{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000259969,0.0005752301,0.0005774535,0.0003433377,0.0001408012,0.0004070765,0.0005629486,0.0002656188,0.001325891],"category_scores_gemma":[0.0002887041,0.000278219,0.000218672,0.0002595153,0.0002597334,0.0003296137,0.0002789095,0.0006417897,0.0004076545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000443472,"about_ca_system_score_gemma":0.0003360682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002736163,"about_ca_topic_score_gemma":0.0009030427,"domain_scores_codex":[0.9998682,0.00002207656,0.000009231982,0.0000272278,0.00003918842,0.00003407204],"domain_scores_gemma":[0.9999366,0.00001482926,0.00001706193,0.000003120428,0.000007588193,0.00002073443],"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":[0.0005912759,0.0002758677,0.0003254874,0.0003547714,0.00003914909,0.000633987,0.00007560901,0.01063162,0.9616574,0.002680779,0.0003965043,0.0223374],"study_design_scores_gemma":[0.001621332,0.008599683,0.002351788,0.0000754306,0.0001471817,0.001300116,0.0000854867,0.02395589,0.9360021,0.001475004,0.02431823,0.00006774496],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9429536,0.01293605,0.03209609,0.0003191687,0.0001355909,0.001039723,0.0007260782,0.0004321969,0.009361482],"genre_scores_gemma":[0.9587514,0.008531894,0.02866588,0.0002715559,0.00004743063,0.0003015819,0.0006724186,0.00004719803,0.002710547],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001325891,"threshold_uncertainty_score":0.004435599,"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."}}