{"id":"W4285592040","doi":"10.1021/acschemneuro.1c00567","title":"Optimizing Epitope Conformational Ensembles Using α-Synuclein Cyclic Peptide “Glycindel” Scaffolds: A Customized Immunogen Method for Generating Oligomer-Selective Antibodies for Parkinson’s Disease","year":2022,"lang":"en","type":"article","venue":"ACS Chemical Neuroscience","topic":"Click Chemistry and Applications","field":"Chemistry","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Genome British Columbia; University of British Columbia","funders":"Canadian Institutes of Health Research; Alberta Innovates; Compute Canada","keywords":"Immunogen; Epitope; Oligomer; Antibody; Alpha-synuclein; Parkinson's disease; Peptide; Cyclic peptide; Chemistry; Disease; Synucleinopathies; Computational biology; Monoclonal antibody; Biophysics; Neuroscience; Biology; Medicine; Biochemistry; Immunology; Pathology","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","sts"],"consensus_categories":[],"category_scores_codex":[0.0003731388,0.0002988768,0.0003542522,0.00005411237,0.001545635,0.0001489056,0.0006990869,0.00007127935,0.00004738024],"category_scores_gemma":[0.000795977,0.0003298811,0.0002522951,0.0003373233,0.0001854325,0.0002674253,0.0003997039,0.000210936,9.606933e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000213555,"about_ca_system_score_gemma":0.0002274523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001531785,"about_ca_topic_score_gemma":3.463335e-7,"domain_scores_codex":[0.9976083,0.00003503382,0.0005635911,0.0007897712,0.0004036679,0.0005996479],"domain_scores_gemma":[0.9980588,0.0008336552,0.0003452688,0.0004053688,0.0001428704,0.0002140496],"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":[0.0002490405,0.0001193512,0.00006395939,0.00009572467,0.00001371986,0.000001615113,0.0002190097,0.007692769,0.9903489,0.0002243719,0.0003378307,0.0006336595],"study_design_scores_gemma":[0.001021676,0.00001162317,0.000008865923,0.00001932771,0.00006063051,0.00002797406,0.000213195,0.2119265,0.7760562,0.0003314113,0.0100037,0.0003188532],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9773535,0.0001360405,0.02051331,0.0003609591,0.00008800366,0.0004909157,0.0007315642,0.0001286608,0.0001970734],"genre_scores_gemma":[0.9347968,0.00002235005,0.06263614,0.0006651295,0.0002200811,0.001212963,0.0002121444,0.00004592539,0.0001884967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2142927,"threshold_uncertainty_score":0.9999153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03618598867269753,"score_gpt":0.3123339694128637,"score_spread":0.2761479807401662,"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."}}