{"id":"W2012651834","doi":"10.1021/ci400550m","title":"Docking Ligands into Flexible and Solvated Macromolecules. 6. Development and Application to the Docking of HDACs and other Zinc Metalloenzymes Inhibitors","year":2013,"lang":"en","type":"article","venue":"Journal of Chemical Information and Modeling","topic":"Peptidase Inhibition and Analysis","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Docking (animal); Chemistry; Zinc; Combinatorial chemistry; Small molecule; Drug discovery; Molecule; Stereochemistry; Computational chemistry; Biochemistry; Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005101801,0.001070015,0.0008761119,0.0003129086,0.000447305,0.0006859632,0.001383155,0.001230166,0.007660356],"category_scores_gemma":[0.00117594,0.0005595754,0.0006451467,0.0005683549,0.0003496639,0.0005816502,0.0007606061,0.0009019764,0.002102468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006253226,"about_ca_system_score_gemma":0.0009213199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003145665,"about_ca_topic_score_gemma":0.002667164,"domain_scores_codex":[0.9997953,0.00006568939,0.00001446012,0.00003206398,0.00006322778,0.00002923953],"domain_scores_gemma":[0.9997924,0.00008823405,0.00002356621,0.00003176592,0.00003961334,0.00002440954],"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":[0.0005065542,0.0001796142,0.001291876,0.000391034,0.000173999,0.0003413671,0.0001546197,0.8888453,0.03050935,0.01244518,0.004178044,0.0609831],"study_design_scores_gemma":[0.0001160321,0.00009342615,0.0002823861,0.00002125613,0.00002262777,0.00007021614,0.00002293652,0.9674788,0.02187044,0.002299122,0.007697144,0.00002558664],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1525941,0.0008295832,0.8085909,0.0004455349,0.000139227,0.0004223581,0.00208173,0.02016401,0.01473253],"genre_scores_gemma":[0.6114945,0.001179535,0.3731681,0.0002383981,0.00002414795,0.0009938382,0.002290944,0.002648123,0.007962425],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007660356,"threshold_uncertainty_score":0.02562648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01362164805566174,"score_gpt":0.2621217438244645,"score_spread":0.2485000957688027,"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."}}