{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001968266,0.0002892637,0.0001892691,0.0001624674,0.0001168272,0.0002058207,0.0002270427,0.0001779753,0.0004921699],"category_scores_gemma":[0.0002468654,0.000103937,0.0001787399,0.0001282818,0.0001235483,0.0001716234,0.0002127181,0.0002234914,0.000136246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002267773,"about_ca_system_score_gemma":0.0001503827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003205772,"about_ca_topic_score_gemma":0.0006316241,"domain_scores_codex":[0.9999123,0.00001239666,0.000004420161,0.00002151608,0.00003366758,0.00001579097],"domain_scores_gemma":[0.9999162,0.00002117477,0.00002292539,0.000009028712,0.00001268182,0.00001803354],"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":[0.0001261197,0.0001099145,0.0009718472,0.00004398653,0.00001836158,0.00008123359,0.00002611216,0.02983734,0.9607342,0.0002947218,0.00008566127,0.007670408],"study_design_scores_gemma":[0.00003749062,0.001009032,0.001795745,0.000006044434,0.00002437664,0.0001446422,0.00003346416,0.1393521,0.8563901,0.000152715,0.001035441,0.00001883707],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874423,0.000128631,0.01166415,0.00002050934,0.000006058723,0.0000246741,0.00004667132,0.00007956127,0.0005874853],"genre_scores_gemma":[0.9870881,0.00009415131,0.01239577,0.00001646352,0.000002121366,0.00003048817,0.00008134475,0.00002015522,0.0002714224],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004921699,"threshold_uncertainty_score":0.001646399,"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."}}