{"id":"W2346448167","doi":"10.1021/acs.jmedchem.6b00267","title":"Rational Design of Calpain Inhibitors Based on Calpastatin Peptidomimetics","year":2016,"lang":"en","type":"article","venue":"Journal of Medicinal Chemistry","topic":"Calpain Protease Function and Regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Aegera Therapeutics (Canada); University of Toronto; Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Ontario Genomics Institute; Québec Consortium for Drug Discovery","keywords":"Calpastatin; Calpain; Peptidomimetic; Chemistry; Proteases; Cysteine; Allosteric regulation; Enzyme inhibitor; Biochemistry; Active site; Enzyme; Stereochemistry; Cysteine protease; Peptide; Small molecule; Structure–activity relationship; In vitro","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":[0.0007230646,0.0001072994,0.0001602429,0.00004423098,0.00002720232,0.000003602865,0.00009658088,0.0001267772,0.0001723605],"category_scores_gemma":[0.0007283125,0.00006735172,0.0001132868,0.00005989477,0.0001217842,0.000003518694,0.00001232242,0.00009968473,0.000001427817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003658769,"about_ca_system_score_gemma":0.000283798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.301328e-7,"about_ca_topic_score_gemma":1.267611e-7,"domain_scores_codex":[0.9988598,0.00008030212,0.0004290976,0.0001149228,0.000410438,0.0001054432],"domain_scores_gemma":[0.998964,0.0001114558,0.0003950527,0.0001322086,0.0002802511,0.0001170603],"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":[0.0009204105,0.00008857034,0.0003813088,0.00003545386,0.0000287104,0.00000707345,0.000009188927,0.001290378,0.9837376,0.000004219175,0.009637512,0.003859582],"study_design_scores_gemma":[0.002187943,0.0006422476,0.0003961349,0.0002311595,0.00003057905,0.00006405597,0.00004751872,0.0006366412,0.9889771,0.00005779406,0.006632943,0.00009587184],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5009753,0.0003284965,0.4947985,0.002727403,0.0003841278,0.0001750194,0.00001770359,0.000006106535,0.0005873171],"genre_scores_gemma":[0.9959509,0.0000281523,0.002323454,0.0001905004,0.000817363,0.000002511825,0.000009767537,0.00001173752,0.0006656442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4949755,"threshold_uncertainty_score":0.2746524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009192127115796289,"score_gpt":0.2324607732444988,"score_spread":0.2232686461287025,"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."}}