{"id":"W4412599464","doi":"10.1016/j.rechem.2025.102556","title":"Pursing Quinoline-8-Sulfonamide derivatives for the identification of potent NPPs inhibitors: In silico molecular docking, molecular dynamics simulations and density field theory (DFT) studies","year":2025,"lang":"en","type":"article","venue":"Results in Chemistry","topic":"Enzyme function and inhibition","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds de recherche du Québec; Deanship of Scientific Research, King Saud University; Natural Sciences and Engineering Research Council of Canada; Higher Education Commision, Pakistan; Deanship of Scientific Research, Imam Mohammed Ibn Saud Islamic University","keywords":"In silico; Quinoline; Sulfonamide; Molecular dynamics; Docking (animal); Identification (biology); Chemistry; Computational chemistry; Computational biology; Combinatorial chemistry; Stereochemistry; Biology; Medicine; Organic chemistry; Biochemistry","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":[0.0003605108,0.0009957165,0.001333187,0.0004349256,0.0003217382,0.0006562465,0.0006956371,0.0006257709,0.00190712],"category_scores_gemma":[0.0005696711,0.0003274594,0.0009210057,0.000580758,0.000222941,0.0004544021,0.0003950636,0.0007308972,0.0003781936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004883726,"about_ca_system_score_gemma":0.0006743261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004200405,"about_ca_topic_score_gemma":0.006837723,"domain_scores_codex":[0.9998651,0.0000408583,0.00000720762,0.00002139269,0.00003819473,0.00002734662],"domain_scores_gemma":[0.9998564,0.00007219476,0.00002218829,0.00000709752,0.00002606289,0.00001604646],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006748351,0.0004993373,0.001980761,0.001130002,0.0002973907,0.0007734871,0.0001031824,0.9205076,0.04073338,0.007101249,0.002211373,0.02398743],"study_design_scores_gemma":[0.0001185342,0.0005088673,0.0003455286,0.00003423967,0.00009627704,0.00006083582,0.00006172935,0.9882515,0.00728816,0.0007917513,0.002415127,0.00002753025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9196889,0.01626226,0.04334301,0.0009533878,0.0001873047,0.0002550336,0.00148678,0.000679155,0.01714416],"genre_scores_gemma":[0.9630306,0.006385931,0.02681335,0.0001839869,0.0000256841,0.0002729722,0.001032741,0.00006221861,0.00219251],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004200405,"threshold_uncertainty_score":0.008351922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009243819133136651,"score_gpt":0.2983994078789908,"score_spread":0.2891555887458541,"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."}}