We have applied nuclear magnetic resonance spectroscopy based plasma phenotyping to reveal diagnostic molecular signatures of SARS-CoV-2 infection via combined diffusional and relaxation editing (DIRE). We compared plasma from healthy age-matched controls (n = 26) with SARS-CoV-2 negative non-hospitalized respiratory patients and hospitalized respiratory patients (n = 23 and 11 respectively) with SARS-CoV-2 rRT-PCR positive respiratory patients (n = 17, with longitudinal sampling time-points). DIRE data were modelled using principal component analysis and orthogonal projections to latent structures discriminant analysis (O-PLS-DA), with statistical cross-validation indices indicating excellent model generalization for the classification of SARS-CoV-2 positivity for all comparator groups (area under the receiver operator characteristic curve = 1). DIRE spectra show biomarker signal combinations conferred by differential concentrations of metabolites with selected molecular mobility properties. These comprise the following: (a) composite N-acetyl signals from α-1-acid glycoprotein and other glycoproteins (designated GlycA and GlycB) that were elevated in SARS-CoV-2 positive patients [p = 2.52 × 10 −10 (GlycA) and 1.25 × 10 −9 (GlycB) vs controls], (b) two diagnostic supramolecular phospholipid composite signals that were identified (SPC-A and SPC-B) from the − + N−(CH 3 ) 3 choline headgroups of lysophosphatidylcholines carried on plasma glycoproteins and from phospholipids in high-density lipoprotein subfractions (SPC-A) together with a phospholipid component of low-density lipoprotein (SPC−B). The integrals of the summed SPC signals (SPC total ) were reduced in SARS-CoV-2 positive patients relative to both controls (p = 1.40 × 10 −7 ) and SARS-CoV-2 negative patients (p = 4.52 × 10 −8 ) but were not significantly different between controls and SARS-CoV-2 negative patients. The identity of the SPC signal components was determined using one and two dimensional diffusional, relaxation, and statistical spectroscopic experiments. The SPC total /GlycA ratios were also significantly different for control versus SARS-CoV-2 positive patients (p = 1.23 × 10 −10 ) and for SARS-CoV-2 negatives versus positives (p = 1.60 × 10 −9 ). Thus, plasma SPC total and SPC total /GlycA are proposed as sensitive molecular markers for SARS-CoV-2 positivity that could effectively augment current COVID-19 diagnostics and may have value in functional assessment of the disease recovery process in patients with long-term symptoms.

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Fragment‐based lead discovery has become a fundamental approach to identify ligands that efficiently interact with disease‐relevant targets. Among the numerous screening techniques, fluorine‐detected NMR has gained popularity owing to its high sensitivity, robustness, and ease of use. To effectively explore chemical space, a universal NMR experiment, a rationally designed fragment library, and a sample composition optimized for a maximal number of compounds and minimal measurement time are required. Here, we introduce a comprehensive method that enabled the efficient assembly of a high‐quality and diverse library containing nearly 4000 fragments and screening for target‐specific binders within days. At the core of the approach is a novel broadband relaxation‐edited NMR experiment that covers the entire chemical shift range of drug‐like 19F motifs in a single measurement. Our approach facilitates the identification of diverse binders and the fast ligandability assessment of new targets.

The complex manifestations of COVID-19 are still not fully decoded on the molecular level. We combined quantitative the nuclear magnetic resonance (NMR) spectroscopy serum analysis of metabolites, lipoproteins and inflammation markers with clinical parameters and a targeted cytokine panel to characterize COVID-19 in a large (534 patient samples, 305 controls) outpatient cohort of recently tested PCR-positive patients. The COVID-19 cohort consisted of patients who were predominantly in the initial phase of the disease and mostly exhibited a milder disease course. Concerning the metabolic profiles of SARS-CoV-2-infected patients, we identified markers of oxidative stress and a severe dysregulation of energy metabolism. NMR markers, such as phenylalanine, inflammatory glycoproteins (Glyc) and their ratio with the previously reported supramolecular phospholipid composite (Glyc/SPC), showed a predictive power comparable to laboratory parameters such as C-reactive protein (CRP) or ferritin. We demonstrated interfaces between the metabolism and the immune system, e.g., we could trace an interleukin (IL-6)-induced transformation of a high-density lipoprotein (HDL) to a pro-inflammatory actor. Finally, we showed that metadata such as age, sex and constitution (e.g., body mass index, BMI) need to be considered when exploring new biomarkers and that adding NMR parameters to existing diagnoses expands the diagnostic toolbox for patient stratification and personalized medicine.

Fragment‐based lead discovery has become a fundamental approach to identify ligands that efficiently interact with disease‐relevant targets. Among the numerous screening techniques, fluorine‐detected NMR has gained popularity owing to its high sensitivity, robustness, and ease of use. To effectively explore chemical space, a universal NMR experiment, a rationally designed fragment library, and a sample composition optimized for a maximal number of compounds and minimal measurement time are required. Here, we introduce a comprehensive method that enabled the efficient assembly of a high‐quality and diverse library containing nearly 4000 fragments and screening for target‐specific binders within days. At the core of the approach is a novel broadband relaxation‐edited NMR experiment that covers the entire chemical shift range of drug‐like 19F motifs in a single measurement. Our approach facilitates the identification of diverse binders and the fast ligandability assessment of new targets.