{"id":"W2059005989","doi":"10.1021/cb300729y","title":"<i>De Novo</i> Design of Protein Kinase Inhibitors by <i>in Silico</i> Identification of Hinge Region-Binding Fragments","year":2013,"lang":"en","type":"article","venue":"ACS Chemical Biology","topic":"Quinazolinone synthesis and applications","field":"Chemistry","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Centre","funders":"Biotechnology and Biological Sciences Research Council; Deutscher Akademischer Austauschdienst; Medical Research Council; Bundesministerium für Bildung und Forschung; Wellcome Trust; University of Dundee","keywords":"Kinase; In silico; Drug discovery; Computational biology; Small molecule; Chemical biology; Biochemistry; Biology; Binding site; Enzyme; Protein-Serine-Threonine Kinases; Function (biology); Chemistry; Protein kinase A; Cell biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001622673,0.000130936,0.000252337,0.00004088677,0.00002315873,0.000008099983,0.000276378,0.0002558489,0.00009124245],"category_scores_gemma":[0.0001928873,0.0001261517,0.00005382298,0.0001458098,0.0001679473,0.00005593872,0.00006261349,0.0001481886,0.00002058786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005961374,"about_ca_system_score_gemma":0.00002759744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001005781,"about_ca_topic_score_gemma":2.477087e-7,"domain_scores_codex":[0.9987605,0.00003513966,0.0005861638,0.0002926705,0.00007903477,0.0002465304],"domain_scores_gemma":[0.9990506,0.0001829103,0.0003243668,0.000324935,0.00005942977,0.00005771481],"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":[0.00001437915,0.0002358137,0.001763877,0.00006502963,0.00001091601,3.108804e-7,0.00005241816,0.000001850208,0.9937223,0.0002467031,0.000605145,0.003281297],"study_design_scores_gemma":[0.0002672788,0.00001156899,0.00002320464,0.00005537325,0.000008373547,0.000002028609,0.00004878823,0.00006823636,0.9978034,0.001149776,0.0004486902,0.0001132179],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984069,0.0001432327,0.000544603,0.0002768766,0.00001316983,0.0002487709,0.00002585329,0.0000224746,0.0003181399],"genre_scores_gemma":[0.9989158,0.00002787126,0.0004466035,0.00002921557,0.00003484722,0.0003154037,0.00007170552,0.00001515483,0.0001433802],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004081203,"threshold_uncertainty_score":0.5144318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0130015385615912,"score_gpt":0.2352795358898304,"score_spread":0.2222779973282392,"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."}}