{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002075909,0.0003466885,0.0002061786,0.0002035061,0.0001293513,0.0004008301,0.0001828412,0.0002724051,0.0007197734],"category_scores_gemma":[0.0002221284,0.0001251612,0.0002317885,0.0002148892,0.0002598983,0.0005046108,0.0002863587,0.0007308836,0.0003795917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000193825,"about_ca_system_score_gemma":0.0002344723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000155103,"about_ca_topic_score_gemma":0.0002752581,"domain_scores_codex":[0.9998889,0.00002133426,0.00001026078,0.00002643092,0.00003142265,0.00002159381],"domain_scores_gemma":[0.9998868,0.00001718418,0.00003236598,0.00002330959,0.00001174833,0.00002849201],"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":[0.00004240574,0.00002327608,0.00021986,0.00004770303,0.000006858759,0.00007514987,0.00002180185,0.0002631753,0.9918888,0.0009004275,0.00006908298,0.006441368],"study_design_scores_gemma":[0.0000191166,0.0004238637,0.0009000346,0.00001011338,0.00001817749,0.0004471615,0.00002894975,0.0008043221,0.9842284,0.0007024932,0.01240586,0.00001150775],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8936375,0.003513717,0.09217685,0.001340473,0.0002015236,0.0002094287,0.0005847723,0.0003122184,0.008023473],"genre_scores_gemma":[0.8955361,0.002684802,0.09822732,0.0002926785,0.00003048413,0.00006145363,0.0003542315,0.00006729217,0.002745543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007197734,"threshold_uncertainty_score":0.002407908,"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."}}