{"id":"W2886789253","doi":"10.1016/j.bbagen.2018.08.010","title":"Revealing the atomistic details behind the binding of B7–1 to CD28 and CTLA-4: A comprehensive protein-protein modelling study","year":2018,"lang":"en","type":"article","venue":"Biochimica et Biophysica Acta (BBA) - General Subjects","topic":"Diabetes and associated disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National Institute of General Medical Sciences; University of Alberta; Alberta Cancer Foundation; Compute Canada; Li Ka Shing Foundation","keywords":"CD28; Docking (animal); Immunological synapse; Binding affinities; Computational biology; Chemistry; Affinities; Protein–protein interaction; T cell; Biology; Biophysics; T-cell receptor; Receptor; Biochemistry; Immunology; Medicine; Immune system","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":[0.0003218474,0.0003597373,0.0003412923,0.00006238263,0.000426286,0.0001222583,0.0005065766,0.0001354102,0.00000395084],"category_scores_gemma":[0.00007473063,0.0002417712,0.0001505477,0.000271455,0.0002682011,0.00001185193,0.000389726,0.0001892171,0.000008627669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002004163,"about_ca_system_score_gemma":0.00008475155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002118205,"about_ca_topic_score_gemma":0.0000845319,"domain_scores_codex":[0.9979125,0.0002780294,0.0003791312,0.0006271637,0.0002948044,0.000508321],"domain_scores_gemma":[0.9987356,0.00004307536,0.0002765299,0.000612678,0.0002069654,0.000125151],"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":[0.0001342297,0.0001651421,0.00004339966,0.00002365886,0.0002252623,9.659004e-7,0.0008274562,0.0001148638,0.9979848,0.00006253646,0.0001754628,0.000242177],"study_design_scores_gemma":[0.0006859443,0.0009746222,0.0007731008,0.00007234253,0.00009919336,0.000001344386,0.0006647731,0.00101603,0.9949449,0.0001520466,0.0002590551,0.0003566795],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968802,0.0001824522,0.0001561794,0.0007341954,0.00008344276,0.001747303,0.00005352968,0.00002066213,0.0001420219],"genre_scores_gemma":[0.9981542,0.00002992019,0.000529958,0.0004387927,0.0003639122,0.0001383074,0.00004197533,0.00005324673,0.0002497116],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003039977,"threshold_uncertainty_score":0.9859144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01655612832647096,"score_gpt":0.2568946246959509,"score_spread":0.2403384963694799,"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."}}