{"id":"W4403762819","doi":"10.1021/acs.jmedchem.4c02009","title":"Rational Design of Macrocyclic Noncovalent Inhibitors of SARS-CoV-2 M<sup>pro</sup> from a DNA-Encoded Chemical Library Screening Hit That Demonstrate Potent Inhibition against Pan-Coronavirus Homologues and Nirmatrelvir-Resistant Variants","year":2024,"lang":"en","type":"article","venue":"Journal of Medicinal Chemistry","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Xenon Pharmaceuticals (Canada)","funders":"","keywords":"Chemistry; Rational design; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); DNA; Stereochemistry; 2019-20 coronavirus outbreak; Coronavirus disease 2019 (COVID-19); Coronavirus; Combinatorial chemistry; Structure–activity relationship; Chemical synthesis; Biochemistry; Virology; Nanotechnology; In vitro","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":[0.00018737,0.0006285237,0.0003465421,0.0003236759,0.0001378412,0.0003359669,0.0004661388,0.0002758258,0.001630727],"category_scores_gemma":[0.0002037395,0.0001934014,0.0002474354,0.0003232783,0.0002310267,0.0002650935,0.0002974533,0.0004501565,0.0005310994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003986635,"about_ca_system_score_gemma":0.0004042334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004257103,"about_ca_topic_score_gemma":0.001664571,"domain_scores_codex":[0.9998969,0.00001796341,0.000008011568,0.00002270302,0.00002754884,0.00002689466],"domain_scores_gemma":[0.9999403,0.000009320808,0.00002067129,0.000004915043,0.00001025755,0.00001461864],"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":[0.0006267789,0.0005752681,0.0004552364,0.0003140156,0.00005198173,0.0004741368,0.00006738299,0.006570752,0.9596,0.001455416,0.0004488365,0.02936026],"study_design_scores_gemma":[0.0002752732,0.005715754,0.00113975,0.00002226926,0.00006743211,0.0004363564,0.00004108267,0.005611336,0.9772151,0.0002325417,0.009211306,0.0000317366],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9482518,0.005199391,0.0318043,0.000247003,0.00008445224,0.001118432,0.001112862,0.0004893605,0.01169251],"genre_scores_gemma":[0.9701968,0.003893604,0.01978759,0.0001803648,0.00001838077,0.0002423488,0.001067318,0.00004347106,0.004570016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001630727,"threshold_uncertainty_score":0.005455315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06318375853030077,"score_gpt":0.31847895523559,"score_spread":0.2552951967052892,"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."}}