{"id":"W4290998851","doi":"10.3390/molecules27165114","title":"Ligand Binding Prediction Using Protein Structure Graphs and Residual Graph Attention Networks","year":2022,"lang":"en","type":"article","venue":"Molecules","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Computational biology; Drug discovery; Pooling; Ligand (biochemistry); Graph; Computer science; Protein ligand; Target protein; Chemistry; Artificial intelligence; Machine learning; Biology; Biochemistry; Theoretical computer science; Receptor","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003056193,0.0001099002,0.00009489698,0.0002188834,0.0004846445,0.0001633594,0.0002437003,0.00003186445,0.000003354263],"category_scores_gemma":[0.00001765324,0.0001186338,0.00003923987,0.0005825808,0.00003668567,0.0002897022,0.0004259345,0.0001901646,2.296302e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004536923,"about_ca_system_score_gemma":0.00003701899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001611694,"about_ca_topic_score_gemma":0.000002753278,"domain_scores_codex":[0.9986939,0.0002763534,0.0001639223,0.0003538271,0.0003355057,0.0001765267],"domain_scores_gemma":[0.9996082,0.00004292185,0.00009271826,0.0001802731,0.0000312046,0.00004469362],"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":[0.00002494433,0.00003879246,0.003073049,0.00002324527,0.00004690425,0.00003352352,0.0003667338,0.7893255,0.1483904,0.05007214,0.0001982323,0.008406497],"study_design_scores_gemma":[0.0003163536,0.00009928802,0.01628618,0.00002570547,0.0000146769,0.00009229057,0.00006704785,0.9260562,0.002724118,0.05403887,0.00007964233,0.0001996423],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6169704,0.0001177373,0.3824088,0.00008542753,0.0001797223,0.0001459133,0.00001526355,0.00006221836,0.00001451644],"genre_scores_gemma":[0.9536577,0.000002504034,0.04617475,0.00005120891,0.00003292613,0.00001815573,0.00003075103,0.00001046063,0.00002150066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3366874,"threshold_uncertainty_score":0.4837746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01458310590133127,"score_gpt":0.2515321246500294,"score_spread":0.2369490187486981,"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."}}