{"id":"W2059097089","doi":"10.1021/jm201098n","title":"Targeting the Binding Function 3 (BF3) Site of the Human Androgen Receptor through Virtual Screening.","year":2011,"lang":"en","type":"article","venue":"Journal of Medicinal Chemistry","topic":"Prostate Cancer Treatment and Research","field":"Medicine","cited_by":147,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; Canadian Institutes of Health Research","keywords":"Androgen receptor; In silico; Mechanism of action; Virtual screening; Prostate cancer; Chemistry; Antiandrogen; Mechanism (biology); Computational biology; Cytotoxicity; Function (biology); Androgen; Drug; Binding site; Drug discovery; Pharmacology; Cancer research; Cancer; Biochemistry; Biology; In vitro; Cell biology; Genetics; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004506347,0.000861011,0.0008858155,0.0004750551,0.0002920105,0.0005033046,0.0005370053,0.0002936253,0.001692823],"category_scores_gemma":[0.000464344,0.0001617377,0.0007384539,0.000440479,0.0002385458,0.0002419392,0.0004502694,0.0004790828,0.0003419828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003136134,"about_ca_system_score_gemma":0.0005382277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001377435,"about_ca_topic_score_gemma":0.002348627,"domain_scores_codex":[0.9997887,0.00009078928,0.000007797012,0.00002435104,0.00005688057,0.00003163061],"domain_scores_gemma":[0.9999127,0.0000466587,0.00001235063,0.000005551111,0.000008125166,0.00001452701],"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":[0.003806526,0.002132884,0.008467825,0.002778299,0.0009294991,0.001883515,0.0002442976,0.2589862,0.4967284,0.007195073,0.01165502,0.2051924],"study_design_scores_gemma":[0.002227256,0.01024099,0.01017047,0.0002206206,0.001335969,0.003974407,0.0002891452,0.5013396,0.396367,0.008828592,0.0647693,0.0002366086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.903299,0.01353708,0.05487498,0.001199548,0.0001990059,0.001230444,0.004363251,0.001918694,0.01937792],"genre_scores_gemma":[0.9487404,0.004967046,0.03969177,0.0003004679,0.00001681616,0.0002754938,0.003145041,0.00006734547,0.002795525],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001692823,"threshold_uncertainty_score":0.005663097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04831820523702504,"score_gpt":0.3040674497260342,"score_spread":0.2557492444890092,"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."}}