{"id":"W3200507993","doi":"10.1101/2021.09.13.460126","title":"Optimizing epitope conformational ensembles using <i>α</i> -synuclein cyclic peptide “glycindel” scaffolds: A customized immunogen method for generating oligomer-selective antibodies for Parkinson’s disease","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Click Chemistry and Applications","field":"Chemistry","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Genome British Columbia; University of British Columbia","funders":"","keywords":"Epitope; Oligomer; Chemistry; Peptide; Cyclic peptide; Fibril; In silico; Computational biology; Monomer; Conformational ensembles; Linear epitope; Protein structure; Biophysics; Biochemistry; Antibody; Biology; Genetics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007659758,0.0009796215,0.001206813,0.000163555,0.001068364,0.000701911,0.0007530833,0.0006888289,0.00007270163],"category_scores_gemma":[0.0007321118,0.001178977,0.000790995,0.0003408783,0.0001360059,0.0003402425,0.0005661417,0.0005213462,0.000004030667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006635708,"about_ca_system_score_gemma":0.001591012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006972874,"about_ca_topic_score_gemma":0.00000329367,"domain_scores_codex":[0.9956338,0.00009491818,0.001301773,0.001586284,0.0004285118,0.0009547569],"domain_scores_gemma":[0.9949098,0.0007414846,0.001224065,0.001369516,0.001315508,0.0004396114],"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":[0.0002757613,0.0001893912,0.0002781202,0.001954762,0.0006721931,0.000008539514,0.00007681608,0.006585596,0.9895241,0.0001955343,0.0002253918,0.00001378155],"study_design_scores_gemma":[0.001969263,0.000008783495,0.0001536748,0.00092138,0.0007262811,1.578183e-7,0.00008175389,0.08870073,0.8993143,0.000009519586,0.006857798,0.001256291],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8914973,0.002725737,0.1002579,0.0001761797,0.0002816343,0.001406209,0.003207867,0.0004224265,0.00002473896],"genre_scores_gemma":[0.6757264,0.0003051022,0.3201299,0.0001715002,0.001026232,0.002358403,0.00005194842,0.0002142492,0.00001625603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.219872,"threshold_uncertainty_score":0.999066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02338046420527936,"score_gpt":0.272443262201491,"score_spread":0.2490627979962116,"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."}}