{"id":"W4377823313","doi":"10.1101/2023.05.22.541727","title":"Development of FERM domain protein-protein interaction inhibitors for MSN and CD44 as a potential therapeutic strategy for Alzheimer’s disease","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Signaling Pathways in Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; Novartis Pharma; Genentech; Ontario Ministry of Economic Development and Innovation; Emory University; European Federation of Pharmaceutical Industries and Associations; Merck KGaA; Ministero dello Sviluppo Economico; Genome Canada; Fundação de Amparo à Pesquisa do Estado de São Paulo; Diamond Light Source; Pfizer","keywords":"FERM domain; Radixin; Allosteric regulation; Moesin; Ezrin; Binding site; Cell biology; Plasma protein binding; Scaffold protein; Chemistry; Biology; Receptor; Biochemistry; Computational biology; Membrane protein; Integral membrane protein; Signal transduction; Cytoskeleton; Cell","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":[0.0002306511,0.000514661,0.0004150435,0.0003218689,0.0001568535,0.0002517915,0.0003896746,0.000359121,0.001331611],"category_scores_gemma":[0.00009527762,0.0001716527,0.0004171763,0.0001761311,0.0001617909,0.0002098215,0.0002016551,0.0006600734,0.0003192072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003195492,"about_ca_system_score_gemma":0.0002478834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004231859,"about_ca_topic_score_gemma":0.001072552,"domain_scores_codex":[0.9999381,0.00001167775,0.000003816757,0.000008736861,0.00001719211,0.00002048469],"domain_scores_gemma":[0.9999619,0.000005620926,0.00001010645,0.000002532086,0.000006930526,0.0000129555],"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":[0.0005383118,0.0007193473,0.0003701672,0.0001927937,0.0000621978,0.0002903963,0.00003233739,0.00181971,0.9696071,0.0008315163,0.0005140733,0.02502206],"study_design_scores_gemma":[0.001514176,0.01298838,0.004962373,0.00006294704,0.0002415111,0.001182662,0.00005239367,0.009417196,0.9417228,0.0004595737,0.02734966,0.00004640016],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9683784,0.01168897,0.01186322,0.0005751358,0.000129086,0.0006041102,0.0006140274,0.0002492513,0.005897781],"genre_scores_gemma":[0.9781773,0.006744973,0.009903519,0.0002700133,0.00003338023,0.0002165541,0.0007237041,0.00001469986,0.003915919],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001331611,"threshold_uncertainty_score":0.004454613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03692874488945985,"score_gpt":0.2782765314652557,"score_spread":0.2413477865757959,"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."}}