{"id":"W2889753652","doi":"10.1021/acschembio.8b00665","title":"Chemical Instability and Promiscuity of Arylmethylidenepyrazolinone-Based MDMX Inhibitors","year":2018,"lang":"en","type":"article","venue":"ACS Chemical Biology","topic":"Synthesis and Characterization of Heterocyclic Compounds","field":"Chemistry","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"FP7 Joint Technology Initiatives; Engineering and Physical Sciences Research Council; Medical Research Council; Ministero dello Sviluppo Economico; Genome Canada; Fundação de Amparo à Pesquisa do Estado de São Paulo; Ontario Ministry of Economic Development and Innovation; European Federation of Pharmaceutical Industries and Associations; Wellcome; Structural Genomics Consortium; Merck KGaA; Novartis Pharma; Wellcome Trust; Pfizer","keywords":"Instability; Promiscuity; Genome instability; Chemistry; Computational biology; Pharmacology; Biology; Biochemistry; DNA; Physics; Ecology; DNA damage","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":[0.0003731898,0.0003182555,0.0002135574,0.00018227,0.0001938834,0.0003268381,0.0002420562,0.0002692896,0.0009400101],"category_scores_gemma":[0.0005979822,0.0001631505,0.0001769151,0.0001819038,0.0003604792,0.0003022274,0.0001781792,0.0004066977,0.0002970959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002410353,"about_ca_system_score_gemma":0.0001631881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000386921,"about_ca_topic_score_gemma":0.0005544986,"domain_scores_codex":[0.9995736,0.0001223237,0.00003102762,0.00008444525,0.0001273289,0.00006124377],"domain_scores_gemma":[0.9996731,0.0001374504,0.00009921328,0.00002579708,0.00003907972,0.0000252281],"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":[0.0000888616,0.000008328137,0.0001233435,0.0000475915,0.000007778262,0.00004124416,0.00003610523,0.0001377766,0.9981504,0.0001666974,0.00005652768,0.001135315],"study_design_scores_gemma":[0.000006179791,0.0001790189,0.0007910898,0.000004068404,0.000009764389,0.0001279627,0.00002748058,0.0004335708,0.9972101,0.00006247692,0.001143164,0.00000517764],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9809586,0.005015177,0.01034964,0.0002091217,0.00004013731,0.00003784096,0.0003471451,0.0001266254,0.0029156],"genre_scores_gemma":[0.9939671,0.001510775,0.002416441,0.00008968513,0.0000146469,0.00003597239,0.0003575204,0.0000250644,0.00158285],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009400101,"threshold_uncertainty_score":0.003144681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01461129439739328,"score_gpt":0.2556243942896791,"score_spread":0.2410130998922859,"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."}}