{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004751579,0.0009793311,0.0007028292,0.001361838,0.0002363581,0.0005747168,0.0008973227,0.0009562652,0.001371377],"category_scores_gemma":[0.001469207,0.0003502442,0.0007314344,0.0007749334,0.000433716,0.0007349622,0.0007078494,0.0007768499,0.0003878403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001010213,"about_ca_system_score_gemma":0.0007430094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01113121,"about_ca_topic_score_gemma":0.01435835,"domain_scores_codex":[0.9997467,0.00008887132,0.000008665375,0.00007724691,0.00004793672,0.0000305842],"domain_scores_gemma":[0.9995148,0.0003102726,0.00006180518,0.00003223841,0.00005295933,0.00002797657],"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":[0.0001237898,0.0001006077,0.001385158,0.00007960621,0.00007332213,0.00007608649,0.00002170617,0.9156209,0.003560864,0.00311393,0.001893411,0.07395069],"study_design_scores_gemma":[0.000002854009,0.000009948921,0.0001130218,0.000001570013,0.000004559616,0.000004882399,0.000001495657,0.9978156,0.0003222659,0.001604748,0.0001175745,0.000001371078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1731233,0.00171629,0.8150198,0.0009565205,0.00005353395,0.00010845,0.0007813179,0.004024514,0.004216269],"genre_scores_gemma":[0.9066753,0.0006576423,0.08678946,0.0003864865,0.00007234416,0.0001089396,0.001753156,0.0001288029,0.003427934],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01113121,"threshold_uncertainty_score":0.02213281,"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."}}