Experimental and Computational Characterization of Human Serum Albumin Recognition by Ga(III)-NOTA Dendrimer Nanomicelles with Distinct PET Biodistribution Profiles

We investigate the interaction of human serum albumin (HSA) with two Ga(III)-NOTA-functionalized amphiphilic dendrimers 1 and 2 that self-assemble into corresponding nanomicelles 1@ and 2@, which were previously evaluated as positron emission tomography imaging nanoplatforms with distinct biodistribution profiles. These two nanosystems share the same Ga(III)-NOTA surface chemistry but differ in hydrophobic architecture and, consequently, in micellar stability. A combined physicochemical and computational workflow was used to quantify albumin binding, protein structural response, colloidal changes, and interfacial organization. Fluorescence quenching indicated HSA engagement by both nanomicelles, with a stronger perturbation of the Trp214 emission response for 2@. Isothermal titration calorimetry confirmed this ranking, showing that HSA has higher apparent affinity for 2@ than for 1@ (Kd = 8.2 ± 3.8 μM and 39.4 ± 26.7 μM, respectively), with exothermic and thermodynamically favorable association in both cases. Analysis of the integrated heat profiles supported apparent compositions of approximately three HSA molecules per 1@ micelle and four HSA molecules per 2@ micelle. Circular dichroism and three-dimensional fluorescence showed that HSA largely retains its α-helical structure and Trp214 microenvironment upon binding, whereas dynamic light scattering and zeta-potential measurements confirmed formation of protein-nanomicelle complexes. Enhanced-sampling simulations reproduced the preferred HSA loading states and suggested that 2@ promotes a broader Ga(III)-NOTA-rich interfacial network. These findings indicate that the internal hydrophobic architecture can modulate albumin recognition even when the nominal Ga(III)-NOTA surface chemistry is conserved, providing a plausible molecular explanation for the distinct biodistribution behavior of these nanoprobes in biomedical imaging.