{"id":"W4417120895","doi":"10.1021/acschembio.5c00702","title":"Overcoming Ligand Discovery Challenges: Developing Peptide-Based Tracers for SPSB2","year":2025,"lang":"en","type":"article","venue":"ACS Chemical Biology","topic":"Protein Degradation and Inhibitors","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Genentech; Innovative Medicines Initiative; Deutschen Konsortium für Translationale Krebsforschung; Ontario Genomics Institute; European Federation of Pharmaceutical Industries and Associations; Structural Genomics Consortium; Janssen Pharmaceuticals; Merck KGaA; Ontario Genomics; Genome Canada; Bristol-Myers Squibb Foundation; Pfizer; Deutsches Krebsforschungszentrum; Bristol-Myers Squibb; Bayer; Diamond Light Source; Takeda Canada; McGill University; Boehringer Ingelheim","keywords":"Degron; Ubiquitin ligase; Proteolysis; Drug discovery; Ligand (biochemistry); Peptide; Plasma protein binding; DNA ligase; Confocal microscopy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006559929,0.0004114798,0.0003244928,0.0002286272,0.0001955266,0.000755779,0.0005190409,0.0007874693,0.0009272135],"category_scores_gemma":[0.0004623604,0.0002721383,0.0002297712,0.0002101891,0.0003549346,0.00073312,0.0005008555,0.0009169312,0.0005913483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006923252,"about_ca_system_score_gemma":0.0003763081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004836192,"about_ca_topic_score_gemma":0.0008202826,"domain_scores_codex":[0.9997782,0.00005231949,0.00001319126,0.00004938152,0.00006985275,0.00003706909],"domain_scores_gemma":[0.9997706,0.00004870336,0.00005088011,0.00002001597,0.00004439171,0.00006544547],"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":[0.00005188432,0.00001145463,0.00007252532,0.00005658823,0.000003703469,0.00003604161,0.00001774413,0.0004087474,0.9965047,0.0003903653,0.00006383567,0.002382539],"study_design_scores_gemma":[0.00001318302,0.000113137,0.0001808748,0.000006363844,0.000003983304,0.0001439294,0.00002042082,0.004021623,0.9913594,0.000103467,0.00402651,0.000007061177],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7795802,0.003872084,0.2109971,0.000835706,0.00008790334,0.0002304536,0.0003821107,0.0005769057,0.003437609],"genre_scores_gemma":[0.7875657,0.003247441,0.2014211,0.0004200604,0.00003593239,0.0002732514,0.0007270858,0.0001867802,0.006122574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009272135,"threshold_uncertainty_score":0.005023181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01966360601027635,"score_gpt":0.2814646283140008,"score_spread":0.2618010223037245,"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."}}