{"id":"W3015149476","doi":"10.20944/preprints202004.0015.v2","title":"Computational Screening of Molecules Approved in Phase-I Clinical Trials to Identify 3CL Protease Inhibitors to Treat COVID-19","year":2020,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Alberta","funders":"","keywords":"Pharmacophore; Virtual screening; Docking (animal); Computational biology; Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Similarity (geometry); 2019-20 coronavirus outbreak; Computer science; Pharmacology; Bioinformatics; Artificial intelligence; Medicine; Biology; Virology; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001408885,0.0009214376,0.001556777,0.001488675,0.0003232713,0.001037085,0.001005795,0.000847964,0.004235978],"category_scores_gemma":[0.003509195,0.0003056591,0.001370502,0.001384213,0.000344417,0.0003388693,0.0004251964,0.0005312681,0.0004106608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008115415,"about_ca_system_score_gemma":0.002066263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004596402,"about_ca_topic_score_gemma":0.008519359,"domain_scores_codex":[0.9996836,0.0001378126,0.00002126039,0.00004684269,0.00005953765,0.00005099051],"domain_scores_gemma":[0.9986423,0.00105544,0.00009933684,0.00004745732,0.00009095133,0.00006456473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003107722,0.0005163267,0.01466587,0.0008335344,0.0007678717,0.0004301955,0.00003692705,0.9351891,0.002144405,0.004302146,0.005695405,0.03231054],"study_design_scores_gemma":[0.0005828048,0.0008442097,0.002158375,0.00004020789,0.0004421765,0.0001316532,0.00003775115,0.9891883,0.001784888,0.002475493,0.00229822,0.0000158831],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.93411,0.003963275,0.02856861,0.001524446,0.0001293144,0.0005489768,0.01182826,0.00140959,0.01791747],"genre_scores_gemma":[0.9708611,0.0007533746,0.01793878,0.0003294783,0.00003097219,0.0002577379,0.007992306,0.00006055987,0.001775784],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.004596402,"threshold_uncertainty_score":0.01417077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.506359205422674,"score_gpt":0.566542188656795,"score_spread":0.06018298323412097,"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."}}