{"id":"W2051777255","doi":"10.1007/s12551-015-0167-5","title":"Oriented samples: a tool for determining the membrane topology and the mechanism of action of cationic antimicrobial peptides by solid-state NMR","year":2015,"lang":"en","type":"article","venue":"Biophysical Reviews","topic":"Antimicrobial Peptides and Activities","field":"Immunology and Microbiology","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Regroupement Québécois sur les Matériaux de Pointe","funders":"Natural Sciences and Engineering Research Council of Canada; Centre québécois sur les matériaux fonctionnels","keywords":"Antimicrobial peptides; Peptide; Membrane; Membrane topology; Mode of action; Antimicrobial; Chemistry; Cationic polymerization; Topology (electrical circuits); Combinatorial chemistry; Nuclear magnetic resonance spectroscopy; Solid-state nuclear magnetic resonance; Mechanism of action; Biophysics; Membrane protein; Biochemistry; Stereochemistry; Biology; Organic chemistry; Physics; Mathematics; Nuclear magnetic resonance","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":[0.0004187486,0.0005029495,0.0002217663,0.0004418041,0.000486959,0.0008265841,0.0005037339,0.0006559973,0.001581673],"category_scores_gemma":[0.0006332808,0.0004046973,0.0001707194,0.0003746292,0.0005188643,0.0008467219,0.0003057445,0.001125704,0.0004150538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002170935,"about_ca_system_score_gemma":0.0002662336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004194158,"about_ca_topic_score_gemma":0.001090556,"domain_scores_codex":[0.9997991,0.00005118267,0.00001245012,0.00004330684,0.00006630678,0.00002774875],"domain_scores_gemma":[0.9995934,0.0001626992,0.00008064624,0.00005532479,0.00007441534,0.00003354981],"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":[0.00006065167,0.00001763375,0.0001468887,0.00005973128,0.000008106355,0.00002912178,0.00004551967,0.0001583776,0.9952847,0.000965082,0.0002029428,0.003021312],"study_design_scores_gemma":[0.00003221618,0.0001323717,0.00119645,0.00002092388,0.00002682281,0.0001196513,0.0001069295,0.005556711,0.9859366,0.001143043,0.005704123,0.00002414218],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7717468,0.002658208,0.2102421,0.0006902903,0.0003062686,0.0001817581,0.002140858,0.0009135429,0.01112019],"genre_scores_gemma":[0.8290393,0.004519305,0.1584777,0.0006347328,0.0001218844,0.0003721829,0.00197443,0.0005741127,0.00428638],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001581673,"threshold_uncertainty_score":0.005291224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04082076466959088,"score_gpt":0.2958067273491485,"score_spread":0.2549859626795576,"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."}}