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Updated: Sep 20, 2026

Ligand Nano-cluster Arrays in a Supported Lipid Bilayer
Published on: April 23, 2017
Ligand conformational entropy as a regime-switching descriptor of the electrostatic-uptake relationship in
Quynh Hoa Truong1, Xuan Khanh Truong1
1Clevix Lab, Clevix LLC, Hanoi, Vietnam.
Abstract:
Surface charge is widely regarded as a primary determinant of nanoparticle-immune cell interactions, yet nanocarriers with similar physicochemical profiles often exhibit markedly different biological outcomes. Here, we show that ligand conformational diversity, quantified through an information-theoretic descriptor (Hligand), is strongly associated with a regime transition in the relationship between surface charge and cellular uptake. Analysis of 105 gold nanoparticles from a benchmark protein corona dataset identifies a critical threshold at Hligand*≈1.76 bits (F = 47.3, p < 10-14): below this value, zeta potential is positively associated with uptake (r = +0.70), whereas above it the relationship reverses (r=-0.58), consistent with steric shielding by flexible surface ligands. Entropy-derived descriptors improve predictive performance across multiple model classes (ΔR2 up to +0.118), with gains concentrated in high-entropy regimes where physicochemical descriptors alone are insufficient. An analytical competition model captures this transition in a compact form (R2 = 0.550), with 2H*≈3.4 effective microstates marking a numerical balance point between electrostatic and steric contributions. Cross-dataset validation on 652 multi-material nanoparticles supports transferability of the descriptor framework (ΔR2=+0.181). We emphasize that Hligand is a constructed information-theoretic descriptor rather than a thermodynamic entropy, and that all findings are derived from retrospective analysis of in vitro datasets and not from controlled experimental manipulation. The identified threshold therefore represents a reproducible statistical pattern and a testable hypothesis for how ligand flexibility modulates interaction regimes. This framework provides a computable basis for organizing nanocarrier design hypotheses and motivates prospective validation in more complex carrier systems.
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