{"id":"W3184229885","doi":"10.1016/j.drudis.2021.07.018","title":"Drugging the ‘undruggable’. Therapeutic targeting of protein–DNA interactions with the use of computer-aided drug discovery methods","year":2021,"lang":"en","type":"review","venue":"Drug Discovery Today","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Terry Fox Foundation; Prostate Cancer Canada","keywords":"Drug discovery; Computational biology; Drug; Pharmaceutical sciences; Bioinformatics; Pharmacology; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001657177,0.0007801589,0.002798724,0.000269073,0.0003948194,0.000354857,0.0008026789,0.0001276977,0.0001233],"category_scores_gemma":[0.0001878187,0.000348008,0.001431985,0.001058031,0.0007737766,0.0007604279,0.0006953719,0.001618884,0.000009735399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001563197,"about_ca_system_score_gemma":0.0011699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007767932,"about_ca_topic_score_gemma":0.00009386805,"domain_scores_codex":[0.9936938,0.002465436,0.001352711,0.0007644472,0.001047557,0.0006760441],"domain_scores_gemma":[0.9920641,0.005043055,0.001143675,0.001288015,0.0003292811,0.0001318353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005208355,0.00104869,0.0001434,0.03663225,0.006335057,0.0001525686,0.003387306,0.0002707292,0.0007208075,0.004728609,0.01392864,0.9321311],"study_design_scores_gemma":[0.0003170187,0.0001033474,0.00003058381,0.02430606,0.001550135,0.0001330754,0.0008138227,0.0002777302,0.000884893,0.00003954664,0.9711214,0.0004224426],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002371816,0.9863969,0.004365864,0.002625933,0.0004435383,0.002934491,0.0003276565,0.00003892225,0.0004948463],"genre_scores_gemma":[0.001419151,0.9481459,0.006980293,0.0004301155,0.0008048887,0.0004298982,0.0005908651,0.0001914858,0.04100742],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9571927,"threshold_uncertainty_score":0.9998972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0931701491453944,"score_gpt":0.3939359949613371,"score_spread":0.3007658458159427,"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."}}