{"id":"W3108778136","doi":"10.3390/biom10121634","title":"Structure-Based Virtual Screening of Ultra-Large Library Yields Potent Antagonists for a Lipid GPCR","year":2020,"lang":"en","type":"article","venue":"Biomolecules","topic":"Receptor Mechanisms and Signaling","field":"Biochemistry, Genetics and Molecular Biology","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Sherbrooke","funders":"","keywords":"Virtual screening; G protein-coupled receptor; Antagonist; Ligand efficiency; Computational biology; Chemistry; Receptor; Ligand (biochemistry); Docking (animal); Pharmacology; Drug discovery; Stereochemistry; Medicine; Biochemistry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003419653,0.00100213,0.001202058,0.0007824181,0.0002949911,0.0007562235,0.0007457454,0.0004891322,0.002830054],"category_scores_gemma":[0.0004557551,0.0002491028,0.0006679205,0.0007780018,0.0002322291,0.0002697285,0.0006413049,0.0005530769,0.000808469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004682676,"about_ca_system_score_gemma":0.0005434811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008224565,"about_ca_topic_score_gemma":0.001845228,"domain_scores_codex":[0.9997403,0.00006071473,0.00001644025,0.00006069215,0.00006899381,0.00005285219],"domain_scores_gemma":[0.9999113,0.00002992307,0.000012553,0.00001044424,0.00001562775,0.00002018211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003634196,0.002174833,0.004136875,0.0013351,0.0005220904,0.001480366,0.0001627911,0.1069242,0.7497815,0.002369764,0.005280477,0.1221978],"study_design_scores_gemma":[0.001945904,0.01873535,0.01133611,0.0001659833,0.001466688,0.00314103,0.0003586542,0.2388862,0.6736441,0.002126541,0.04795342,0.000239964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9601055,0.005145344,0.0192866,0.0003443863,0.00007978438,0.0005201063,0.004664807,0.001274263,0.008579236],"genre_scores_gemma":[0.9583902,0.003593049,0.02413359,0.0002371769,0.00001777245,0.0003707999,0.008385491,0.00007409523,0.004797913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002830054,"threshold_uncertainty_score":0.009467483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01410635034397305,"score_gpt":0.2328977621259575,"score_spread":0.2187914117819845,"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."}}