{"id":"W4309621347","doi":"10.21203/rs.3.rs-2235299/v1","title":"Genomic landscape of the emerging XDR Salmonella Typhi for mining druggable targets clpP, hisH, folP and gpmI and screening of novel TCM inhibitors, molecular docking and simulation analyses","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Salmonella and Campylobacter epidemiology","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Penn Center for Musculoskeletal Disorders; Directorate for Biological Sciences; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Alliance de recherche numérique du Canada; Universidade Estadual de Campinas; Centro Nacional de Processamento de Alto Desempenho em São Paulo; University of Karachi","keywords":"Druggability; Biology; Computational biology; Salmonella typhi; Docking (animal); Homology modeling; Gene; Genome; Genetics; Biochemistry; Enzyme; Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001032394,0.0002918516,0.0003786251,0.0004749846,0.0002259237,0.0003199153,0.0001897822,0.0002477546,0.002027899],"category_scores_gemma":[0.0001824205,0.0001202942,0.0004496572,0.0006767474,0.000080099,0.0001273878,0.0001804709,0.0001825749,0.0002039191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002730971,"about_ca_system_score_gemma":0.0002849053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002632332,"about_ca_topic_score_gemma":0.002641415,"domain_scores_codex":[0.9999655,0.000006632613,0.000002221304,0.000009564197,0.000007741794,0.000008242425],"domain_scores_gemma":[0.999954,0.00001630401,0.00001114033,0.000002405382,0.000008067159,0.000008123292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001975935,0.0005528057,0.1509408,0.00113142,0.0003951979,0.003142892,0.000401416,0.3426971,0.4386279,0.004737969,0.003398678,0.05199782],"study_design_scores_gemma":[0.0001104813,0.001307324,0.1444639,0.00006310208,0.0003050389,0.001265055,0.0007662844,0.8137068,0.02925797,0.002683934,0.006014609,0.0000554254],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919621,0.0005676827,0.003986121,0.0001284412,0.00000407346,0.00002856768,0.001956703,0.0001270956,0.001239328],"genre_scores_gemma":[0.9882482,0.0004899417,0.006138829,0.00003332401,0.000002229008,0.00003516516,0.004453263,0.00001626238,0.000582777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002632332,"threshold_uncertainty_score":0.006784022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1292982129723803,"score_gpt":0.3971591877988865,"score_spread":0.2678609748265063,"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."}}