{"id":"W4410124772","doi":"10.1021/acsmedchemlett.4c00622","title":"Allosteric Covalent Inhibitors of the STAT3 Transcription Factor from Virtual Screening","year":2025,"lang":"en","type":"article","venue":"ACS Medicinal Chemistry Letters","topic":"Cytokine Signaling Pathways and Interactions","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Institute of Genetics; National Research, Development and Innovation Office; University of Toronto Mississauga; Nemzeti Kutatási Fejlesztési és Innovációs Hivatal; University of Toronto; Budapesti Műszaki és Gazdaságtudományi Egyetem; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Magyar Tudományos Akadémia","keywords":"Allosteric regulation; Virtual screening; Transcription factor; STAT3; Transcription (linguistics); Covalent bond; Chemistry; Computational biology; Computer science; Enzyme; Biochemistry; Biology; Drug discovery; Phosphorylation; Gene","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":[0.00007475549,0.0001572378,0.0002566357,0.00004077816,0.0000728395,0.00000966072,0.000140291,0.00007266663,0.0002967728],"category_scores_gemma":[0.00008961651,0.0001131108,0.0001631214,0.0002050916,0.0001540913,0.00005163077,0.00003592755,0.0003732355,0.000002278278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008620503,"about_ca_system_score_gemma":0.00008010877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002042568,"about_ca_topic_score_gemma":0.000002421384,"domain_scores_codex":[0.9988393,0.00002419101,0.000366254,0.0002279173,0.0003709013,0.0001713974],"domain_scores_gemma":[0.9993451,0.00009476188,0.0001240256,0.0002966101,0.00006710343,0.00007245696],"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":[0.000166214,0.00005593169,0.002892451,0.00009729146,0.0001275238,0.00001005978,0.0004380304,0.00001771815,0.9896311,0.000004810976,0.004291719,0.002267168],"study_design_scores_gemma":[0.001140208,0.00004811533,0.01072032,0.0009105058,0.000212359,0.00001578073,0.0007240718,0.00005756828,0.9801401,0.000008309498,0.005931487,0.00009111993],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9858283,0.0001387252,0.00270886,0.01007087,0.0005023666,0.0001537428,0.00005724724,0.00003277646,0.0005070879],"genre_scores_gemma":[0.9961647,0.00001333921,0.0001243111,0.003028172,0.0003118734,0.0000089201,0.00006225013,0.00001243197,0.0002740024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01033637,"threshold_uncertainty_score":0.4612524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01592198671397647,"score_gpt":0.2568645545986542,"score_spread":0.2409425678846777,"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."}}