{"id":"W2769626034","doi":"10.1016/j.ijbiomac.2017.11.107","title":"Interaction of catecholamine precursor l-Dopa with lysozyme: A biophysical insight","year":2017,"lang":"en","type":"article","venue":"International Journal of Biological Macromolecules","topic":"Protein Interaction Studies and Fluorescence Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Institute of Population and Public Health; Department of Biotechnology, Government of West Bengal; King Saud University; University Grants Commission; Department of Science and Technology, Ministry of Science and Technology, India; Department of Biotechnology, Ministry of Science and Technology, India","keywords":"Lysozyme; Chemistry; Hydrogen bond; Kinetics; Molecular dynamics; Dihydroxyphenylalanine; Docking (animal); Crystallography; Biochemistry; Computational chemistry; Dopamine; Molecule; Organic chemistry; Biology","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":[0.0001071031,0.0001695438,0.0001612805,0.00008288844,0.0002121609,0.0002807683,0.0002735704,0.0003955895,0.0005901361],"category_scores_gemma":[0.0001452274,0.0001082476,0.0001946767,0.00008144085,0.0002758082,0.000366717,0.0001617269,0.0004904224,0.0001822667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002839107,"about_ca_system_score_gemma":0.0001231172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007695294,"about_ca_topic_score_gemma":0.0004953935,"domain_scores_codex":[0.9999413,0.0000110842,0.000002559717,0.00001344303,0.00001392359,0.00001763606],"domain_scores_gemma":[0.9999356,0.00002755064,0.00001154377,0.000004690795,0.000009009344,0.00001146005],"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":[0.00007622803,0.00002630391,0.0004046416,0.00003209848,0.00000554616,0.0003275376,0.00004033195,0.0001145667,0.997924,0.0003060051,0.00003249131,0.0007101106],"study_design_scores_gemma":[0.000008036958,0.0001147399,0.004976749,0.000006464834,0.00001301166,0.000586119,0.0001437985,0.005364179,0.9872623,0.0002390115,0.001275584,0.000009977395],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931856,0.001292747,0.003246178,0.0003244997,0.00001475577,0.000007610076,0.0000477449,0.00001596347,0.001864768],"genre_scores_gemma":[0.9973481,0.0005552891,0.0009258596,0.00005393208,0.000006337942,0.000004596449,0.0000455896,0.000003511291,0.001056854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007695294,"threshold_uncertainty_score":0.002059937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01980540299009311,"score_gpt":0.3047248675608722,"score_spread":0.2849194645707792,"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."}}