364555,0.00006683251,0.0004218997,0.000398644,0.00006153958,0.8367541,0.1374918,0.001185157,0.01787244,0.00003802097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.722138,0.006074072,0.2407588,0.0008286986,0.0001728617,0.0007598303,0.003124271,0.003754108,0.02238943],"genre_scores_gemma":[0.8467249,0.002680435,0.1413956,0.0002383315,0.00001831447,0.0004427623,0.002833542,0.0001333151,0.00553274],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00390628,"threshold_uncertainty_score":0.01306778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.139499964993425,"score_gpt":0.3891404885886971,"score_spread":0.2496405235952721,"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."}}