{"id":"W3126607922","doi":"10.1101/2021.02.03.429625","title":"A high-throughput radioactivity-based assay for screening SARS-CoV-2 nsp10-nsp16 complex","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Structural Genomics Consortium; University of Toronto","funders":"Genentech; University of Toronto; Ontario Genomics Institute; European Federation of Pharmaceutical Industries and Associations; Merck KGaA; Mitacs; Ontario Genomics; Genome Canada; Fundação de Amparo à Pesquisa do Estado de São Paulo; McGill University; Pfizer","keywords":"Methyltransferase; Druggability; Biology; High-throughput screening; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Messenger RNA; Computational biology; Coronavirus disease 2019 (COVID-19); Virology; Methylation; Genetics; Medicine; Gene","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":[0.001922143,0.002097178,0.001338941,0.001422718,0.0005765898,0.0007388871,0.001300898,0.001249198,0.003665263],"category_scores_gemma":[0.001228765,0.0009035066,0.0007211589,0.00124131,0.0005654061,0.0005827864,0.0008336563,0.00152289,0.005167822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005481683,"about_ca_system_score_gemma":0.0006437068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009196198,"about_ca_topic_score_gemma":0.002153774,"domain_scores_codex":[0.9971277,0.0009822806,0.0002128132,0.0003879633,0.001100533,0.0001886565],"domain_scores_gemma":[0.9991763,0.0002445815,0.00009064242,0.000144173,0.0002476491,0.00009661036],"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":[0.0001453492,0.0001812117,0.0005739203,0.0001404286,0.00003124894,0.00004985343,0.00006222029,0.0002439929,0.9936473,0.0001781527,0.0004796173,0.004266712],"study_design_scores_gemma":[0.0000157777,0.000480259,0.00120716,0.00001213578,0.00003266545,0.0001904488,0.00002945347,0.001952407,0.9918286,0.00008635985,0.004144382,0.0000203711],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4701887,0.007795232,0.4816904,0.001308191,0.0007069985,0.002515253,0.009603847,0.007466535,0.01872494],"genre_scores_gemma":[0.4437409,0.005334205,0.470055,0.0004027997,0.0002512097,0.002190378,0.02008194,0.0007724309,0.05717124],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003665263,"threshold_uncertainty_score":0.01226157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06868509858353959,"score_gpt":0.3230910760851831,"score_spread":0.2544059775016435,"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."}}