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Updated: Jan 9, 2026

Atomic Scale Structural Studies of Macromolecular Assemblies by Solid-state Nuclear Magnetic Resonance Spectroscopy
Published on: September 17, 2017
The Core-Shell Conformational Space of Compartmentalized Single-Chain Nanoparticles by Paramagnetic and
Federico Faglia1,2, Justus F Thümmler3, Christopher Pötzl1,2
1Faculty of Chemistry, Institute of Biological Chemistry, University of Vienna, Währinger Str. 38, Vienna, 1090, Austria.
Abstract:
Single-chain nanoparticles (SCNPs) are formed by the collapse of individual polymer chains, generating entities comparable to proteins in size, internal structure, and function. Especially, the formation of hierarchies induced by complex folds of linear polymer chains can result in internalized compartments, reminiscent of pockets in enzymes. However, direct experimental access to their architecture or mode of contact remains a challenge. Here, the conformational organization of a prototypical amphiphilic SCNP is dissected to reveal conformational details of its internally heterogeneous morphology driven by site-specific intramolecular compaction. Using a synergistic combination of unconventional paramagnetic NMR, hyperpolarized water-based dissolution dynamic nuclear polarization (d-DNP), and NMR-guided molecular dynamics simulations, intramolecular structures and solvent accessibility are mapped at atomistic resolution. These findings uncover distinct nanoscopic compartments formed via back-folding of PEG side chains toward the SCNP backbone. Furthermore, these compartments shield internal segments, mimicking hydrophobic pockets found in folded proteins. Thus, this work introduces a transferable methodology for probing functional compartmentalization in synthetic macromolecules. It provides a tool for rationally designing next-generation nanomaterials and enzyme mimetics with programmable internal order via residue-resolved structural information. At the same time, this method's prowess is evidenced through a high-resolution description of the local conformations found within hierarchically structured SCNPs.
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