{"id":"W4391474866","doi":"10.1038/s41589-023-01532-x","title":"High-throughput reprogramming of an NRPS condensation domain","year":2024,"lang":"en","type":"article","venue":"Nature Chemical Biology","topic":"Biochemical and Structural Characterization","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research; Eidgenössische Technische Hochschule Zürich; Government of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Nonribosomal peptide; Adenylylation; Yeast; Synthetic biology; Combinatorial chemistry; Substrate (aquarium); Computational biology; Chemistry; Function (biology); Biochemistry; Biology; Biosynthesis; Cell biology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009987271,0.0001408488,0.0001626527,0.00002917251,0.00002018374,0.00001500847,0.0001566214,0.0009236269,0.00003013138],"category_scores_gemma":[0.00009688506,0.0001112629,0.00008030683,0.0001255834,0.0001570738,0.00000613369,0.00007180596,0.0002981561,0.000003580277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001323689,"about_ca_system_score_gemma":0.00002646635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005974523,"about_ca_topic_score_gemma":0.000001209907,"domain_scores_codex":[0.9990187,0.0000388802,0.0002249443,0.0004690427,0.00006792853,0.0001805202],"domain_scores_gemma":[0.9995603,0.00001763356,0.00005360611,0.0002331112,0.00007407407,0.0000613066],"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":[0.0000694106,0.00001705857,0.0001132682,0.00003840469,0.00003094587,0.000001726897,0.00001659867,2.268344e-7,0.9850746,0.004768084,0.0001072857,0.00976239],"study_design_scores_gemma":[0.0001673403,0.0001365127,0.0002094846,0.00001349491,0.00001147204,0.0000250388,0.000008664185,0.00001986704,0.9797101,0.005718915,0.01384085,0.000138257],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972671,0.001323065,0.0004816723,0.0003041201,0.000332666,0.0000959268,0.00005638602,0.00004141131,0.00009762603],"genre_scores_gemma":[0.9921378,0.00003760359,0.004235743,0.0002316888,0.0006043531,0.000008645234,0.00269461,0.00001474321,0.00003475062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01373357,"threshold_uncertainty_score":0.7123857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004271171270126708,"score_gpt":0.2637282113757103,"score_spread":0.2594570401055836,"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."}}