{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005905865,0.0001159945,0.00028731,0.0000503095,0.00002785707,0.000006780643,0.0001517936,0.0001613162,0.00003137177],"category_scores_gemma":[0.0006376454,0.00009855683,0.0001449857,0.0001213025,0.00006424189,0.000007066916,0.000029406,0.0001141424,1.363817e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001845465,"about_ca_system_score_gemma":0.0001570377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001014418,"about_ca_topic_score_gemma":7.4355e-7,"domain_scores_codex":[0.9989452,0.00002360135,0.0005436813,0.0001295537,0.0002234827,0.0001345183],"domain_scores_gemma":[0.9981351,0.00004020284,0.0007892042,0.0001465955,0.0008029513,0.00008598153],"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":[0.0001114831,0.00009009127,0.0007672528,0.0002495687,0.00008994906,6.312578e-7,0.00003176838,0.001915975,0.9955106,0.000001256105,0.00008247268,0.001148901],"study_design_scores_gemma":[0.0008975827,0.0006269942,0.000220619,0.0001241306,0.00007994685,0.0000125724,0.00007530973,0.001064374,0.9966419,0.0000587644,0.0001103711,0.00008739599],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9431505,0.001644785,0.05459742,0.0001293463,0.00005525341,0.00017387,0.000006109613,0.00000158776,0.000241145],"genre_scores_gemma":[0.9881679,0.0003139126,0.01103392,0.00001204213,0.0003102548,0.0000097889,0.00002753928,0.00001574609,0.000108851],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04501746,"threshold_uncertainty_score":0.4019031,"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."}}