{"id":"W2506776793","doi":"10.1016/j.ejmech.2016.07.078","title":"Bridging computational modeling with amino acid replacements to investigate GHS-R1a-peptidomimetic recognition","year":2016,"lang":"en","type":"article","venue":"European Journal of Medicinal Chemistry","topic":"Regulation of Appetite and Obesity","field":"Neuroscience","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University; Lawson Health Research Institute","funders":"","keywords":"Peptidomimetic; Chemistry; Docking (animal); Ghrelin; G protein-coupled receptor; Molecular mechanics; Homology modeling; Stereochemistry; Receptor; Agonist; Ligand (biochemistry); Molecular model; Binding site; Molecular dynamics; Biophysics; Biochemistry; Computational chemistry; Peptide; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008404512,0.0001460917,0.0001827926,0.00007607512,0.0001050851,0.00003483642,0.0002483208,0.00001778391,0.0001535006],"category_scores_gemma":[0.0006372852,0.0000958813,0.00005322312,0.000153076,0.0001110368,0.0002088039,0.00004852381,0.0001849422,0.00009135339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006495031,"about_ca_system_score_gemma":0.00007732446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.759325e-7,"about_ca_topic_score_gemma":6.5752e-8,"domain_scores_codex":[0.9982178,0.0001579492,0.0004915869,0.0002464094,0.0006861973,0.0002000112],"domain_scores_gemma":[0.998894,0.00008417574,0.0003607408,0.0001410367,0.000197183,0.0003228498],"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":[0.0003904199,0.00003796327,0.0002568947,0.00003292519,0.00001298293,0.0003492095,0.0001648386,0.003980394,0.9793946,0.000004307513,0.000524104,0.01485141],"study_design_scores_gemma":[0.00283189,0.0004085047,0.0009931208,0.001747006,0.00004452649,0.001450327,0.00007216876,0.004163223,0.9872661,0.0002304425,0.0005505707,0.0002421464],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9025729,0.00001749648,0.09199111,0.001691167,0.00007818083,0.00005367151,0.000004180643,0.00002011881,0.003571161],"genre_scores_gemma":[0.9948122,0.00001444272,0.003498034,0.000866055,0.0004844316,4.9284e-7,0.00000200874,0.00002352537,0.0002988416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09223926,"threshold_uncertainty_score":0.3909926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03815599548495353,"score_gpt":0.2439566798306961,"score_spread":0.2058006843457426,"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."}}