{"id":"W4386691480","doi":"10.1038/s41467-023-40023-4","title":"The H163A mutation unravels an oxidized conformation of the SARS-CoV-2 main protease","year":2023,"lang":"en","type":"article","venue":"Nature Communications","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Institute of General Medical Sciences; Centre for Bioengineering and Biotechnology, University of Waterloo; Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada; University of Waterloo; National Institutes of Health; National Science Foundation; Government of Canada; Division of Materials Research; Canada First Research Excellence Fund","keywords":"Metadynamics; Point mutation; Chemistry; Protease; Mutant; Mutation; Biophysics; Protein structure; Cysteine; Conformational change; Transition (genetics); Molecular dynamics; Stereochemistry; Enzyme; Biochemistry; Biology; Computational chemistry","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":[0.001714751,0.0001080192,0.000106073,0.000110764,0.0007894172,0.0001314291,0.003928245,0.0001130473,6.290597e-7],"category_scores_gemma":[0.000852493,0.00007111081,0.00009001427,0.001589753,0.0001951619,0.0006627205,0.0009380305,0.0005407884,0.00002197676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006232995,"about_ca_system_score_gemma":0.0002632757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002765161,"about_ca_topic_score_gemma":0.000194593,"domain_scores_codex":[0.9978242,0.001047363,0.0003648326,0.0001616876,0.0004322969,0.0001696266],"domain_scores_gemma":[0.9951308,0.001473709,0.0002879722,0.002764619,0.0003146837,0.00002816556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001396694,0.00009396517,0.00006722818,0.00001655648,0.00003069215,7.208561e-7,0.002970602,0.003823654,0.01723342,0.9511179,0.003484229,0.02114712],"study_design_scores_gemma":[0.000444422,0.00003281251,0.02600531,0.00003763117,0.00001603937,0.0000201967,0.0002996516,0.828311,0.03353584,0.09055435,0.0205511,0.0001917005],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4351586,0.001953581,0.4382797,0.1085896,0.002176851,0.005064222,0.0001758594,0.001168131,0.007433366],"genre_scores_gemma":[0.9657187,0.00005023443,0.03348606,0.0004977263,0.00001862528,0.0001120592,0.00005723626,0.000008921678,0.00005042247],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8605635,"threshold_uncertainty_score":0.7299722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05122601312445628,"score_gpt":0.376659922860003,"score_spread":0.3254339097355467,"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."}}