{"id":"W4404029705","doi":"10.1021/acs.jcim.4c00788","title":"Understanding and Predicting Ligand Efficacy in the μ-Opioid Receptor through Quantitative Dynamical Analysis of Complex Structures","year":2024,"lang":"en","type":"article","venue":"Journal of Chemical Information and Modeling","topic":"Receptor Mechanisms and Signaling","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Opioid; Opioid receptor; Computational biology; Ligand (biochemistry); Chemistry; Computer science; Receptor; Biology; Biochemistry","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":[0.0006853669,0.0005084123,0.000456523,0.0002692244,0.0001482076,0.0003627726,0.0003161595,0.0004090134,0.0005968189],"category_scores_gemma":[0.00129862,0.0001706112,0.0004925479,0.0001651898,0.0003188453,0.0005511441,0.0003195827,0.0006211332,0.0001515333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003166551,"about_ca_system_score_gemma":0.0003610055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001538059,"about_ca_topic_score_gemma":0.001172566,"domain_scores_codex":[0.9998753,0.00003996189,0.000007670473,0.00003060185,0.00002996323,0.0000166269],"domain_scores_gemma":[0.9996057,0.0002241404,0.00007901032,0.00003679202,0.00003095706,0.00002343966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001564452,0.00009740877,0.005239527,0.0001215594,0.00006405255,0.00008124957,0.00004758121,0.9206363,0.053792,0.001869867,0.0004023306,0.01749161],"study_design_scores_gemma":[0.000003534348,0.0000332427,0.0006942902,0.000001869789,0.000004440936,0.000009474965,0.000004262246,0.9958134,0.002884377,0.000437064,0.0001094557,0.000004486164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6929392,0.0007959346,0.3034231,0.000337135,0.00002418321,0.00005713938,0.0003285127,0.0005789708,0.001515878],"genre_scores_gemma":[0.9716802,0.0002707221,0.02721149,0.00006269893,0.00001091384,0.00005960654,0.0002830957,0.0000407349,0.0003806613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001538059,"threshold_uncertainty_score":0.003624618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07721734421023392,"score_gpt":0.3213617009987585,"score_spread":0.2441443567885246,"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."}}