{"id":"W3201784646","doi":"10.1021/acs.jmedchem.1c00655","title":"Computational Design of Potent D-Peptide Inhibitors of SARS-CoV-2","year":2021,"lang":"en","type":"article","venue":"Journal of Medicinal Chemistry","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research; National Research Council of Science and Technology; National Research Foundation of Korea; Government of Canada","keywords":"Immunogenicity; Chemistry; Peptidomimetic; Peptide; Vero cell; IC50; In vitro; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Antibody; Peptide library; Virology; Receptor; Biochemistry; Peptide sequence; Coronavirus disease 2019 (COVID-19); Immunology; Biology; Medicine; Gene","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":[0.0004391627,0.001003436,0.001297326,0.000643505,0.0005151974,0.0008139465,0.001025895,0.0008572363,0.004206941],"category_scores_gemma":[0.001053664,0.0004433336,0.0007409758,0.0004855076,0.0003850132,0.0004229193,0.0005345864,0.0007931367,0.0004245728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007229721,"about_ca_system_score_gemma":0.00201802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005108487,"about_ca_topic_score_gemma":0.01137251,"domain_scores_codex":[0.9998876,0.00003510812,0.000005391229,0.0000162776,0.00002486247,0.00003075436],"domain_scores_gemma":[0.9997131,0.0001918584,0.00002215441,0.000009399583,0.00003569199,0.00002784582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005022147,0.0002016062,0.001851504,0.0003295832,0.0001466044,0.0003232174,0.00003830643,0.9705629,0.001989465,0.007077127,0.003287277,0.01369012],"study_design_scores_gemma":[0.0002807509,0.0002066246,0.0002360406,0.00002159273,0.00006725477,0.00003451107,0.0000517402,0.9939612,0.000639905,0.002532147,0.001960229,0.000008011321],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8132964,0.006719149,0.09603988,0.002709572,0.0004513762,0.0006575263,0.004574907,0.001828455,0.07372277],"genre_scores_gemma":[0.9269146,0.00135787,0.0625504,0.0007396705,0.00005244524,0.0006005687,0.003558528,0.0001438985,0.004081967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005108487,"threshold_uncertainty_score":0.01407367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05664201087870851,"score_gpt":0.3550462167054464,"score_spread":0.2984042058267379,"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."}}