From Single Ligand-Receptor Bond Strength to Collective Avidity: Mechanics-Guided Superselective Nanoparticle...

Multivalent adhesion between ligand-coated nanoparticles (NPs) and cell membrane receptors is central to targeted nanomedicine, yet how NP mechanics tune the classic affinity-selectivity trade-off remains unclear. Here we combine Monte Carlo simulations with thermodynamic analysis to probe the binding free-energy landscape of rigid, semirigid, and deformable NPs interacting with target receptors. By sweeping membrane tension, receptor density, and ligand-receptor affinities (spanning the full weak-to-strong regime), we uncover a mechanics-governed switch in optimal design. The entropy-enthalpy compensation reveals that deformable NPs dominate at intermediate affinities, exploiting shape adaptability to recruit nearly all available receptors even at low expression levels, albeit at significant entropic cost. The semirigid NPs, in turn, require the strongest affinity to offset configurational penalties and maximize avidity, while rigid NPs never engage more than ∼10% of their ligand capacity. The interactions under weak individual bonds fail to nucleate adhesion under any mechanical or biochemical condition tested. Additionally, increasing membrane tension selectively suppresses multivalency of binding for rigid and semirigid NPs but leaves deformable NPs largely unaffected. The results collapse onto mechanics-affinity phase diagrams that can predict design windows where (super) selective adhesion emerges from the interplay of NP stiffness, membrane deformation, bond strength, and receptor density. These insights provide quantitative guidelines for engineering deformable, affinity-tuned nanocarriers capable of high selectivity under physiologically relevant mechanical and biochemical heterogeneity.