{"id":"W2083189299","doi":"10.1016/j.jmgm.2010.05.005","title":"LigAlign: Flexible ligand-based active site alignment and analysis","year":2010,"lang":"en","type":"article","venue":"Journal of Molecular Graphics and Modelling","topic":"Microbial Natural Products and Biosynthesis","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Bill and Melinda Gates Foundation","keywords":"Ligand (biochemistry); Structural alignment; Active site; Computer science; Chemistry; Sequence alignment; Biochemistry; Peptide sequence; Enzyme","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":[0.0004116787,0.0001319075,0.0003623477,0.0004231728,0.0000776407,0.00004605778,0.00004620116,0.0001144721,0.000005966443],"category_scores_gemma":[0.00002869524,0.00009422014,0.0002202611,0.0003349386,0.00006972936,0.00005913484,0.0000187882,0.0003880683,1.867766e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007035908,"about_ca_system_score_gemma":0.00004655926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002206381,"about_ca_topic_score_gemma":0.000004530107,"domain_scores_codex":[0.9991289,0.0000198458,0.0002887503,0.0001786798,0.0002396686,0.0001441015],"domain_scores_gemma":[0.9992026,0.00003102288,0.0002055497,0.0001382963,0.0002416185,0.00018088],"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":[0.000208295,0.00007673221,0.0006942677,0.00004304246,0.0006361753,0.00007987852,0.0001017121,0.001161192,0.9944414,0.0005745939,0.00002359208,0.001959051],"study_design_scores_gemma":[0.0008237373,0.0002715107,0.0004163634,0.00009753124,0.002278717,0.0001244003,0.00002664861,0.03555941,0.957845,0.0009093795,0.001477092,0.0001701545],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9681452,0.001333192,0.02855054,0.001765654,0.00006673289,0.00008796559,0.000005906862,0.00000569627,0.00003912759],"genre_scores_gemma":[0.9907205,0.0009524749,0.007617495,0.0005985704,0.00007973488,1.575556e-7,0.000003777405,0.00001138882,0.00001592735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03659641,"threshold_uncertainty_score":0.3842186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01319318373585886,"score_gpt":0.2450266513800391,"score_spread":0.2318334676441802,"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."}}