{"id":"W2465999258","doi":"10.1038/srep29086","title":"A Rational Approach for the Identification of Non-Hydroxamate HDAC6-Selective Inhibitors","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Histone Deacetylase Inhibitors Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Fondation Pierre Mercier; Università degli Studi di Perugia; Université de Genève; Ministero dell’Istruzione, dell’Università e della Ricerca; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"HDAC6; Acetylation; Chemistry; Virtual screening; Histone deacetylase; Hydrazide; In vitro; Biochemistry; Histone; Cancer research; Computational biology; Biology; Drug discovery","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":[0.0005010465,0.001146875,0.001459755,0.0007963428,0.0003346817,0.0009919022,0.001037503,0.0005389506,0.004015622],"category_scores_gemma":[0.0006429122,0.0005126125,0.001027834,0.0007565871,0.0004304688,0.0007777365,0.0008069394,0.001338642,0.001663707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006589231,"about_ca_system_score_gemma":0.001149984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000668835,"about_ca_topic_score_gemma":0.001917272,"domain_scores_codex":[0.9997337,0.00004407219,0.00002405457,0.00006646742,0.00007962016,0.00005201325],"domain_scores_gemma":[0.9998788,0.00003225837,0.00002281608,0.00002078736,0.00002918812,0.00001625791],"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":[0.001645532,0.001599237,0.002671288,0.003975701,0.0004301667,0.001970449,0.000229569,0.09837929,0.6082181,0.04026569,0.009226768,0.2313883],"study_design_scores_gemma":[0.002593132,0.007660319,0.002716886,0.0005412698,0.001139673,0.003820286,0.0003030214,0.1931931,0.5711846,0.01956438,0.1969691,0.0003140982],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4351471,0.03578139,0.4732213,0.002392809,0.0004721719,0.003927286,0.007135369,0.003171644,0.03875086],"genre_scores_gemma":[0.6826974,0.02980983,0.2674883,0.001048561,0.0001025828,0.001844092,0.0082143,0.0002524948,0.008542551],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004015622,"threshold_uncertainty_score":0.01343358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0110388868739471,"score_gpt":0.2785995384006583,"score_spread":0.2675606515267112,"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."}}