{"id":"W3109714884","doi":"10.1101/2020.12.04.412569","title":"A First-in-class, Highly Selective and Cell-active Allosteric Inhibitor of Protein Arginine Methyltransferase 6 (PRMT6)","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Cancer-related gene regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Structural Genomics Consortium; Ontario Institute for Cancer Research; University of Toronto","funders":"Ontario Genomics; National Institutes of Health; Ontario Ministry of Research, Innovation and Science; Fundação de Amparo à Pesquisa do Estado de São Paulo; Genome Canada; Eli Lilly and Company; Icahn School of Medicine at Mount Sinai; Pfizer; Novartis Pharma; Ontario Genomics Institute; European Federation of Pharmaceutical Industries and Associations; Merck KGaA","keywords":"Allosteric regulation; Methyltransferase; Chemistry; Allosteric modulator; Enzyme; Enantiomer; Arginine; Epigenetics; Biochemistry; Methylation; Stereochemistry; Amino acid; 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":[0.0002216851,0.000363373,0.0002804408,0.0001791296,0.0001818339,0.0002121864,0.0003689392,0.0004063701,0.001898669],"category_scores_gemma":[0.0001286442,0.0001122023,0.000182613,0.0001554452,0.0002442612,0.000131374,0.0001837649,0.0006655072,0.001072093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003014831,"about_ca_system_score_gemma":0.0003362776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005085435,"about_ca_topic_score_gemma":0.0007887837,"domain_scores_codex":[0.9998797,0.00001425137,0.00000494094,0.00002359674,0.0000538604,0.00002360822],"domain_scores_gemma":[0.9999568,0.00000586411,0.00001003705,0.000004728452,0.000008272489,0.00001437614],"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":[0.0001539096,0.00007645638,0.0002596842,0.0001706282,0.00001646411,0.0001028437,0.00001789898,0.0003579869,0.9823752,0.0008261342,0.002131684,0.01351112],"study_design_scores_gemma":[0.00005056349,0.0002115468,0.0004648189,0.000004660342,0.00001241546,0.0003521265,0.000005238069,0.001014828,0.9779236,0.00009650161,0.01985786,0.000005981596],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8665311,0.03060764,0.07000995,0.001886474,0.0006490602,0.0004477373,0.003541713,0.001793737,0.02453261],"genre_scores_gemma":[0.9402498,0.007127374,0.02860996,0.0004399376,0.00009724648,0.0001365232,0.003675256,0.000130516,0.01953328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001898669,"threshold_uncertainty_score":0.006351709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007218981635250513,"score_gpt":0.2018740814353661,"score_spread":0.1946550998001156,"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."}}