{"id":"W4377220763","doi":"10.1007/s00894-023-05586-5","title":"Molecular modeling study of natural products as potential bioactive compounds against SARS-CoV-2","year":2023,"lang":"en","type":"article","venue":"Journal of Molecular Modeling","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Universidade Federal de Lavras; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Québec Consortium for Drug Discovery","keywords":"Protein Data Bank (RCSB PDB); Docking (animal); Virtual screening; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Computational biology; Coronavirus disease 2019 (COVID-19); Molecular dynamics; Coronavirus; Chemistry; Bioinformatics; Pharmacology; Biology; Medicine; Biochemistry; Computational chemistry; Infectious disease (medical specialty); Veterinary medicine; Disease","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001549399,0.0003061935,0.000561885,0.000854945,0.0001307874,0.0001874127,0.001278782,0.00007845796,2.054009e-7],"category_scores_gemma":[0.0003379219,0.0002968695,0.0003151924,0.00142115,0.00003383172,0.0008153133,0.0005800152,0.0005812048,0.000004569059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001243569,"about_ca_system_score_gemma":0.0004420182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000395769,"about_ca_topic_score_gemma":0.000001198401,"domain_scores_codex":[0.995856,0.0005229861,0.001088472,0.0005218819,0.001602041,0.0004085527],"domain_scores_gemma":[0.9973101,0.00007925539,0.000572351,0.000557099,0.001397048,0.00008411879],"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":[0.00006094343,0.000178368,0.00000188975,0.00001504318,0.0001600414,0.0004814123,0.0007547173,0.6247842,0.3714656,0.0004128101,0.000006598646,0.00167834],"study_design_scores_gemma":[0.001014894,0.0002944577,0.000009489856,0.00008600878,0.00006029783,0.0001348654,0.0005362856,0.9172961,0.07416152,0.006147051,0.000002272059,0.000256752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5318271,0.0002761565,0.4669321,0.0002630898,0.000456233,0.0001697427,8.26393e-7,0.00003651739,0.00003828219],"genre_scores_gemma":[0.9574071,0.00001769151,0.04223921,0.0001922133,0.00009572112,0.000003844578,0.0000035594,0.00003865032,0.000002032053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.42558,"threshold_uncertainty_score":0.9999483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04046997625535597,"score_gpt":0.3306013250388186,"score_spread":0.2901313487834626,"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."}}