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 (
H
l
i
g
a
n
d
), 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
H
l
i
g
a
n
d
*
≈
1.76
bits (
F
= 47.3,
p
−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 (
Δ
R
2
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 (
R
2
= 0.550), with
2
H
*
≈
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 (
Δ
R
2
=
+
0.181
). We emphasize that
H
l
i
g
a
n
d
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.