{"id":"W2149566960","doi":"10.1021/jm400919p","title":"Small-Molecule Ligands of Methyl-Lysine Binding Proteins: Optimization of Selectivity for L3MBTL3","year":2013,"lang":"en","type":"article","venue":"Journal of Medicinal Chemistry","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"Structural Genomics Consortium; Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research; National Institute of General Medical Sciences; Wellcome Trust","keywords":"Chemistry; Lysine; Small molecule; Drug discovery; Epigenetics; Methylation; Biochemistry; In vitro; Binding site; Structure–activity relationship; Antagonism; Selectivity; Function (biology); Plasma protein binding; Combinatorial chemistry; Stereochemistry; Computational biology; Receptor; Cell biology; Gene; Amino acid; Biology","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":[0.0004591729,0.0004757631,0.0004882966,0.0002154262,0.0002156106,0.0003754474,0.0005254942,0.0004574753,0.001624573],"category_scores_gemma":[0.0002766383,0.0002194339,0.0002479971,0.0002294575,0.0002442799,0.0002473333,0.0002624697,0.000716907,0.0006347452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006567244,"about_ca_system_score_gemma":0.0004218718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00107907,"about_ca_topic_score_gemma":0.00330663,"domain_scores_codex":[0.9997484,0.00004723922,0.00001580824,0.0000494991,0.00006267192,0.00007632728],"domain_scores_gemma":[0.9999099,0.00002384603,0.00001914866,0.000007626971,0.00001584693,0.00002365613],"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":[0.0002784414,0.00007969252,0.0001425036,0.0000782171,0.00001317052,0.00006498529,0.00002872832,0.0007312585,0.9931591,0.0003927978,0.0002328278,0.004798263],"study_design_scores_gemma":[0.0002897192,0.001734781,0.0008333627,0.00001120301,0.00003092417,0.0003978063,0.000028323,0.003036615,0.9854505,0.0001161028,0.008045901,0.00002490563],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9599543,0.006980819,0.02056062,0.0007387153,0.0001018445,0.000542659,0.0007240301,0.0003735889,0.01002343],"genre_scores_gemma":[0.9792128,0.003107344,0.01273754,0.0003893239,0.0000272467,0.0001720198,0.0004572793,0.00003886112,0.003857591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001624573,"threshold_uncertainty_score":0.005434752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01473217068486298,"score_gpt":0.2560064871953881,"score_spread":0.2412743165105251,"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."}}