Structural and systems-level analysis of polyphenolic scaffold compatibility at immune checkpoint interfaces: a PD-L1 dimer–focused in silico study

Context Protein–protein interaction interfaces of immune checkpoints present persistent challenges for molecular modeling due to shallow topology, limited pocket definition, and conformational flexibility. Although polyphenolic compounds have been widely explored in immune-related computational studies, their structural compatibility with immune checkpoint interface architectures remains poorly defined at the scaffold level. In this study, we investigated interface-focused structural compatibility of representative polyphenolic scaffolds at immune checkpoint proteins, with primary emphasis on the programmed death-ligand 1 (PD-L1) dimer interface and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) included as a structural comparator. The analysis reveals reproducible pose convergence and non-random residue footprint overlap at the PD-L1 dimer interface, supported by stable intrinsic interface architecture during apo-state molecular dynamics simulations. Network-based analysis further situates predicted ligand-associated targets within immune-related interaction neighborhoods, providing systems-level context consistent with a structurally permissive signaling environment. These findings characterize interface-level structural compatibility rather than functional immune checkpoint inhibition and generate testable hypotheses for subsequent experimental studies. Methods Interface-preserving molecular docking was performed using AutoDock Vina with multi-seed sampling to assess spatial compatibility, pose convergence, and residue-level footprint overlap at immune checkpoint interfaces. Docking validation included redocking benchmarks and decoy-based evaluation. Molecular dynamics simulations of the apo PD-L1 dimer were conducted using GROMACS with a classical all-atom force field to characterize intrinsic interface stability, residue flexibility, interfacial contacts, and hydrogen-bond persistence. Predicted molecular targets of representative polyphenols were identified using similarity-based target prediction tools and analyzed through protein–protein interaction network construction and topological analysis using Cytoscape. All computational workflows were executed using standard molecular modeling and network analysis software, with full methodological details provided in the main text and Online Resource 1.