Biological NMR

Bijaylaxmi Patra (Centre of BioMedical Research (CBMR), India)

LinkedIn: @Bijaylaxmi Patra; X: @BijaylaxmiNMR; Bluesky: @bijaylaxmi.bsky.social‬

Abstract: Collagen, the most abundant protein in animals, is a major structural constituent of muscle and connective tissues and plays a crucial role in determining their mechanical properties. Its structure and stability are strongly influenced by interactions with the surrounding environment, particularly water; however, the molecular basis of these effects remains insufficiently understood. In this study, we probe dehydration–induced changes in collagen dynamics within the native bone extracellular matrix (ECM) using 13C solid–state Nuclear Magnetic Resonance (NMR) relaxation measurements (T1 and T2) along with rotational correlation time analysis to examine water–collagen interactions at the molecular level. Our residue–specific investigation uncovers distinct motional behavior among the aliphatic carbons of the Gly–Pro–Hyp triplet and alanine residues, which together account for nearly 70% of type I collagen. The extracted 13C correlation times reveal substantial motional heterogeneity, where dehydration primarily suppresses the mobility of hydroxyproline Cβ, while H/D exchange significantly affects hydroxyproline Cα, Cβ, and Cγ, as well as glycine Cα. These results provide new insights into hydration–dependent collagen dynamics in native bone and demonstrate the utility of 13C relaxation measurements for investigating water–mediated stabilization and motion in collagen, with broader implications for understanding pathological processes and designing biomimetic materials.

Srijon Sen (IIT Kharagpur, India)

Abstract: Protein–protein interactions (PPIs) mediated by Src homology 3 (SH3) domains are central to oncogenic signaling and represent challenging therapeutic targets. In breast cancer, the β-PIX SH3 domain interacts with the proline-rich region of Cbl, sequestering it and impairing EGFR downregulation, thereby promoting aberrant signaling. Here, we employ solution-state NMR spectroscopy to structurally and dynamically characterize the β-PIX SH3 domain and to elucidate its interaction with designed peptide inhibitors.

Uniformly ¹⁵N-labeled β-PIX SH3 domain was expressed and purified, and ¹⁵N–¹H HSQC spectra exhibited well-dispersed resonances indicative of a folded protein. Backbone resonance assignments were achieved with high completeness. Secondary structure propensity analysis confirmed a canonical SH3 fold comprising five β-strands and a short 3₁₀ helix. ¹⁵N relaxation measurements (R₁, R₂, and heteronuclear NOE) revealed a structurally stable core with localized flexibility in the RT loop, a key determinant of ligand binding.

Peptide inhibitors were designed using computational approaches and molecular dynamics simulations. NMR titration experiments showed significant chemical shift perturbations upon peptide binding, enabling mapping of the interaction interface on the SH3 domain. Cyclic peptides exhibited enhanced binding compared to linear counterparts, as evidenced by larger perturbations and improved binding affinities. These observations were further supported by isothermal titration calorimetry and fluorescence anisotropy measurements.

Overall, this study demonstrates the power of NMR in resolving structural, dynamic, and interaction features of the β-PIX SH3 domain and provides a framework for the rational design of peptide-based inhibitors targeting SH3-mediated PPIs in cancer.

Therese Malliavin (CNRS, Université de Lorraine, France)

LinkedIn: @Therese Malliavin

Abstract: Intrinsically disordered proteins (IDP) and intrinsically disordered regions (IDR) are at the center of numerous regulation and control pathways in the cell, and attract consequently extreme interest nowadays in structural biology. Nevertheless, it is difficult to characterize the conformational landscape of IDP,
as they sample highly variable conformations of similar energy. Thus, the structural convergence criterion used in classical NMR structure determination does not apply here. Therefore, the analysis of IDP conformational spaces classically relies on the use of Monte Carlo and molecular dynamics simulations. We present here the use of the  geometric Threading-Augmented interval Branch-and-Prune (TAiBP) approach which permits to enumerate systematically the possible conformations verifying a set of NMR chemical shifts. The combinatorial explosion due to the enumeration is alleviated by partitioning the input instances into consecutive peptide fragments and by systematic solutions clustering using self-organizing maps. The obtained sets of protein conformations can be further filtered using Small Angle X-ray Scattering (SAXS) curves or Residual Dipolar Coupling (RDC) values. Several applications will be presented.
References:
Huang, Shih, Jeng, Chang, Lin, Malliavin. pH Sensitivity of the SERF1a Conformational Ensemble. ACS Omega 2026 11:2614-2627. doi: 10.1021/acsomega.5c07620 Förster, Idier, Liberti, Mucherino, Lin, Malliavin. Low-resolution description of the conformational space for intrinsically disordered proteins. Sci Rep 2022 12:19057. doi: 10.1038/s41598-022-21648-9
Malliavin. Tandem domain structure determination based on a systematic enumeration of conformations. Sci Rep 2021 11:16925. doi: 10.1038/s41598-021-96370-z
Malliavin, Mucherino, Lavor, Liberti. Systematic Exploration of Protein Conformational Space Using a Distance Geometry Approach. J Chem Inf Model 2019 59:4486-4503
doi: 10.1021/acs.jcim.9b00215

Gottfried Otting (Australian National University, Australia)

Abstract: Using genetic encoding, single phenylalanine residues were replaced by pentafluorophenylalanine. The 19F-NMR spectrum shows that the C6F5 group rotates much more slowly than the phenyl rings of canonical phenylalanine residues. Crystal structures show minimal structural perturbation. Two applications stand out: (a) The five 19F-NMR resonances of a slowly rotating C6F5 group enable simple measurements of the aromatic ring flips even in big proteins (> 40 kDa) without isotope labelling. The ring flip rates are a measure of local protein malleability and change in response to ligand binding. (b) The 19F chemical shifts are very sensitive reporters of allosteric effects.

Amrita Sahu (Centre of Biomedical research, India)

LinkedIn: Amrita Sahu

Abstract: Chronic kidney disease (CKD) and Type 2 diabetes mellitus (DM) are global health burdens, with diabetes being the leading cause of end-stage renal disease, both marked by systemic metabolic disruption. This study applied 1H NMR-based serum metabolomics to characterize metabolic alterations in CKD only (n = 31), DM (n = 33), and their comorbid state (CKD_DM;   n = 45). A total of 45 polar metabolites and seven lipid signals were quantified, and statistical analysis was performed using MetaboAnalyst 6.0. The CKD_DM profile was not a linear combination of the CKD and DM profiles. Compared with DM, CKD_DM shows perturbation in pyruvate, glycerophospholipid, and butanoate metabolism, while tyrosine metabolism, TCA cycle, and cysteine–methionine were prominently altered in CKD only and CKD_DM group. CKD only and CKD_DM partially overlapped based on polar metabolites, and lipid-associated signals clearly separated all three groups. mROC analyses identified a significant six-metabolite panel (creatinine, glucose, urea, myo-inositol, glycine, choline) that robustly distinguished CKD_DM from DM(AUC>0.9). TMAO, isobutyrate, glycerol (AUC > 0.76), and a three-lipid-signal panel (AUC > 0.99) distinguished CKD only from CKD_DM, and the seven-metabolite panel separates CKD only from DM(AUC>0.9). Overall, CKD_DM emerges as a distinct metabolic phenotype with integrated metabolite and lipid signatures, enhanced disease stratification, and improved diagnostics.
Keywords: Chronic Kidney disease, Diabetes, NMR-based metabolomics, Metabolic biomarkers

Rimjhim Trivedi (Centre of Biomedical Research, India)

LinkedIn: Rimjhim Trivedi, X: @rimjhimtrivedi1

Abstract: Cognitive decline is a major age-related neurodegenerative condition lacking minimally invasive biomarkers. Systemic metabolic changes often mirror brain bioenergetic dysfunction, offering potential indicators of disease progression. This study used quantitative 1H NMR-based serum metabolomics to identify metabolic signatures linked to cognitive decline (CD, n = 40) compared with cognitively normal controls (NCD, n = 54). High-field 800 MHz 1H NMR spectroscopy was applied, followed by multivariate (PCA, OPLS-DA, Random Forest) and univariate analyses. Receiver operating characteristic (ROC) analysis assessed diagnostic performance, while correlations with Mini-Mental State Examination (MMSE) scores evaluated clinical relevance. Thirty-three metabolites and key ratios were quantified. CD subjects showed elevated glucose, pyruvate, acetate, acetoacetate, creatine, mannose, and urea, with reduced lactate, alanine, histidine, glutamine, glutamate, and branched-chain amino acids. Ratios including glutamine-to-glucose (QGR), alanine-to-glucose (AGR), and histidine-to-tyrosine (HTR) were significantly decreased. AGR and QGR declined with disease severity, and AGR correlated positively with MMSE scores. ROC analysis demonstrated strong diagnostic performance for QGR (AUC = 0.876), AGR (AUC = 0.840), and HTR (AUC = 0.822). Pathway analysis indicated impaired glycolysis-mitochondrial coupling, reduced pyruvate dehydrogenase activity, altered amino acid metabolism, and compensatory ketone/fatty-acid utilization. These findings highlight serum metabolomics as a promising non-invasive approach for assessing cognitive decline and monitoring progression.