{"id":"W2064730478","doi":"10.1021/jm401582c","title":"Targeting Low-Druggability Bromodomains: Fragment Based Screening and Inhibitor Design against the BAZ2B Bromodomain","year":2013,"lang":"en","type":"article","venue":"Journal of Medicinal Chemistry","topic":"Protein Degradation and Inhibitors","field":"Biochemistry, Genetics and Molecular Biology","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; Directorate for Biological Sciences; Canadian Institutes of Health Research; Genome Canada; Wellcome Trust; GlaxoSmithKline; Ontario Ministry of Research and Innovation; Pfizer; Eli Lilly and Company","keywords":"Bromodomain; Druggability; Chemistry; Computational biology; Ligand efficiency; Epigenetics; Small molecule; Drug discovery; Ligand (biochemistry); Biochemistry; Biology; Receptor; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0004364687,0.0005378036,0.0005496473,0.0002578156,0.0002100569,0.0005032015,0.00054427,0.0003349795,0.0007894885],"category_scores_gemma":[0.0003275346,0.0002308901,0.0002524952,0.0002438047,0.0003378997,0.0002741072,0.0002770255,0.0007731812,0.0003088426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006572711,"about_ca_system_score_gemma":0.0003695211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000877758,"about_ca_topic_score_gemma":0.002203568,"domain_scores_codex":[0.9998283,0.00003308382,0.00001046092,0.00002669558,0.00006628539,0.00003508422],"domain_scores_gemma":[0.9998941,0.00002693558,0.00002626717,0.000008306438,0.00001975005,0.00002457136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002358625,0.0001617713,0.0002811111,0.00007710013,0.00002601525,0.000071699,0.00003565201,0.004305491,0.9870865,0.0003995242,0.0001502161,0.007169039],"study_design_scores_gemma":[0.0001475068,0.0008522514,0.000699377,0.00000785981,0.00004162116,0.0002811504,0.0000263371,0.006930836,0.986231,0.0001182624,0.004643433,0.00002035965],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9506711,0.004137856,0.04131697,0.0003558367,0.00002615016,0.0003124809,0.0004774636,0.0002282878,0.002473874],"genre_scores_gemma":[0.9719672,0.003703214,0.02145422,0.0000928592,0.00001062708,0.0001147201,0.0007259771,0.00004058444,0.00189049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000877758,"threshold_uncertainty_score":0.004768908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008665042210148095,"score_gpt":0.2199667708710871,"score_spread":0.211301728660939,"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."}}