{"id":"W2903748661","doi":"10.1002/prot.25644","title":"Rapid and accurate structure‐based therapeutic peptide design using GPU accelerated thermodynamic integration","year":2018,"lang":"en","type":"article","venue":"Proteins Structure Function and Bioinformatics","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research; National Institutes of Health","keywords":"Peptide; Chemistry; Combinatorial chemistry; Amino acid; Thermodynamic integration; Molecular dynamics; Computer science; Computational biology; Computational chemistry; Biophysics; Biochemistry; Biology","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":[0.0001669107,0.0002854758,0.0001797442,0.00009660408,0.0003203378,0.0001633431,0.0001036482,0.0002774658,0.0001217416],"category_scores_gemma":[0.00004581894,0.0002107949,0.0000390285,0.000139439,0.0001488443,0.00003858849,0.00004842682,0.0001238158,0.000001957901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001742722,"about_ca_system_score_gemma":0.00008003387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009826739,"about_ca_topic_score_gemma":0.00002422632,"domain_scores_codex":[0.9989427,0.0001038196,0.0003076546,0.0002516223,0.0001536469,0.0002405735],"domain_scores_gemma":[0.9992707,0.00001336761,0.0002144582,0.0002558804,0.0001586416,0.00008690477],"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":[0.000315902,0.000006908596,0.00003983003,0.000041768,0.00004790348,1.743701e-7,0.00009844422,0.00004055323,0.9192911,0.0001202501,0.00001651112,0.07998061],"study_design_scores_gemma":[0.0008801025,0.001144542,0.001057638,0.00004758273,0.00007849735,0.00004333983,0.0001870837,0.1418513,0.8508703,0.002330496,0.001091489,0.0004176356],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4177675,0.0002613348,0.5808473,0.00004961852,0.0001907609,0.0007281218,0.00003597538,0.00003264624,0.00008674836],"genre_scores_gemma":[0.9463981,0.00005037577,0.05265442,0.0005397826,0.0001875713,0.00001320855,0.000101065,0.00002509772,0.00003032834],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5286306,"threshold_uncertainty_score":0.8595968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03198787567597096,"score_gpt":0.2515171783990417,"score_spread":0.2195293027230708,"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."}}