{"id":"W4381337494","doi":"10.1101/2023.06.19.543857","title":"Ribosomal A-site interactions with near-cognate tRNAs drive stop codon readthrough","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Grantová Agentura, Univerzita Karlova; Univerzita Karlova v Praze; Grantová Agentura České Republiky; Akademie Věd České Republiky; Ministerstvo Školství, Mládeže a Tělovýchovy; University of Bern","keywords":"Transfer RNA; Ribosome; Translation (biology); Genetic code; P-site; Stop codon; Genetics; Biology; Cognate; Ribosomal RNA; Computational biology; Translational frameshift; Ribosomal protein; A-site; Messenger RNA; RNA; Binding site; Amino acid; Gene","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":[0.0002065036,0.0002447939,0.0001896409,0.0001076693,0.0002000713,0.0004475138,0.0001695502,0.0002359751,0.002120594],"category_scores_gemma":[0.0002927467,0.0001247932,0.000189411,0.00008050286,0.0002548929,0.0001140662,0.0002990752,0.0004876902,0.00120634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002469003,"about_ca_system_score_gemma":0.0001835646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003347592,"about_ca_topic_score_gemma":0.0004230098,"domain_scores_codex":[0.9998488,0.00002998268,0.00001235476,0.00003482034,0.0000468018,0.00002703849],"domain_scores_gemma":[0.9997562,0.00009192756,0.00003962754,0.00002946161,0.00001389374,0.00006882758],"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":[0.00009580341,0.00002831071,0.0002509177,0.00002546336,0.00000420573,0.00009129577,0.00001984465,0.0001947613,0.9973236,0.0005559309,0.000178584,0.001231201],"study_design_scores_gemma":[0.00002161576,0.0001453706,0.001540795,0.000007701236,0.000006710946,0.0002163633,0.00004685467,0.003779704,0.9888911,0.0003485882,0.004989354,0.000005812339],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944859,0.0003742113,0.00212111,0.00007049835,0.00004616037,0.000007486293,0.00006870271,0.0001149591,0.002711092],"genre_scores_gemma":[0.9960526,0.0001031825,0.001573774,0.00003766172,0.000009320491,0.000004950311,0.000152782,0.00004909257,0.002016628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002120594,"threshold_uncertainty_score":0.007094085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01631227675813999,"score_gpt":0.2329323763719724,"score_spread":0.2166200996138324,"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."}}