{"id":"W4416714296","doi":"10.1038/s42004-025-01763-0","title":"Challenging AlphaFold in predicting proteins with large-scale allosteric transitions","year":2025,"lang":"en","type":"article","venue":"Communications Chemistry","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Michael Smith Health Research BC; University of British Columbia Hospital; Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Allosteric regulation; Sequence (biology); Class (philosophy); Function (biology); Protein structure; Conformational ensembles","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":[0.0001001037,0.0001236058,0.0001111312,0.00003242922,0.0001801251,0.00001900734,0.0005242194,0.000135853,0.000007616832],"category_scores_gemma":[0.00002578492,0.0001260575,0.00004200121,0.0002147708,0.00009157819,0.000005616123,0.0002399765,0.0002137665,8.393806e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002637813,"about_ca_system_score_gemma":0.00009173353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000841067,"about_ca_topic_score_gemma":0.0001950018,"domain_scores_codex":[0.9993075,0.00002980685,0.0001818288,0.0002249894,0.0000594196,0.000196454],"domain_scores_gemma":[0.9985967,0.00001116091,0.00004796732,0.001252334,0.00005562794,0.00003624333],"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":[0.00006373729,0.0002861416,0.009759765,0.0001845065,0.00009133575,0.000002501682,0.0004460385,0.000371407,0.9863731,0.0003790734,0.0001032775,0.001939166],"study_design_scores_gemma":[0.006273312,0.0002085006,0.01785959,0.001304719,0.0002003456,0.0001251192,0.006191237,0.02616605,0.8641801,0.001601417,0.07429779,0.001591749],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9045227,0.00425867,0.03860745,0.002947896,0.00003240806,0.0006360619,0.0000805625,0.00007918032,0.04883511],"genre_scores_gemma":[0.9914846,0.000266987,0.006938434,0.0001374547,0.00002561139,0.000200096,0.0003504368,0.00001396862,0.0005824544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1221929,"threshold_uncertainty_score":0.5140477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00624085971127268,"score_gpt":0.2450938076370232,"score_spread":0.2388529479257505,"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."}}