A dual-layer computational framework for prioritising therapeutic candidates targeting extracellular vesicle-mediated immune escape in pancreatic ductal adenocarcinoma
Zhu, Y.; Yang, X.; Isah, M. B.; Zhang, X.
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Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterised by a highly immunosuppressive tumour microenvironment and limited therapeutic responses. Tumour-derived extracellular vesicles (EVs) contribute to PDAC progression by transferring immunomodulatory molecules and tumour-associated signals, suggesting EV-associated processes as potential intervention opportunities. However, the heterogeneity of EV biology and the complexity of tumour-immune interactions make single-target intervention strategies challenging. Here, we developed a computation-driven dual-layer candidate-prioritisation framework to identify potential modulators associated with PDAC EV-mediated immune escape through complementary production-side and action-side strategies. For the production-side layer, we focused on upstream processes related to EV biogenesis, cargo regulation, inflammatory signalling, and tumour-associated pathways. An 88-gene PDAC EV-associated target framework was integrated with cell-type-resolved prognosis annotations from ctPANDA and predicted targets of 18 natural products derived from Scutellaria baicalensis, Epimedium spp., and Cornus officinalis to prioritise natural-product candidates with disease relevance and potential chemical tractability. In parallel, key targets with experimentally resolved ligand-binding structures were subjected to pocket-guided de novo small-molecule design based on co-crystal ligand-defined binding sites, followed by structural, docking-based, and physicochemical screening of generated compounds. For the action-side layer, VHH and scFv binders were computationally designed and screened against extracellular regions of MET and CD81 to prioritise candidates potentially suitable for EV recognition and capture. This study provides a computational strategy for narrowing candidate spaces across both EV-associated production pathways and released vesicle recognition. The resulting small molecules, antibody-like binder models, and screening workflows provide a resource for future experimental validation of strategies targeting PDAC EV-associated immune regulation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/740294v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@11829b0org.highwire.dtl.DTLVardef@158efb5org.highwire.dtl.DTLVardef@1e17cc5org.highwire.dtl.DTLVardef@c69696_HPS_FORMAT_FIGEXP M_FIG C_FIG
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