{"id":"W4206752585","doi":"10.26434/chemrxiv.14130353.v2","title":"Accelerating the Discovery of the Beyond Rule of Five Compounds That Have High Affinities Toward SARS-CoV-2 Spike RBD","year":2021,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Science and Engineering Research Board; Compute Canada; Shastri Indo-Canadian Institute","keywords":"Spike (software development); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Molecular dynamics; Coronavirus disease 2019 (COVID-19); Affinities; Computational biology; Binding affinities; Drug discovery; 2019-20 coronavirus outbreak; Spike Protein; Chemistry; Biology; Computer science; Bioinformatics; Stereochemistry; Virology; Medicine; Computational chemistry; Receptor; Infectious disease (medical specialty); Disease; Biochemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004847132,0.00075721,0.001689269,0.0005418381,0.0003736608,0.001166919,0.0006143604,0.0005437915,0.002610299],"category_scores_gemma":[0.001026227,0.0003156803,0.0008802049,0.0004695381,0.0003047187,0.0004866314,0.0004654147,0.000647822,0.0004210977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006647057,"about_ca_system_score_gemma":0.001686135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002679575,"about_ca_topic_score_gemma":0.005362258,"domain_scores_codex":[0.9998112,0.00004097077,0.00001146538,0.00003819999,0.00006107643,0.00003712466],"domain_scores_gemma":[0.9997504,0.00009930036,0.00005205054,0.00002603993,0.00003797028,0.0000341805],"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":[0.001253607,0.0007249499,0.00963751,0.001181252,0.0004109646,0.0009352828,0.00007768114,0.8072665,0.07125753,0.02829122,0.003973853,0.07498967],"study_design_scores_gemma":[0.0005151423,0.001076608,0.001485198,0.00005615831,0.0003081152,0.0002309766,0.00005577694,0.952032,0.02856816,0.006229006,0.00939425,0.00004859309],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8891555,0.004522073,0.08125074,0.0008676846,0.0001255729,0.0003072537,0.001876185,0.00127335,0.02062152],"genre_scores_gemma":[0.9443539,0.002304011,0.04918901,0.0003183054,0.0000196311,0.0001427269,0.001550252,0.00009573708,0.002026428],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002679575,"threshold_uncertainty_score":0.008732319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08383804122433648,"score_gpt":0.3117945795876478,"score_spread":0.2279565383633114,"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."}}