Probing Molecular Dynamics and Interactions in Human Blood Serum via Ultrafast High-Resolution Relaxometry

Nuclear Magnetic Relaxation Dispersion (NMRD) profiles carry information on the molecular dynamics across a broad range of timescales, but exploiting this in a complex biological matrix has long been limited by sensitivity and resolution. Ultrafast High-Resolution Relaxometry (UHRR) overcomes these limitations by combining high-field NMR detection with a Fast-Shuttle-System (FSS) and a prototype Field-Cycling-Coil (FCC), enabling site-specific ¹H relaxation rate measurements from 0.1 mT to 11 T on a 600 MHz spectrometer. Here we applied UHRR to intact Human Blood Serum (HBS), without any pre-treatment or purification, as a proof of concept for the characterization of molecular dynamics and metabolite-macromolecule interactions in native biofluids. NMRD profiles were acquired for both macromolecular components and small metabolites. All UHRR measurements were analysed using TrAGICo, a Python-based software package designed for extracting and evaluating data from 1D and pseudo-2D Bruker NMR spectra. Our results demonstrate that lipoproteins, glycoproteins, albumin lysyl groups and phospholipids, all exhibit characteristic dispersions described by distribution of correlation times spanning nanoseconds to microseconds. For most small metabolites (e.g. lactate, creatinine, 3-hydroxybutyrate, valine, alanine), the NMRD profiles show modest or absent field dependence, preventing a clear detection of binding interactions under the experimental conditions. A notable exception is phenylalanine, whose aromatic protons display a well-defined dispersion, suggestive of a transient interaction with a serum macromolecule. The sensitivity of UHRR toward protein–ligand interactions was further validated by spiking HBS with Y-DOTA(BOM)₃, an albumin-targeted complex. Its NMRD profile in serum displays a clear dispersion with τc ≈ 30–32 ns, consistent with albumin tumbling and in excellent agreement with previous results. Taken together, these results establish UHRR as a powerful tool for the in situ dynamic fingerprinting of biofluids, with direct implications for biomarker discovery and the characterization of metabolite–protein interactions in their native biological context.