{"id":"W2975107521","doi":"10.1101/442806","title":"Rapid covalent-probe discovery by electrophile fragment screening","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Click Chemistry and Applications","field":"Chemistry","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Israel Science Foundation; Pfizer; Rising Tide Foundation; Ontario Genomics; Ontario Ministry of Research, Innovation and Science; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Genome Canada; Fundação de Amparo à Pesquisa do Estado de São Paulo; Novartis Pharma; Ontario Genomics Institute; European Federation of Pharmaceutical Industries and Associations; Merck KGaA","keywords":"Electrophile; Chemistry; Covalent bond; Combinatorial chemistry; Ligand efficiency; Fragment (logic); Ligand (biochemistry); Drug discovery; Cysteine; Selectivity; Deubiquitinating enzyme; Stereochemistry; High-throughput screening; Enzyme; Biochemistry; Organic chemistry; Gene; Receptor; Computer science; Ubiquitin","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002924141,0.0008419654,0.0006641782,0.00007837793,0.0003874027,0.0005209252,0.001154513,0.000869864,0.001219922],"category_scores_gemma":[0.0001293768,0.0009702204,0.0003206563,0.0003265095,0.0002586955,0.0001989814,0.0008809632,0.001301277,0.0001382393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003742661,"about_ca_system_score_gemma":0.0003677479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003702301,"about_ca_topic_score_gemma":3.560989e-7,"domain_scores_codex":[0.9960994,0.00003780447,0.0007483306,0.001652471,0.000572259,0.000889746],"domain_scores_gemma":[0.9961761,0.00008598875,0.0006336357,0.002400567,0.0003230957,0.0003806337],"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":[0.00003598182,0.0002757016,0.0007483152,0.0005889134,0.0002365248,0.00001229493,0.000003752547,0.0000098495,0.9861957,0.0001527734,0.01173573,0.000004489194],"study_design_scores_gemma":[0.000454333,0.00001823111,0.0003690807,0.000456517,0.0001501678,2.86929e-8,0.000002889065,0.0001539004,0.8980861,0.000005833724,0.09933712,0.0009657984],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.983426,0.003445509,0.008290428,0.000540511,0.0003426808,0.0004752244,0.002305692,0.0008884505,0.0002855019],"genre_scores_gemma":[0.9927512,0.0007281916,0.00341372,0.0002269358,0.001702866,0.0007211345,0.0000163363,0.0002230004,0.0002165549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08810958,"threshold_uncertainty_score":0.9996931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01440558281832885,"score_gpt":0.2214086189432059,"score_spread":0.207003036124877,"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."}}