Molecular dynamics and clustering analysis of self-assembled biodegradable polymeric nanoparticles for insulin...

Self-assembled biodegradable polymeric nanoparticles are promising carriers for protein therapeutics such as insulin, whose clinical administration remains challenging. Accordingly, we used molecular dynamics (MD) simulations to investigate how poly (lactic acid) (PLA), poly (ethylene glycol)-PLA (PEG-PLA), poly (lactic-co-glycolic acid) (PLGA), PEG-PLGA, and methoxy-PEG (mPEG)-PLGA oligomers self-assemble on the insulin surface. We further applied essential dynamics and K-means clustering analyses to evaluate protein motions and characterize oligomer assembly states, respectively. We observed no meaningful loss of insulin structural stability in the oligomer-containing systems, and most formed compact, approximately spherical aggregates. In contrast, mPEG-PLGA showed limited protein coverage because its oligomer chains predominantly assembled rather than contacting insulin. PEG incorporation into PLA and PLGA increased oligomer-insulin interactions, primarily governed by van der Waals (vdW) and hydrophobic contributions. Essential dynamics analysis showed no marked changes in insulin's dominant motion patterns, while PEG-PLA, PLGA, and PEG-PLGA sampled comparatively compact conformational states. Clustering analysis categorized the sampled configurations into three structurally distinct assembly states, with compact configurations occurring more frequently in these three systems. Integrating triplicate trajectories, residue-level contact and relative energetic analyses, essential dynamics, and replicate-aware clustering provides a comparative atomistic description of how oligomer chemistry and architecture influence insulin stability and motions, oligomer-insulin adsorption, and early self-assembly behavior. These findings may support computational screening and subsequent experimental evaluation of polymeric carriers for insulin and other protein therapeutics.