{"id":"W4405602713","doi":"10.26434/chemrxiv-2024-v1sc1","title":"Large library docking and biophysical analysis of small molecule TMPRSS2 inhibitors","year":2024,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"HER2/EGFR in Cancer Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of British Columbia; University of Toronto","funders":"Canadian Institutes of Health Research; Genentech; Mitacs; Killam Trusts; Wellcome Trust; Ontario Genomics Institute; European Federation of Pharmaceutical Industries and Associations; American Foundation for Pharmaceutical Education; Merck KGaA; National Institutes of Health; Ontario Genomics; Genome Canada; Bayer; Natural Sciences and Engineering Research Council of Canada; Canadian Light Source; Pfizer; National Institute of Health Sciences","keywords":"Docking (animal); Computational biology; TMPRSS2; Small molecule; Chemistry; Biology; Medicine; Biochemistry; Coronavirus disease 2019 (COVID-19); Internal medicine","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":[0.000207107,0.0005020397,0.0006330623,0.0004491463,0.0002812878,0.0005489722,0.0004884318,0.0002471365,0.001701565],"category_scores_gemma":[0.0004919591,0.0001818358,0.0003251704,0.000563743,0.0001839897,0.0002433776,0.0002708549,0.0004454374,0.0004443355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000726313,"about_ca_system_score_gemma":0.0004001666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002552298,"about_ca_topic_score_gemma":0.002788954,"domain_scores_codex":[0.9998004,0.00002400537,0.00001109922,0.00003166636,0.000098488,0.00003442666],"domain_scores_gemma":[0.9998853,0.00004767022,0.00001523848,0.00001293303,0.00002126829,0.00001763862],"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":[0.0009424962,0.0008723888,0.002789014,0.0001506102,0.0001128698,0.0002705707,0.00007937192,0.2599782,0.7075251,0.003013287,0.001372797,0.02289328],"study_design_scores_gemma":[0.00009761564,0.0006243157,0.001830197,0.000003269872,0.00002819665,0.00008054323,0.00004587041,0.4227854,0.5725633,0.000409857,0.001506106,0.00002524447],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.971592,0.0004180988,0.02235614,0.0001623427,0.00001681647,0.00005932135,0.001106751,0.0005324069,0.003756169],"genre_scores_gemma":[0.9831777,0.0005100694,0.01179414,0.00004104283,0.000003512131,0.00007484693,0.00186937,0.00008896104,0.00244032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002552298,"threshold_uncertainty_score":0.005692303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03558635022213707,"score_gpt":0.3351820752374129,"score_spread":0.2995957250152759,"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."}}