{"id":"W3212053117","doi":"10.1016/j.jbc.2021.101412","title":"Cardiac ryanodine receptor N-terminal region biosensors identify novel inhibitors via FRET-based high-throughput screening","year":2021,"lang":"en","type":"article","venue":"Journal of Biological Chemistry","topic":"Ion channel regulation and function","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institute on Aging; National Institutes of Health; Australian Research Council; Canadian Institutes of Health Research; National Heart, Lung, and Blood Institute; RYR-1 Foundation","keywords":"Ryanodine receptor; RYR1; Skeletal muscle; Ryanodine receptor 2; Endoplasmic reticulum; Förster resonance energy transfer; Chemistry; Biophysics; Biochemistry; High-throughput screening; Cardiac muscle; Myocyte; Cell biology; Biology; Fluorescence; Anatomy","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":[0.001799845,0.0008841593,0.001316173,0.0003181706,0.0003620906,0.0008487343,0.0009823345,0.001052523,0.003016038],"category_scores_gemma":[0.001528036,0.0002858036,0.0005185548,0.0003487959,0.0004117898,0.000630826,0.0004193058,0.001808751,0.00153347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006397311,"about_ca_system_score_gemma":0.0003931161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005240596,"about_ca_topic_score_gemma":0.001635675,"domain_scores_codex":[0.9987281,0.0002262858,0.00009202047,0.0002104594,0.0006188656,0.0001242511],"domain_scores_gemma":[0.9994881,0.0002420941,0.00006531713,0.00006792165,0.00009931153,0.00003719614],"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":[0.00009713611,0.00006978818,0.0001505876,0.00007578602,0.00002321666,0.0000486409,0.00003507417,0.000358642,0.9941187,0.0003223504,0.0005153808,0.004184675],"study_design_scores_gemma":[0.00001156387,0.000198413,0.0003999743,0.000006488011,0.00001956416,0.0001537726,0.00002199757,0.002522183,0.9940594,0.0001257677,0.002468144,0.000012616],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6764176,0.005812672,0.2853416,0.002702185,0.0005170011,0.0009652642,0.00481582,0.004199161,0.01922853],"genre_scores_gemma":[0.8809726,0.002801555,0.08951907,0.0009838071,0.00005363386,0.0007289688,0.002852406,0.0004665834,0.02162137],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003016038,"threshold_uncertainty_score":0.01008964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02749928599483218,"score_gpt":0.2612950981668433,"score_spread":0.2337958121720111,"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."}}