{"id":"W3010775563","doi":"10.1101/2020.03.19.999235","title":"Evolution of an enzyme conformational ensemble guides design of an efficient biocatalyst","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; National Science Foundation; Kinship Foundation; Pew Charitable Trusts; David and Lucile Packard Foundation; Office of the President, University of California; Ministero dello Sviluppo Economico","keywords":"Protein design; Biocatalysis; Active site; Enzyme; Protein engineering; Directed evolution; Catalysis; Rational design; Chemistry; Conformational change; Protein structure; Stereochemistry; Crystallography; Materials science; Nanotechnology; Biochemistry; Reaction mechanism","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000416393,0.0003303302,0.0003960516,0.0001255993,0.0000609449,0.00003292673,0.0005211861,0.0005060677,0.000005778805],"category_scores_gemma":[0.0001665221,0.0003508478,0.0001160528,0.0001881007,0.0001561395,0.00001301576,0.0003176692,0.0002023768,0.000002929817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006742537,"about_ca_system_score_gemma":0.0008415693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005204441,"about_ca_topic_score_gemma":0.000002016843,"domain_scores_codex":[0.9981446,0.0001342991,0.0005924634,0.0005767515,0.0003029008,0.0002490246],"domain_scores_gemma":[0.9976788,0.00001147607,0.0005812692,0.0009558406,0.000593211,0.0001793869],"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":[0.0001243552,0.00009268537,0.0001073371,0.0002333994,0.00009083449,0.000002966178,0.000008002975,0.01828439,0.9801651,0.0008561508,0.00003170205,0.000003123304],"study_design_scores_gemma":[0.0003606531,0.0002948586,0.004435082,0.00007042181,0.00006796846,5.505926e-8,0.000005566081,0.02704456,0.9671858,0.00001339652,0.0001638982,0.0003577349],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8339823,0.0007061172,0.1640689,0.0000174804,0.0002294413,0.0005118,0.0004377727,0.00003942038,0.000006759545],"genre_scores_gemma":[0.9673024,0.00003107955,0.03228695,0.00004432775,0.0002312527,0.00004112247,0.00001635328,0.00004570825,7.439506e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1333201,"threshold_uncertainty_score":0.9998944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01179913048829206,"score_gpt":0.222362458263748,"score_spread":0.2105633277754559,"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."}}