{"id":"W2774536896","doi":"10.1073/pnas.1715501114","title":"Aminoglycoside interactions and impacts on the eukaryotic ribosome","year":2017,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":210,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; National Institutes of Health; French Infrastructure for Integrated Structural Biology; Institute of Genetics; Fondation pour la Recherche Médicale; Kazan Federal University; Fondation ARC pour la Recherche sur le Cancer; Agence Nationale de la Recherche","keywords":"Ribosome; Aminoglycoside; Translation (biology); Protein biosynthesis; Eukaryotic Ribosome; Biology; A-site; Cell biology; Biophysics; Computational biology; Binding site; Chemistry; Biochemistry; RNA; Antibiotics; Messenger RNA","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006093513,0.00005490429,0.00005736405,0.00002732964,0.0004418666,0.00004474275,0.0005956473,0.00004102615,0.000006140003],"category_scores_gemma":[0.0009889292,0.00002886013,0.00003890213,0.00004361029,0.0005200579,0.00002151527,0.0001468971,0.00006304046,7.462123e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004434671,"about_ca_system_score_gemma":0.00001286847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000399392,"about_ca_topic_score_gemma":1.132811e-7,"domain_scores_codex":[0.9993827,0.000005128995,0.0001063283,0.0001340725,0.0002936739,0.00007812238],"domain_scores_gemma":[0.9995783,0.00004487389,0.0002671333,0.00001579735,0.00007421445,0.00001968529],"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":[0.00001042082,0.0000102131,0.002080626,0.000006394486,0.000008977973,1.453881e-9,0.00002052686,0.000002320634,0.9702653,0.02697601,0.0003417034,0.000277481],"study_design_scores_gemma":[0.00004632467,0.00005182614,0.09339279,0.00004480802,0.000004582992,0.000005387388,0.00004186251,0.00003968054,0.8930409,0.01306608,0.0002307071,0.00003506147],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878943,0.00005094573,0.000001414386,0.006290982,0.00002017126,0.00009929256,0.000005990584,0.000001385052,0.005635505],"genre_scores_gemma":[0.999146,0.00005422715,0.0001483683,0.0003209528,0.00007382443,0.000006988114,4.768357e-8,0.000002217865,0.0002473028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09131216,"threshold_uncertainty_score":0.3398526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04613468167802272,"score_gpt":0.3163322413981264,"score_spread":0.2701975597201037,"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."}}