{"id":"W3202854404","doi":"10.1016/j.bbapap.2021.140720","title":"Binding interactions in a kinase active site modulate background ATP hydrolysis","year":2021,"lang":"en","type":"article","venue":"Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics","topic":"Biochemical and Molecular Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Isothermal titration calorimetry; Chemistry; Enzyme kinetics; ATP hydrolysis; Nucleoside; Kinase; Product inhibition; Substrate (aquarium); Allosteric regulation; Biophysics; Stereochemistry; Hydrolysis; Active site; Nucleoside triphosphate; Pyrophosphate; Biochemistry; Adenosine triphosphate; Enzyme; Titration; Nucleotide; ATPase; Non-competitive inhibition; Biology; Organic chemistry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000186934,0.0003771109,0.0003513183,0.0001398771,0.0001769879,0.0001683777,0.0002457383,0.000242937,0.00002660327],"category_scores_gemma":[0.00009248657,0.0003703872,0.0002179261,0.0004573154,0.0001911483,0.00003156205,0.0005821022,0.0005133624,0.0000190149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005788264,"about_ca_system_score_gemma":0.0002046649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00013783,"about_ca_topic_score_gemma":0.0001127941,"domain_scores_codex":[0.997698,0.0001969632,0.0003644844,0.0009536906,0.0002402305,0.0005466483],"domain_scores_gemma":[0.9988701,0.00002310917,0.0001475594,0.0005941921,0.0001404325,0.0002245489],"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":[0.000356705,0.0003164242,0.0000174401,0.00006685294,0.0001301813,0.00002970747,0.0001772084,0.000005148495,0.9975827,0.00006743101,0.00006106804,0.001189164],"study_design_scores_gemma":[0.0009020192,0.0002027066,0.0008582738,0.00009037314,0.00003456241,0.00003575951,0.000103936,0.0003486418,0.9947204,0.0001727739,0.002070227,0.0004603012],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958805,0.0002002105,0.0003087276,0.002147628,0.00005995725,0.0008625485,0.0001724046,0.00002475586,0.0003432885],"genre_scores_gemma":[0.9939181,0.0005124083,0.003487711,0.0003797641,0.0001841373,0.0002741516,0.0005894871,0.00006191379,0.0005923422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003178983,"threshold_uncertainty_score":0.9998748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01980897897023864,"score_gpt":0.2855405625878715,"score_spread":0.2657315836176328,"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."}}