{"id":"W4387405271","doi":"10.1101/2023.10.05.560930","title":"Targeting LC3/GABARAP for degrader development and autophagy modulation","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Autophagy in Disease and Therapy","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Genentech; Deutsche Forschungsgemeinschaft; Deutschen Konsortium für Translationale Krebsforschung; Ontario Genomics Institute; European Federation of Pharmaceutical Industries and Associations; Merck KGaA; Ontario Genomics; Genome Canada; Bundesministerium für Bildung und Forschung; Diamond Light Source; McGill University; Bayer; Pfizer; Deutsches Krebsforschungszentrum; Bristol-Myers Squibb","keywords":"Druggability; Autophagosome; Autophagy; ULK1; In silico; Computational biology; Docking (animal); Small molecule; Chemistry; Drug discovery; Biology; Cell biology; Biochemistry; Kinase; Medicine","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":[0.0002755228,0.0003998959,0.0003633629,0.0001755272,0.0001928112,0.0003543924,0.0002585238,0.0003149348,0.001750252],"category_scores_gemma":[0.0001491526,0.0001120125,0.0003021072,0.0001811129,0.0002422481,0.0001690743,0.000347039,0.0004964834,0.0007599787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003440149,"about_ca_system_score_gemma":0.0003081394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006138623,"about_ca_topic_score_gemma":0.0007826814,"domain_scores_codex":[0.9998571,0.00003311526,0.00001170677,0.00002435373,0.00004463533,0.00002923167],"domain_scores_gemma":[0.9999338,0.00001239502,0.00001701628,0.000009329169,0.0000112167,0.00001620483],"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":[0.0001727395,0.00006095696,0.0003347869,0.0001326858,0.00001835485,0.00009913947,0.00002142921,0.00147093,0.9914535,0.0003182353,0.0002690627,0.005648188],"study_design_scores_gemma":[0.00002076484,0.0002089785,0.0003769399,0.000008159733,0.00001044848,0.0001186313,0.000009055201,0.001578352,0.9939757,0.00005634308,0.003629736,0.000006902354],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9572489,0.007483803,0.02815556,0.0003777527,0.00007500216,0.000198772,0.001271726,0.0004861328,0.004702397],"genre_scores_gemma":[0.9617256,0.002765888,0.0304005,0.0001851725,0.00001266945,0.0001424348,0.001005876,0.00006667817,0.003695141],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001750252,"threshold_uncertainty_score":0.005855203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03124421689710492,"score_gpt":0.2636584490641951,"score_spread":0.2324142321670901,"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."}}