{"id":"W3199137400","doi":"10.3390/pathogens10091208","title":"Evaluation of Inhibitory Activity In Silico of In-House Thiomorpholine Compounds between the ACE2 Receptor and S1 Subunit of SARS-CoV-2 Spike","year":2021,"lang":"en","type":"article","venue":"Pathogens","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Universidad Nacional Autónoma de México","keywords":"Spike Protein; In silico; Coronavirus disease 2019 (COVID-19); Spike (software development); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Coronavirus; Protein subunit; Inhibitory postsynaptic potential; Receptor; 2019-20 coronavirus outbreak; Angiotensin-converting enzyme 2; Pharmacology; Virology; Computational biology; Chemistry; Biology; Medicine; Biochemistry; Neuroscience; Computer science; Infectious disease (medical specialty); Disease; Internal medicine; Gene","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":[0.003633647,0.0001067904,0.0003161013,0.0001743064,0.0000238251,0.00001429178,0.0002907744,0.00005829234,0.00000379152],"category_scores_gemma":[0.0005648683,0.00009663499,0.00005868797,0.00087636,0.0001230285,0.0002109627,0.0003138288,0.0001439231,0.000001468317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007691528,"about_ca_system_score_gemma":0.0004121142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001202945,"about_ca_topic_score_gemma":0.0002412352,"domain_scores_codex":[0.9970427,0.00143355,0.0004218484,0.0002703384,0.000697661,0.0001339462],"domain_scores_gemma":[0.9978675,0.0009848245,0.0002565661,0.0004174534,0.0004528518,0.00002081638],"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":[0.00001727058,0.000224783,0.04708,0.00005559827,0.00002210497,0.000003116354,0.002009277,0.004642588,0.9131331,0.0005768975,0.0000238786,0.03221131],"study_design_scores_gemma":[0.0005932164,0.00004405695,0.2971682,0.00006207294,0.00002478343,0.000003154452,0.00006825918,0.06469537,0.6351684,0.002051554,0.00003381854,0.00008706152],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910194,0.0002149427,0.00805951,0.0002273199,0.0001113592,0.0002093591,0.00004700831,0.00001086875,0.0001001957],"genre_scores_gemma":[0.9917706,0.00001828211,0.00813538,0.00002345634,0.00002709239,0.00000777629,0.00000674413,0.000009135645,0.000001549984],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2779647,"threshold_uncertainty_score":0.3940661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09709158716969542,"score_gpt":0.3561395983459761,"score_spread":0.2590480111762807,"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."}}