{"id":"W2055922525","doi":"10.1021/jm0508437","title":"Docking of Aminoglycosides to Hydrated and Flexible RNA","year":2006,"lang":"en","type":"article","venue":"Journal of Medicinal Chemistry","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":113,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University","funders":"","keywords":"AutoDock; Chemistry; Docking (animal); Searching the conformational space for docking; Nucleic acid; RNA; Macromolecule; Force field (fiction); Intermolecular force; Molecular dynamics; Computation; Molecule; Computational chemistry; Stereochemistry; Binding site; Algorithm; Biochemistry; Computer science; Artificial intelligence; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003282705,0.0001027728,0.0002064143,0.00003165952,0.00002743252,0.000008477174,0.0001379401,0.000101547,0.0000344427],"category_scores_gemma":[0.0001331979,0.00008396889,0.00006179693,0.00006461218,0.000049378,0.000003623112,0.00003813117,0.00008628222,5.341084e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009670823,"about_ca_system_score_gemma":0.00006260561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001380059,"about_ca_topic_score_gemma":9.660467e-7,"domain_scores_codex":[0.9991629,0.00001863677,0.0003565461,0.0001131394,0.0002183237,0.000130443],"domain_scores_gemma":[0.9993541,0.00001849938,0.0002636116,0.0001193066,0.0001421403,0.0001023603],"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":[0.0001512345,0.00002719741,0.0004846086,0.00006056512,0.00002672234,0.00001695015,0.00001663906,0.00004343527,0.9952949,0.000008158874,0.0009621257,0.002907492],"study_design_scores_gemma":[0.0003965185,0.0002540846,0.0005076922,0.0001525375,0.00003143189,0.0002533257,0.00009268941,0.000004319466,0.993969,0.0002465487,0.004007553,0.00008432767],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937472,0.0022094,0.001481875,0.0002257987,0.00006314763,0.00003957611,0.00000244532,0.000002395917,0.00222815],"genre_scores_gemma":[0.9974557,0.00009431134,0.001408649,0.00008044882,0.0005468762,0.000001259907,0.000003061356,0.00001031148,0.0003994258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003708445,"threshold_uncertainty_score":0.3424152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006386216128756852,"score_gpt":0.231658859572621,"score_spread":0.2252726434438641,"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."}}