{"id":"W2130141176","doi":"10.1124/mol.113.087551","title":"Muscarinic Receptors as Model Targets and Antitargets for Structure-Based Ligand Discovery","year":2013,"lang":"en","type":"article","venue":"Molecular Pharmacology","topic":"Receptor Mechanisms and Signaling","field":"Biochemistry, Genetics and Molecular Biology","cited_by":63,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Division of Chemistry; National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences; Bayerisch-Kalifornischen Hochschulzentrum; Emory University; National Institutes of Health; National Science Foundation","keywords":"Receptor; G protein-coupled receptor; Muscarinic acetylcholine receptor; Docking (animal); Agonist; Allosteric regulation; Chemistry; Stereochemistry; Muscarinic acetylcholine receptor M2; Muscarinic acetylcholine receptor M3; Drug discovery; Biochemistry","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":[0.000956483,0.0006629924,0.0007552998,0.0005226628,0.0003700203,0.001026726,0.0007948633,0.0008409831,0.001333002],"category_scores_gemma":[0.0004984924,0.0003616814,0.0004202087,0.0004047677,0.0004865587,0.0007899416,0.0005708754,0.001222097,0.0006175075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009584174,"about_ca_system_score_gemma":0.0004073711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003783835,"about_ca_topic_score_gemma":0.0008166614,"domain_scores_codex":[0.9996731,0.0000943851,0.00001557502,0.00004984624,0.0001197938,0.00004727158],"domain_scores_gemma":[0.9998945,0.00003131388,0.00002290653,0.00001965235,0.00001396105,0.00001765996],"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":[0.0006260278,0.0002715688,0.0004507804,0.0003066184,0.00006111827,0.0002852611,0.00006601236,0.005177644,0.9310738,0.02266252,0.001716967,0.03730176],"study_design_scores_gemma":[0.000435008,0.002396947,0.0007561429,0.00005041652,0.0001763015,0.000887126,0.00005503835,0.01421254,0.932568,0.008445904,0.03995873,0.00005781616],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.683557,0.04896974,0.2343768,0.005084885,0.0006293376,0.0008648315,0.001748499,0.001732799,0.02303615],"genre_scores_gemma":[0.9042893,0.01966558,0.0651736,0.0008335291,0.0001415139,0.0003638566,0.001350789,0.00008938961,0.008092417],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001333002,"threshold_uncertainty_score":0.006953776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0064318981385366,"score_gpt":0.2567349290766394,"score_spread":0.2503030309381027,"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."}}