{"id":"W3088604570","doi":"10.1016/j.jmgm.2020.107762","title":"Prediction of potential inhibitors of the dimeric SARS-CoV2 main proteinase through the MM/GBSA approach","year":2020,"lang":"en","type":"article","venue":"Journal of Molecular Graphics and Modelling","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Instituto Politécnico Nacional; Consejo Nacional de Ciencia y Tecnología; Swine Innovation Porc","keywords":"Lopinavir; Ritonavir; Protease; Chemistry; Context (archaeology); Molecular mechanics; Drug discovery; Human immunodeficiency virus (HIV); Molecular dynamics; Enzyme; Medicine; Biochemistry; Virology; Biology; Computational chemistry; Viral load; Antiretroviral therapy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006731861,0.0001020679,0.0001909095,0.0000634045,0.00008944752,0.00004244758,0.000479892,0.000046112,1.49554e-7],"category_scores_gemma":[0.00004229153,0.00006271592,0.0002296632,0.000533622,0.0001153229,0.0002267162,0.0001684868,0.0002915982,2.423085e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008604191,"about_ca_system_score_gemma":0.0001077694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001602119,"about_ca_topic_score_gemma":7.02974e-8,"domain_scores_codex":[0.9984282,0.0002698298,0.0004704376,0.0001500698,0.0005762428,0.0001052653],"domain_scores_gemma":[0.9990198,0.00004523128,0.0005224196,0.0001869242,0.0001835527,0.00004206393],"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":[0.00002453908,0.0000496659,0.00002881104,0.00004610127,0.00006086225,0.000006430867,0.0009798234,0.9446645,0.02176671,0.03156506,0.00002078038,0.0007867039],"study_design_scores_gemma":[0.0002546136,0.0001181366,0.00009294813,0.00005197691,0.00004410178,0.00005355109,0.00004766152,0.9466424,0.02082631,0.0317445,0.00006847669,0.00005529495],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3036126,0.0004215572,0.6947153,0.0009860322,0.0001145796,0.0001247074,0.000002699714,0.00000293283,0.00001957693],"genre_scores_gemma":[0.9227374,0.0001113855,0.07689375,0.0001934013,0.00005427875,0.000001614677,4.131291e-7,0.000007193401,6.083109e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6191247,"threshold_uncertainty_score":0.2557481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04042835228804592,"score_gpt":0.2480488519803546,"score_spread":0.2076204996923086,"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."}}