{"id":"W4413318648","doi":"10.1021/acsomega.5c04807","title":"Discovery of Potential Tyrosinase Inhibitors via Machine Learning and Molecular Docking with Experimental Validation of Activity and Skin Permeation","year":2025,"lang":"en","type":"article","venue":"ACS Omega","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada); Discovery Centre","funders":"","keywords":"Tyrosinase; Permeation; Docking (animal); Chemistry; Combinatorial chemistry; Computer science; Biophysics; Computational biology; Biochemistry; Enzyme; Medicine; Membrane; 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":[0.0006695061,0.001210727,0.00128846,0.000476861,0.0002630303,0.0005251457,0.0006212835,0.0005634393,0.001373542],"category_scores_gemma":[0.0009499101,0.0002912173,0.0009830733,0.000728547,0.0002391955,0.0004054194,0.0003617542,0.0007803273,0.0004084541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000552951,"about_ca_system_score_gemma":0.0005097516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002445156,"about_ca_topic_score_gemma":0.002533264,"domain_scores_codex":[0.9997401,0.00007905034,0.0000159441,0.00005295485,0.00006597273,0.00004590528],"domain_scores_gemma":[0.9997773,0.00009021163,0.00004545878,0.00002110412,0.00004957196,0.00001647636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001478209,0.001510415,0.003785273,0.001166798,0.0004164927,0.0003968236,0.0000897347,0.6892204,0.2434204,0.002106744,0.001921492,0.05448717],"study_design_scores_gemma":[0.0001686355,0.00136245,0.001125491,0.00002627073,0.0001785515,0.00009717718,0.00003264877,0.8846161,0.1103241,0.0003206867,0.001700219,0.00004762166],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9425596,0.003787509,0.04626748,0.0003694199,0.00005314633,0.0002508891,0.001424961,0.0007089375,0.004578024],"genre_scores_gemma":[0.9668737,0.002215443,0.0275581,0.00008576242,0.000009654244,0.0002632856,0.001200117,0.00004535527,0.001748554],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002445156,"threshold_uncertainty_score":0.004861832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005673497266606637,"score_gpt":0.2675296303650676,"score_spread":0.261856133098461,"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."}}