{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Jorgensen C"],"funding":["European Commission"],"pagination":["9050"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12469845"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["26(18)"],"pubmed_abstract":["We explored the pharmacology of the P-glycoprotein (P-gp) efflux pump and its role in multidrug resistance. We used Protein Data Bank (PDB) database mining and the artificial intelligence (AI) model Boltz-2.1.1, developed for simultaneous structure and affinity prediction, to explore the multimeric nature of recent P-gp inhibitors. We construct a MARTINI coarse-grained (CG) force field description of P-gp embedded in a model of the endothelial blood-brain barrier. We found that recent P-gp inhibitors have been captured in either monomeric, dimeric, or trimeric states. Our CG model demonstrates the ability of P-gp substrates to permeate and transition across the BBB bilayer. We report a multimodal binding model of P-gp inhibition in which later generations of inhibitors are found in dimeric and trimeric states. We report analyses of P-gp substrates that point to an extended binding surface that explains how P-gp can bind over 300 substrates non-selectively. Our coarse-grained model of substrate permeation into membranes expressing P-gp shows benchmarking similarities to prior atomistic models and provide new insights on far longer timescales."],"journal":["International journal of molecular sciences"],"pubmed_title":["Simulation and Machine Learning Assessment of P-Glycoprotein Pharmacology in the Blood-Brain Barrier: Inhibition and Substrate Transport."],"pmcid":["PMC12469845"],"funding_grant_id":["101023783"],"pubmed_authors":["Thulasi S","Lopez Martinez E","Prior H","Draheim RR","Barker M","Gregory C","Jorgensen C","Oliphant E","Franey BW","Ajay A","Oluwasegun J"],"additional_accession":[]},"is_claimable":false,"name":"Simulation and Machine Learning Assessment of P-Glycoprotein Pharmacology in the Blood-Brain Barrier: Inhibition and Substrate Transport.","description":"We explored the pharmacology of the P-glycoprotein (P-gp) efflux pump and its role in multidrug resistance. We used Protein Data Bank (PDB) database mining and the artificial intelligence (AI) model Boltz-2.1.1, developed for simultaneous structure and affinity prediction, to explore the multimeric nature of recent P-gp inhibitors. We construct a MARTINI coarse-grained (CG) force field description of P-gp embedded in a model of the endothelial blood-brain barrier. We found that recent P-gp inhibitors have been captured in either monomeric, dimeric, or trimeric states. Our CG model demonstrates the ability of P-gp substrates to permeate and transition across the BBB bilayer. We report a multimodal binding model of P-gp inhibition in which later generations of inhibitors are found in dimeric and trimeric states. We report analyses of P-gp substrates that point to an extended binding surface that explains how P-gp can bind over 300 substrates non-selectively. Our coarse-grained model of substrate permeation into membranes expressing P-gp shows benchmarking similarities to prior atomistic models and provide new insights on far longer timescales.","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Sep","modification":"2026-05-02T03:17:11.962Z","creation":"2026-05-02T03:11:42.894Z"},"accession":"S-EPMC12469845","cross_references":{"pubmed":["41009615"],"doi":["10.3390/ijms26189050"]}}