{"id":"W3185978387","doi":"10.26434/chemrxiv.10316177.v1","title":"Computational Approach Choice in Modeling Flexible Enzyme Active Sites","year":2019,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Enzyme Catalysis and Immobilization","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sulfenic acid; Chemistry; Nucleophile; Sulfonium; Substrate (aquarium); ONIOM; Stereochemistry; Molecule; Computational chemistry; Catalysis; Enzyme; Salt (chemistry); Organic chemistry; Cysteine","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":[0.0009331894,0.0007479324,0.001336078,0.0004924369,0.0008004202,0.001123604,0.002896421,0.001682217,0.00470728],"category_scores_gemma":[0.002229806,0.0005145432,0.001103941,0.0007527299,0.000647563,0.0006803624,0.001090401,0.001447871,0.0006503047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000981041,"about_ca_system_score_gemma":0.00201446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009064704,"about_ca_topic_score_gemma":0.005933648,"domain_scores_codex":[0.999683,0.000139403,0.00001199903,0.00003615587,0.0000730616,0.00005633226],"domain_scores_gemma":[0.9994146,0.0003389519,0.00003123772,0.00006551183,0.00009626603,0.00005345522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001100173,0.0000993567,0.00121873,0.0001519028,0.00005700854,0.0002589331,0.00008484493,0.9674703,0.001712064,0.02411242,0.000898985,0.003825399],"study_design_scores_gemma":[0.00005451826,0.0000300338,0.0001781195,0.00001327505,0.00001310858,0.00001628534,0.00003674561,0.9942458,0.0003269243,0.003551052,0.001524003,0.00001007922],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5938669,0.001407678,0.3406043,0.002684326,0.0004832761,0.0007831234,0.004570524,0.001175964,0.05442392],"genre_scores_gemma":[0.8237143,0.0009033039,0.1641176,0.0005712564,0.0000935671,0.002434989,0.001788166,0.0003932462,0.005983616],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.009064704,"threshold_uncertainty_score":0.01802391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02949947071008206,"score_gpt":0.2776532630371321,"score_spread":0.2481537923270501,"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."}}