{"id":"W2104521207","doi":"10.1139/cjc-2015-0039","title":"Pharmacophore modeling and molecular docking studies of acridines as potential DPP-IV inhibitors","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Chemistry","topic":"Diabetes Treatment and Management","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Jordan","keywords":"Pharmacophore; Chemistry; Docking (animal); Dipeptidyl peptidase; Pharmacology; Combinatorial chemistry; Stereochemistry; Isostere; Dipeptidyl peptidase-4; Molecular model; Biochemistry; Glucagon-like peptide-1; Enzyme; Type 2 diabetes; Diabetes mellitus; Endocrinology","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":[0.0004114531,0.001244118,0.00131861,0.0004684178,0.0002898202,0.0006152786,0.0008220714,0.0005158163,0.002985029],"category_scores_gemma":[0.0005353645,0.0003674368,0.0008888999,0.0007424505,0.0001960914,0.0003941403,0.000349533,0.0006172562,0.0004710565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005786811,"about_ca_system_score_gemma":0.0006826766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006800655,"about_ca_topic_score_gemma":0.00690772,"domain_scores_codex":[0.9997854,0.00008027923,0.00000893801,0.00002623269,0.00005389596,0.00004538507],"domain_scores_gemma":[0.9998413,0.00007063378,0.00003047146,0.000008477344,0.00002799345,0.00002095249],"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":[0.000866066,0.0004945428,0.001594018,0.0005537005,0.0001777999,0.0004918948,0.00006304427,0.9506167,0.02917967,0.00289276,0.001295176,0.01177457],"study_design_scores_gemma":[0.0002868376,0.001074482,0.0006750041,0.00004735044,0.0001683403,0.00009222354,0.00008433999,0.9810858,0.01346915,0.0005189333,0.002443779,0.00005381825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9474071,0.006429362,0.02710424,0.0005937715,0.00009733701,0.0002082119,0.001892835,0.0004904895,0.01577665],"genre_scores_gemma":[0.97487,0.003324796,0.01826296,0.0001140782,0.00001243192,0.0001249527,0.001150607,0.00006431843,0.002075864],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006800655,"threshold_uncertainty_score":0.01352215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02587336260101997,"score_gpt":0.2832273578712312,"score_spread":0.2573539952702112,"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."}}