{"id":"W2503334250","doi":"10.1021/acsinfecdis.6b00105","title":"How To Make a Glycopeptide: A Synthetic Biology Approach To Expand Antibiotic Chemical Diversity","year":2016,"lang":"en","type":"article","venue":"ACS Infectious Diseases","topic":"Microbial Natural Products and Biosynthesis","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Streptomyces coelicolor; Synthetic biology; Computational biology; Chemical space; Chemical biology; Biology; Glycopeptide antibiotic; Scaffold; Combinatorial chemistry; Natural product; Chemical synthesis; Glycopeptide; Enzyme; Biochemistry; Bacteria; Chemistry; Streptomyces; Drug discovery; Antibiotics; In vitro; Genetics; Computer science; Vancomycin","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":[0.00007159629,0.0002081434,0.0003470274,0.0001436435,0.0001462095,0.00003788863,0.0001517366,0.0001083782,0.00004754888],"category_scores_gemma":[0.00133732,0.0001237314,0.000117968,0.0002823995,0.0001170209,0.00005585766,0.0004116176,0.00007867311,0.0001235994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001176156,"about_ca_system_score_gemma":0.00004201359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005322446,"about_ca_topic_score_gemma":0.000005878419,"domain_scores_codex":[0.9987618,0.00004369726,0.0001289573,0.0005643527,0.0001342633,0.0003669585],"domain_scores_gemma":[0.9989239,0.00009922776,0.0000413854,0.0004056578,0.0001128095,0.000417044],"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":[0.0003884547,0.000779047,0.0599575,0.0001340777,0.0001484551,0.00002099118,0.00009566594,2.584954e-7,0.8785949,0.0002711656,0.009215477,0.05039404],"study_design_scores_gemma":[0.004364111,0.001940648,0.072558,0.0008142576,0.001264954,0.0004585899,0.0001616799,0.000002822882,0.8719468,0.0006938027,0.04428054,0.001513772],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922135,0.0001591287,0.00023945,0.005320999,0.0001655183,0.0006348967,0.0001096116,0.0001698214,0.000987048],"genre_scores_gemma":[0.9969804,0.00003488255,0.0001976771,0.001470889,0.0003330495,0.000003271065,0.00001036869,0.00001957603,0.0009499094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04888027,"threshold_uncertainty_score":0.504562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0141884805817691,"score_gpt":0.2371853095712045,"score_spread":0.2229968289894354,"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."}}