{"id":"W4402190012","doi":"10.1021/jacs.4c05297","title":"Converting the Amyloidogenic Islet Amyloid Polypeptide into a Potent Nonaggregating Peptide Ligand by Side Chain-to-Side Chain Macrocyclization","year":2024,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Chemical Synthesis and Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"PROTEO; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Maurice Wilkins Centre for Molecular Biodiscovery; Neurological Foundation of New Zealand","keywords":"Chemistry; Side chain; Islet; Peptide; Ligand (biochemistry); Chain (unit); Amyloid (mycology); Biochemistry; Stereochemistry; Receptor; Polymer; Organic chemistry; Internal medicine; Insulin","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":[],"consensus_categories":[],"category_scores_codex":[0.0005523533,0.0002568097,0.0003847535,0.00002080758,0.0001997204,0.0001101303,0.0006380277,0.00008479874,0.000007688737],"category_scores_gemma":[0.0003985971,0.000152845,0.00106982,0.0005118093,0.0003149131,0.00001045926,0.000337303,0.0004345129,0.000005775992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001572215,"about_ca_system_score_gemma":0.00008926795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001475231,"about_ca_topic_score_gemma":0.000005877353,"domain_scores_codex":[0.9981241,0.00009052786,0.0006175377,0.0003522682,0.000436824,0.0003787259],"domain_scores_gemma":[0.9986926,0.0001510385,0.0005316574,0.0003279757,0.000116338,0.0001804215],"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":[0.0000380782,0.00003596718,0.0003393034,0.00002322634,0.0003549542,0.000002062124,0.0003291766,0.00007969925,0.9777135,0.000002763083,0.01064412,0.01043714],"study_design_scores_gemma":[0.0001641409,0.00005602707,0.00007840572,0.0001227816,0.0001585935,0.00005454425,0.0007400233,0.001470677,0.9839237,0.00008628055,0.01292785,0.0002169732],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9860222,0.001712646,0.001962263,0.009991399,0.00008804781,0.0001085027,0.0000150243,0.00001355854,0.00008636292],"genre_scores_gemma":[0.9928118,0.0004544189,0.001086615,0.004406842,0.0008819886,0.000007832943,0.00001198402,0.00004298385,0.0002955211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01022017,"threshold_uncertainty_score":0.6232837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004723133754003017,"score_gpt":0.2339015689631613,"score_spread":0.2291784352091583,"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."}}