Lipid Composition Determines Hybrid Nanoparticle Selectivity: Beyond Membrane Mimicry in Cancer Targeting.

Abstract

Lipid-functionalized hybrid nanoparticles (hNPs) are promising for selective cancer delivery, due to their tunable membrane interactions. Yet, whether mimicking target membrane composition enhances recognition, and which determinants govern selectivity remains unresolved. Using coarse-grained molecular dynamics, umbrella sampling simulations, and lipid-specific decomposition analyses on 40 membrane-hNP systems, we examine how individual lipid species govern hNP interactions with mammalian-like and tumor-like bilayers. Our results showed cholesterol acts as the dominant stabilizer, generating free-energy minima and driving remodeling in both bilayers. Conversely, zwitterionic lipids showed weakened interactions, limited insertion, suppressed exchange, and entropic penalties. Tumor-like membranes amplify cholesterol's role in mediating hNP-membrane recognition, facilitating deeper insertion and lipid reorganization. Strikingly, composition-matched hNPs did not preferentially bind their corresponding membrane, whereas cholesterol-enriched formulations displayed increased affinity and selectivity. Thus, lipid-composition mimicry fails as a design principle for selective recognition. These findings provide a mechanistic basis for rational lipid selection, emphasizing complementarity over membrane mimicry.