{"id":"W4386878764","doi":"10.1021/acs.accounts.3c00412","title":"Synthesis of Peptidyl-tRNA Mimics for Structural Biology Applications","year":2023,"lang":"en","type":"review","venue":"Accounts of Chemical Research","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Allergy and Infectious Diseases; University of Illinois at Urbana-Champaign; National Institute of General Medical Sciences; Directorate for Biological Sciences; Österreichische Forschungsförderungsgesellschaft; Killam Trusts; Universität Innsbruck; Austrian Science Fund; Agence Nationale de la Recherche; National Institutes of Health; National Science Foundation","keywords":"Peptidyl transferase; Ribosome; Transfer RNA; Protein biosynthesis; Translation (biology); Genetic code; T arm; Translational frameshift; Ribosomal RNA; Amino acid; Biology; Computational biology; Biochemistry; RNA; Chemistry; Messenger RNA; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002590636,0.0005076269,0.0002800777,0.0002250034,0.0002403148,0.0003840116,0.0004305316,0.0006351368,0.009905295],"category_scores_gemma":[0.0003415389,0.0003547403,0.0003459199,0.0002134213,0.0001511843,0.0005023769,0.0002972962,0.001189955,0.005711153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003866916,"about_ca_system_score_gemma":0.0002549315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001748313,"about_ca_topic_score_gemma":0.0002767164,"domain_scores_codex":[0.9998313,0.0000237158,0.00001288077,0.00004104848,0.00006186556,0.00002915697],"domain_scores_gemma":[0.9998767,0.00002555402,0.00002425674,0.0000231092,0.00002263833,0.00002758099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001192919,0.00004082457,0.00003444067,0.0001437288,0.00001191039,0.0001707085,0.00002830161,0.0005760325,0.9873939,0.001674055,0.002828211,0.006978668],"study_design_scores_gemma":[0.00003000002,0.0001515813,0.0001099055,0.0000116891,0.000007638146,0.0001148867,0.00001033774,0.002649902,0.9648882,0.0002621147,0.03175184,0.00001185972],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.5485438,0.01062504,0.2892557,0.00305227,0.003540999,0.001455308,0.009407762,0.01126633,0.1228528],"genre_scores_gemma":[0.8075768,0.005396845,0.1250165,0.0008314684,0.0001853674,0.001012384,0.006312612,0.001229929,0.05243803],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.009905295,"threshold_uncertainty_score":0.03313655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1320424352466776,"score_gpt":0.4582886973044606,"score_spread":0.326246262057783,"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."}}