{"id":"W4360825536","doi":"10.1021/jacs.2c09387","title":"High Accuracy Prediction of PROTAC Complex Structures","year":2023,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Protein Degradation and Inhibitors","field":"Biochemistry, Genetics and Molecular Biology","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sinai Health System; Lunenfeld-Tanenbaum Research Institute; Ontario Institute for Cancer Research; University of Toronto","funders":"Division of Computing and Communication Foundations; National Institute of General Medical Sciences; Division of Mathematical Sciences; National Science Foundation; Ontario Institute for Cancer Research; Office of the Director; Government of Ontario","keywords":"Chemistry; Ternary complex; DNA ligase; Ubiquitin ligase; Docking (animal); Ternary operation; Computational biology; Linker; Protein degradation; Ubiquitin; Biological system; Biochemistry; Computer science; DNA; 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":[0.0001371405,0.00006846566,0.0001452752,0.0000098639,0.00003850395,0.000007033705,0.0002447667,0.00004215915,0.00001113882],"category_scores_gemma":[0.0002105664,0.00004375442,0.0002841828,0.0002166594,0.0002265009,0.000004191388,0.0001047191,0.0001302552,6.799887e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001801475,"about_ca_system_score_gemma":0.00005141316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009361499,"about_ca_topic_score_gemma":1.137834e-7,"domain_scores_codex":[0.9993272,0.00003428952,0.0002544578,0.00007993296,0.0002033913,0.0001007108],"domain_scores_gemma":[0.9991522,0.00001804263,0.0005270493,0.000152545,0.0001095503,0.00004064491],"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":[0.000032923,0.00001548443,0.001051711,0.000007427149,0.00005579679,1.078118e-7,0.00002861987,0.00002678716,0.9406679,0.00001240253,0.05673308,0.001367755],"study_design_scores_gemma":[0.0002560502,0.0001072826,0.01713447,0.000009557188,0.00001490993,0.00001121748,0.0001256788,0.00005181528,0.9727904,0.0002382191,0.009216099,0.00004429779],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986203,0.00002845375,0.0001307186,0.0009744905,0.0001143945,0.00007900693,0.00002268794,0.000005710359,0.00002427193],"genre_scores_gemma":[0.9975221,0.00009476751,0.001590678,0.0003372629,0.0003814138,0.000002216634,0.00001572497,0.000007941956,0.0000479151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04751698,"threshold_uncertainty_score":0.1784253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01534936670500082,"score_gpt":0.2690590210778986,"score_spread":0.2537096543728978,"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."}}