{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001285823,0.0001919114,0.0002217338,0.00002493439,0.0001480822,0.00004924355,0.0002581988,0.0001561963,0.00008896415],"category_scores_gemma":[0.0007683152,0.0001286254,0.0001149849,0.00007619501,0.0002146837,0.00001690116,0.00007700299,0.0003532745,0.000001782346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003726161,"about_ca_system_score_gemma":0.0001555712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006356302,"about_ca_topic_score_gemma":2.147223e-7,"domain_scores_codex":[0.9984125,0.0001500787,0.0005466193,0.0002185087,0.0004312181,0.000241097],"domain_scores_gemma":[0.9988158,0.00009483525,0.0004024586,0.0002331586,0.00023702,0.0002166689],"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":[0.0001014268,0.00006034732,0.0004714051,0.00006782265,0.00004116063,0.00000972872,0.00004350196,0.0003095458,0.9854239,6.783364e-7,0.009468468,0.004002017],"study_design_scores_gemma":[0.001832832,0.0002674827,0.0008521243,0.0002796141,0.00003460392,0.0001013226,0.0007299644,0.002393804,0.9885322,0.00008495408,0.004664916,0.0002262235],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9552114,0.001787836,0.04066349,0.001768815,0.0001225276,0.0002375697,0.000003018118,0.000006963747,0.0001983872],"genre_scores_gemma":[0.9913993,0.0001082761,0.00654385,0.0007957385,0.001025704,0.00001430953,0.00001301662,0.00001891812,0.00008091877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03618787,"threshold_uncertainty_score":0.5245191,"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."}}