{"id":"W4311673765","doi":"10.15537/smj.2022.43.12.20220599","title":"Identification of human immunodeficiency virus -1 E protein-targeting lead compounds by pharmacophore based screening","year":2022,"lang":"en","type":"article","venue":"Saudi Medical Journal","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Addiction and Mental Health","funders":"Taif University","keywords":"Pharmacophore; Virtual screening; Docking (animal); Human immunodeficiency virus (HIV); In silico; Computational biology; Medicine; Drug; Combinatorial chemistry; Virology; Stereochemistry; Pharmacology; Biochemistry; Biology; Chemistry; Gene; Veterinary medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002515523,0.0006906721,0.0009945717,0.0007901291,0.0002256118,0.0005451348,0.0007088316,0.0004786715,0.003269411],"category_scores_gemma":[0.0006125164,0.0002054629,0.0006206917,0.0005769776,0.0001532054,0.0003185749,0.0003143867,0.0003068109,0.0003812925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005278204,"about_ca_system_score_gemma":0.0008659848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001245973,"about_ca_topic_score_gemma":0.002761746,"domain_scores_codex":[0.9998667,0.00003117564,0.000006259066,0.00002416349,0.00005200717,0.00001960243],"domain_scores_gemma":[0.9998918,0.0000457661,0.00002579839,0.000005660585,0.00002064432,0.00001038747],"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":[0.001723806,0.002682364,0.0159512,0.002018999,0.0004495879,0.001697052,0.00009769065,0.6002132,0.1513269,0.006739855,0.005108332,0.211991],"study_design_scores_gemma":[0.0009259772,0.004571253,0.006292154,0.0001351592,0.0005635897,0.001084325,0.0001231887,0.9091153,0.06542195,0.002673622,0.009032219,0.00006127469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9169491,0.007699109,0.05320154,0.0008181442,0.00004719391,0.001366797,0.002896446,0.001822572,0.01519908],"genre_scores_gemma":[0.9323113,0.003403137,0.05796942,0.0002276988,0.00001479886,0.0004260039,0.002863531,0.00004992939,0.002734246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003269411,"threshold_uncertainty_score":0.01093727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02173889094049322,"score_gpt":0.3285118104030403,"score_spread":0.3067729194625471,"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."}}