{"id":"W4414622237","doi":"10.1016/j.foodres.2025.117637","title":"In silico and molecular docking approaches in food-derived bioactive peptide discovery: Trends, challenges, and prospects","year":2025,"lang":"en","type":"article","venue":"Food Research International","topic":"Protein Hydrolysis and Bioactive Peptides","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"In silico; Docking (animal); Binding affinities; Peptide; Amino acid residue; Protein–ligand docking","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":[0.0004999932,0.000132719,0.0001444875,0.0004608354,0.00004693917,0.00008286467,0.0001962787,0.0001117852,0.000003785733],"category_scores_gemma":[0.0002008953,0.0001219684,0.00003818586,0.0001931798,0.0002066312,0.00002964746,0.0004201183,0.0002479555,4.191952e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006290103,"about_ca_system_score_gemma":0.00006085352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006155237,"about_ca_topic_score_gemma":0.0009679652,"domain_scores_codex":[0.9986234,0.0001536614,0.0001691287,0.0005267858,0.0002500872,0.000276954],"domain_scores_gemma":[0.9996548,0.0000379635,0.00003584236,0.0001563171,0.00006799288,0.000047126],"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":[0.0007079687,0.0005579293,0.01010696,0.0001066947,0.0005448049,0.00003229682,0.0006335632,0.00007805879,0.9052281,0.04383992,0.0001424694,0.03802123],"study_design_scores_gemma":[0.002461595,0.001286591,0.09193551,0.0002149493,0.000007230314,0.00001370762,0.0011037,0.001044573,0.8826695,0.01168948,0.007201319,0.0003718518],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9813356,0.00913817,0.0000459419,0.003108329,0.00004201509,0.0002468174,0.00002650222,0.000003936247,0.0060527],"genre_scores_gemma":[0.9979056,0.001388238,0.0001185513,0.00005023635,0.0000667735,0.0001445376,0.00003767087,0.00001003345,0.000278349],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08182855,"threshold_uncertainty_score":0.4973727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06532146263844932,"score_gpt":0.3331994338544852,"score_spread":0.2678779712160358,"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."}}