{"id":"W4407350032","doi":"10.1021/acschembio.4c00812","title":"Workflow for E3 Ligase Ligand Validation for PROTAC Development","year":2025,"lang":"en","type":"article","venue":"ACS Chemical Biology","topic":"Protein Degradation and Inhibitors","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Structural Genomics Consortium; LOEWE-Zentrum für Translationale Medizin und Pharmakologie; Deutschen Konsortium für Translationale Krebsforschung; Fraunhofer-Gesellschaft; Innovative Medicines Initiative; Technische Universität München; Bundesministerium für Bildung und Forschung; Deutsche Krebshilfe; Hessisches Ministerium für Wissenschaft und Kunst; Deutsche Forschungsgemeinschaft; Deutsches Krebsforschungszentrum","keywords":"Workflow; Ubiquitin ligase; DNA ligase; Ligand (biochemistry); Computer science; Computational biology; Business; Process management; Chemistry; Ubiquitin; Biology; Database; Biochemistry; Receptor; DNA","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":[0.003480557,0.00179195,0.001861186,0.001794997,0.0009601064,0.00132838,0.001167822,0.001026308,0.01022175],"category_scores_gemma":[0.002656897,0.0008687708,0.001206317,0.0008891831,0.0005530108,0.000827527,0.001420864,0.002369379,0.008360359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009992127,"about_ca_system_score_gemma":0.002756771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001442778,"about_ca_topic_score_gemma":0.001815121,"domain_scores_codex":[0.9974054,0.0003371158,0.000286691,0.0006301519,0.001055785,0.0002848731],"domain_scores_gemma":[0.9981163,0.0004016995,0.0002071739,0.0004366686,0.0006449348,0.0001932927],"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":[0.0007781444,0.0002634529,0.001375605,0.0005467818,0.0000831224,0.0004841498,0.0002472536,0.001899647,0.9390284,0.002006168,0.005081776,0.04820551],"study_design_scores_gemma":[0.00006005819,0.0002989038,0.001187489,0.00005533759,0.00005390908,0.000424404,0.00005683051,0.007918524,0.9444734,0.0006811793,0.04468925,0.0001007294],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08506707,0.001963849,0.8577602,0.0005865953,0.000360461,0.005276595,0.00949985,0.03107277,0.008412726],"genre_scores_gemma":[0.1802868,0.002693152,0.7763067,0.0008518635,0.00008341176,0.007714471,0.01502091,0.004119518,0.01292306],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01022175,"threshold_uncertainty_score":0.03419518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01221062706261001,"score_gpt":0.2842726104764001,"score_spread":0.2720619834137901,"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."}}