{"id":"W4200304835","doi":"10.1101/2021.12.20.472081","title":"De Novo Design of Immunoglobulin-like Domains","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Structural Genomics Consortium; Princess Margaret Cancer Centre; University of Toronto","funders":"Genentech; Ministerio de Ciencia e Innovación; McGill University; European Synchrotron Radiation Facility; Ontario Genomics Institute; European Federation of Pharmaceutical Industries and Associations; European Social Fund; Merck KGaA; Ontario Genomics; Agencia Estatal de Investigación; Genome Canada; Bayer; Bristol-Myers Squibb; Pfizer; Agència de Gestió d'Ajuts Universitaris i de Recerca; National Science Foundation","keywords":"Design for manufacturability; Antibody; Computational biology; Protein engineering; Hypervariable region; Computer science; Structural motif; Protein design; Scaffold protein; Protein structure; Chemistry; Biology; Immunology; Engineering; Biochemistry; Enzyme; Signal transduction","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":[0.0002735544,0.0002705429,0.0002372613,0.0002754692,0.0001086736,0.0004345247,0.0004671098,0.0003627379,0.0008905933],"category_scores_gemma":[0.000276704,0.0002221,0.0002604786,0.0001696236,0.0001773938,0.0002288084,0.0003514721,0.0005167038,0.0004574118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004655582,"about_ca_system_score_gemma":0.0002983308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003000448,"about_ca_topic_score_gemma":0.0005811744,"domain_scores_codex":[0.9998711,0.00002236928,0.00001175498,0.00002919402,0.00003633255,0.00002913183],"domain_scores_gemma":[0.9998366,0.00003110622,0.00005379699,0.00001824522,0.00002894545,0.00003135031],"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":[0.00008082022,0.0001497049,0.0004336732,0.0001240878,0.00002558788,0.00018009,0.00005431434,0.01957335,0.958361,0.006173356,0.0003995184,0.01444459],"study_design_scores_gemma":[0.0001064967,0.0006583182,0.000838428,0.00001616908,0.00003236004,0.0002254568,0.00003740126,0.06240059,0.9150131,0.001377064,0.01926872,0.00002582124],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.844875,0.0007476255,0.1445683,0.0001937404,0.0001052673,0.0001923769,0.0003229166,0.0003555289,0.00863934],"genre_scores_gemma":[0.894523,0.0005385952,0.1004154,0.0001110041,0.00001559375,0.0001001969,0.0004012232,0.00008090778,0.003814176],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008905933,"threshold_uncertainty_score":0.003377855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02792874938978158,"score_gpt":0.2711914074545013,"score_spread":0.2432626580647197,"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."}}