Rapid and reliable protein structure determination via chemical shift threading

NMR investigations of glycan conformation, dynamics, and interactions

Glycans are ubiquitous in nature, decorating our cells and serving as the initial points of contact with any visiting entities. These glycan interactions are fundamental to host-pathogen recognition and are related to various diseases, including inflammation and cancer. Therefore, understanding the conformations and dynamics of glycans, as well as the key features that regulate their interactions with proteins, is crucial for designing new therapeutics. Due to the intrinsic flexibility of glycans, NMR is an essential tool for unravelling these properties. In this review, we describe the key NMR parameters that can be extracted from the different experiments, and which allow us to deduce the necessary geometry and molecular motion information, with a special emphasis on assessing the internal motions of the glycosidic linkages. We specifically address the NMR peculiarities of various natural glycans, from histo-blood group antigens to glycosaminoglycans, and also consider the special characteristics of their synthetic analogues (glycomimetics). Finally, we discuss the application of NMR protocols to study glycan-related molecular recognition events, both from the carbohydrate and receptor perspectives, including the use of stable isotopes and paramagnetic NMR methods to overcome the inherent degeneracy of glycan chemical shifts.

In-Cell Structural Biology by NMR: The Benefits of the Atomic Scale

In-cell structural biology aims at extracting structural information about proteins or nucleic acids in their native, cellular environment. This emerging field holds great promise and is already providing new facts and outlooks of interest at both fundamental and applied levels. NMR spectroscopy has important contributions on this stage: It brings information on a broad variety of nuclei at the atomic scale, which ensures its great versatility and uniqueness. Here, we detail the methods, the fundamental knowledge, and the applications in biomedical engineering related to in-cell structural biology by NMR. We finally propose a brief overview of the main other techniques in the field (EPR, smFRET, cryo-ET, etc.) to draw some advisable developments for in-cell NMR. In the era of large-scale screenings and deep learning, both accurate and qualitative experimental evidence are as essential as ever to understand the interior life of cells. In-cell structural biology by NMR spectroscopy can generate such a knowledge, and it does so at the atomic scale. This review is meant to deliver comprehensive but accessible information, with advanced technical details and reflections on the methods, the nature of the results, and the future of the field.

PyShifts: A PyMOL Plugin for Chemical Shift-Based Analysis of Biomolecular Ensembles

Here, we present PyShifts-a PyMOL plugin for chemical shift-based analysis of biomolecular ensembles. With PyShifts, users can compare and visualize differences between experimentally measured and computationally predicted chemical shifts. When analyzing multiple conformations of a biomolecule with PyShifts, users can also sort a set of conformations based on chemical shift differences and identify the conformers that exhibit the best agreement between measured and predicted chemical shifts. Although we have integrated PyShifts with the chemical shift predictors LARMOR^D and LARMOR^Cα, PyShifts can read in chemical shifts from any source, and so, users can employ PyShifts to analyze biomolecular structures using chemical shifts computed by any chemical shift predictor. We envision, therefore, that PyShifts (https://github.com/atfrank/PyShifts) will find utility as a general-purpose tool for exploring chemical shift-structure relationships in biomolecular ensembles.

Toward Structure Determination of Disulfide-Rich Peptides Using Chemical Shift-Based Methods

Disulfide-rich peptides are a class of molecules for which NMR spectroscopy has been the primary tool for structural characterization. Here, we explore whether the process can be achieved by using structural information encoded in chemical shifts. We examine (i) a representative set of five cyclic disulfide-rich peptides that have high-resolution NMR and X-ray structures and (ii) a larger set of 100 disulfide-rich peptides from the PDB. Accuracy of the calculated structures was dependent on the methods used for searching through conformational space and for identifying native conformations. Although Hα chemical shifts could be predicted reasonably well using SHIFTX, agreement between predicted and experimental chemical shifts was sufficient for identifying native conformations for only some peptides in the representative set. Combining chemical shift data with the secondary structure information and potential energy calculations improved the ability to identify native conformations. Additional use of sparse distance restraints or homology information to restrict the search space also improved the resolution of the calculated structures. This study demonstrates that abbreviated methods have potential for elucidation of peptide structures to high resolution and further optimization of these methods, e.g., improvement in chemical shift prediction accuracy, will likely help transition these methods into the mainstream of disulfide-rich peptide structural biology.