Current approaches for integrating solution NMR spectroscopy and small-angle scattering to study the structure and dynamics of biomolecular complexes

Bridging attraction of condensed bovine serum albumin solution in the presence of trivalent ions: A SANS study

The bridging attraction of condensed bovine serum albumin (BSA) solution (D2O) in the presence of yttrium chloride (YCl3) was studied by small angle neutron scattering (SANS). With increasing the concentration of YCl3 (cY) from 3 to 15 mM and from 15 to 100 mM, the intensity in low-q region increases and then decreases. Combining the tri-axial ellipsoid (TaE) geometry and the multi-component sticky hard sphere (SHS) potential, a SHS-TaE model was established to quantitatively determine the size and distribution of particles. In this way, the structural mechanism of the aggregation-redissolution process in protein solution was demonstrated and discussed. As cY increases from 3 to 100 mM, the SHS radius rL decreases from ca. 2.97 to 2.50 nm, suggesting that the relatively well dispersed BSAs may form aggregates with various polydispersities. The axis a increases from 1.88 to 2.30 nm, while b and c decrease from 3.53 to 3.23 nm and from 4.12 to 3.55 nm, respectively. (RgTaE decreases from ca. 2.57 to 2.38 nm). Moreover, the scattering length density (SLD) of BSA decreases from 3.67 to 1.56 × 10-6 Å-2. All these results consistently indicate a strengthened attraction and the BSA molecules might shrink and tune out to be more like of oblate ellipsoid with increasing the amount of YCl3.

Observation of pH-Dependent Residual Structure in the Pmel17 Repeat Domain and the Implication for Its Amyloid Formation

The varying conformational states of amyloid-forming protein monomers can determine their fibrillation outcome. In this study, we utilize solution NMR and the paramagnetic relaxation enhancement (PRE) effect to observe monomer properties of the repeat domain (RPT) from a human functional amyloid, premelanosomal protein, Pmel17. After excision from the full-length protein, RPT can self-assemble into amyloid fibrils, functioning as a scaffold for melanin deposition. Here, we report possible conformational states of the short RPT (sRPT) isoform, which has been demonstrated to be a fibrillation nucleator. NMR experiments were performed to determine conformational differences in sRPT by comparing aggregation-prone vs nonaggregating solution conditions. We observed significant chemical shift perturbations localized to residues near the C-terminus, demonstrating that the local chemical environment of the amyloid core region is highly sensitive to changes in pH. Next, we introduced cysteine point mutations for the covalent attachment of PRE ligands to sRPT to facilitate the observation of intramolecular interactions. We also utilized solvent PRE molecules with opposing charges to measure changes in the electrostatic potential of sRPT in different pH environments. These observed PRE effects offer insight into initial molecular events that might promote intermolecular interactions, which can trigger fibrillation. Taken together, our results show that sRPT monomers adopt a conformation inconsistent with a fully random coil at neutral pH and undergo conformational changes at lower pH values. These observations highlight regulatory mechanisms via organelle-associated pH conditions that can affect the fibrillation activity of proteins like RPT.

Biophysical and Integrative Characterization of Protein Intrinsic Disorder as a Prime Target for Drug Discovery

Protein intrinsic disorder is increasingly recognized for its biological and disease-driven functions. However, it represents significant challenges for biophysical studies due to its high conformational flexibility. In addressing these challenges, we highlight the complementary and distinct capabilities of a range of experimental and computational methods and further describe integrative strategies available for combining these techniques. Integrative biophysics methods provide valuable insights into the sequence–structure–function relationship of disordered proteins, setting the stage for protein intrinsic disorder to become a promising target for drug discovery. Finally, we briefly summarize recent advances in the development of new small molecule inhibitors targeting the disordered N-terminal domains of three vital transcription factors.

Combining NMR, SAXS and SANS to characterize the structure and dynamics of protein complexes

Understanding the structure and dynamics of biological macromolecules is essential to decipher the molecular mechanisms that underlie cellular functions. The description of structure and conformational dynamics often requires the integration of complementary techniques. In this review, we highlight the utility of combining nuclear magnetic resonance (NMR) spectroscopy with small angle scattering (SAS) to characterize these challenging biomolecular systems. NMR can assess the structure and conformational dynamics of multidomain proteins, RNAs and biomolecular complexes. It can efficiently provide information on interaction surfaces, long-distance restraints and relative domain orientations at residue-level resolution. Such information can be readily combined with high-resolution structural data available on subcomponents of biomolecular assemblies. Moreover, NMR is a powerful tool to characterize the dynamics of biomolecules on a wide range of timescales, from nanoseconds to seconds. On the other hand, SAS approaches provide global information on the size and shape of biomolecules and on the ensemble of all conformations present in solution. Therefore, NMR and SAS provide complementary data that are uniquely suited to investigate dynamic biomolecular assemblies. Here, we briefly review the type of data that can be obtained by both techniques and describe different approaches that can be used to combine them to characterize biomolecular assemblies. We then provide guidelines on which experiments are best suited depending on the type of system studied, ranging from fully rigid complexes, dynamic structures that interconvert between defined conformations and systems with very high structural heterogeneity.

Solvent paramagnetic relaxation enhancement as a versatile method for studying structure and dynamics of biomolecular systems

Solvent paramagnetic relaxation enhancement (sPRE) is a versatile nuclear magnetic resonance (NMR)-based method that allows characterization of the structure and dynamics of biomolecular systems through providing quantitative experimental information on solvent accessibility of NMR-active nuclei. Addition of soluble paramagnetic probes to the solution of a biomolecule leads to paramagnetic relaxation enhancement in a concentration-dependent manner. Here we review recent progress in the sPRE-based characterization of structural and dynamic properties of biomolecules and their complexes, and aim to deliver a comprehensive illustration of a growing number of applications of the method to various biological systems. We discuss the physical principles of sPRE measurements and provide an overview of available co-solute paramagnetic probes. We then explore how sPRE, in combination with complementary biophysical techniques, can further advance biomolecular structure determination, identification of interaction surfaces within protein complexes, and probing of conformational changes and low-population transient states, as well as deliver insights into weak, nonspecific, and transient interactions between proteins and co-solutes. In addition, we present examples of how the incorporation of solvent paramagnetic probes can improve the sensitivity of NMR experiments and discuss the prospects of applying sPRE to NMR metabolomics, drug discovery, and the study of intrinsically disordered proteins.

Interdomain Dynamics via Paramagnetic NMR on the Highly Flexible Complex Calmodulin/Munc13-1

Paramagnetic NMR constraints are very useful to study protein interdomain motion, but their interpretation is not always straightforward. On the example of the particularly flexible complex Calmodulin/Munc13-1, we present a new approach to characterize this motion with pseudocontact shifts and residual dipolar couplings. Using molecular mechanics, we sampled the conformational space of the complex and used a genetic algorithm to find ensembles that are in agreement with the data. We used the Bayesian information criterion to determine the ideal ensemble size. This way, we were able to make an accurate, unambiguous, reproducible model of the interdomain motion of Calmodulin/Munc13-1 without prior knowledge about the domain orientation from crystallography.

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.

Biasing RNA Coarse-Grained Folding Simulations with Small-Angle X-ray Scattering Data

RNA molecules can easily adopt alternative structures in response to different environmental conditions. As a result, a molecule's energy landscape is rough and can exhibit a multitude of deep basins. In the absence of a high-resolution structure, small-angle X-ray scattering data (SAXS) can narrow down the conformational space available to the molecule and be used in conjunction with physical modeling to obtain high-resolution putative structures to be further tested by experiments. Because of the low resolution of these data, it is natural to implement the integration of SAXS data into simulations using a coarse-grained representation of the molecule, allowing for much wider searches and faster evaluation of SAXS theoretical intensity curves than with atomistic models. We present here the theoretical framework and the implementation of a simulation approach based on our coarse-grained model HiRE-RNA combined with SAXS evaluations "on-the-fly" leading the simulation toward conformations agreeing with the scattering data, starting from partially folded structures as the ones that can easily be obtained from secondary structure prediction-based tools. We show on three benchmark systems how our approach can successfully achieve high-resolution structures with remarkable similarity with the native structure recovering not only the overall shape, as imposed by SAXS data, but also the details of initially missing base pairs.

Segmental and site-specific isotope labelling strategies for structural analysis of posttranslationally modified proteins

Posttranslational modifications can alter protein structures, functions and locations, and are important cellular regulatory and signalling mechanisms. Spectroscopic techniques such as nuclear magnetic resonance, infrared and Raman spectroscopy, as well as small-angle scattering, can provide insights into the structural and dynamic effects of protein posttranslational modifications and their impact on interactions with binding partners. However, heterogeneity of modified proteins from natural sources and spectral complexity often hinder analyses, especially for large proteins and macromolecular assemblies. Selective labelling of proteins with stable isotopes can greatly simplify spectra, as one can focus on labelled residues or segments of interest. Employing chemical biology tools for modifying and isotopically labelling proteins with atomic precision provides access to unique protein samples for structural biology and spectroscopy. Here, we review site-specific and segmental isotope labelling methods that are employed in combination with chemical and enzymatic tools to access posttranslationally modified proteins. We discuss illustrative examples in which these methods have been used to facilitate spectroscopic studies of posttranslationally modified proteins, providing new insights into biology.

Structural and Functional Insights into the Transmembrane Domain Association of Eph Receptors

Eph receptors are the largest family of receptor tyrosine kinases and by interactions with ephrin ligands mediate a myriad of processes from embryonic development to adult tissue homeostasis. The interaction of Eph receptors, especially at their transmembrane (TM) domains is key to understanding their mechanism of signal transduction across cellular membranes. We review the structural and functional aspects of EphA1/A2 association and the techniques used to investigate their TM domains: NMR, molecular modelling/dynamics simulations and fluorescence. We also introduce transmembrane peptides, which can be used to alter Eph receptor signaling and we provide a perspective for future studies.

Zooming in on protein-RNA interactions: a multi-level workflow to identify interaction partners

Interactions between proteins and RNA are at the base of numerous cellular regulatory and functional phenomena. The investigation of the biological relevance of non-coding RNAs has led to the identification of numerous novel RNA-binding proteins (RBPs). However, defining the RNA sequences and structures that are selectively recognised by an RBP remains challenging, since these interactions can be transient and highly dynamic, and may be mediated by unstructured regions in the protein, as in the case of many non-canonical RBPs. Numerous experimental and computational methodologies have been developed to predict, identify and verify the binding between a given RBP and potential RNA partners, but navigating across the vast ocean of data can be frustrating and misleading. In this mini-review, we propose a workflow for the identification of the RNA binding partners of putative, newly identified RBPs. The large pool of potential binders selected by in-cell experiments can be enriched by in silico tools such as catRAPID, which is able to predict the RNA sequences more likely to interact with specific RBP regions with high accuracy. The RNA candidates with the highest potential can then be analysed in vitro to determine the binding strength and to precisely identify the binding sites. The results thus obtained can furthermore validate the computational predictions, offering an all-round solution to the issue of finding the most likely RNA binding partners for a newly identified potential RBP.

Structures and target RNA preferences of the RNA-binding protein family of IGF2BPs: An overview

Insulin-like growth factor 2 mRNA-binding proteins (IMPs, IGF2BPs) act in mRNA transport and translational control but are oncofetal tumor marker proteins. The IMP protein family represents a number of bona fide multi-domain RNA-binding proteins with up to six RNA-binding domains, resulting in a high complexity of possible modes of interactions with target mRNAs. Their exact mechanism in stability control of oncogenic mRNAs is only partially understood. Our and other laboratories' recent work has significantly pushed the understanding of IMP protein specificities both toward RNA engagement and between each other from NMR and crystal structures serving the basis for systematic biochemical and functional investigations. We here summarize the known structural and biochemical information about IMP RNA-binding domains and their RNA preferences. The article also touches on the respective roles of RNA secondary and protein tertiary structures for specific RNA-protein complexes, including the limited knowledge about IMPs' protein-protein interactions, which are often RNA mediated.

Protein Structure Prediction from NMR Hydrogen-Deuterium Exchange Data

Amide hydrogen-deuterium exchange (HDX) has long been used to determine regional flexibility and binding sites in proteins; however, the data are too sparse for full structural characterization. Experiments that measure HDX rates, such as HDX-NMR, have far higher throughput compared to structure determination via X-ray crystallography, cryo-EM, or a full suite of NMR experiments. Data from HDX-NMR experiments encode information on the protein structure, making HDX a prime candidate to be supplemented by computational algorithms for protein structure prediction. We have developed a methodology to incorporate HDX-NMR data into ab initio protein structure prediction using the Rosetta software framework to predict structures based on experimental agreement. To demonstrate the efficacy of our algorithm, we examined 38 proteins with HDX-NMR data available, comparing the predicted model with and without the incorporation of HDX data into scoring. The root-mean-square deviation (rmsd, a measure of the average atomic distance between superimposed models) of the predicted model improved by 1.42 Å on average after incorporating the HDX-NMR data into scoring. The average rmsd improvement for the proteins where the selected model rmsd changed after incorporating HDX data was 3.63 Å, including one improvement of more than 11 Å and seven proteins improving by greater than 4 Å, with 12/15 proteins improving overall. Additionally, for independent verification, two proteins that were not part of the original benchmark were scored including HDX data, with a dramatic improvement of the selected model rmsd of nearly 9 Å for one of the proteins. Moreover, we have developed a confidence metric allowing us to successfully identify near-native models in the absence of a native structure. Improvement in model selection with a strong confidence measure demonstrates that protein structure prediction with HDX-NMR is a powerful tool which can be performed with minimal additional computational strain and expense.

Combining Experimental Data and Computational Methods for the Non-Computer Specialist

Experimental methods are indispensable for the study of the function of biological macromolecules, not just as static structures, but as dynamic systems that change conformation, bind partners, perform reactions, and respond to different stimulus. However, providing a detailed structural interpretation of the results is often a very challenging task. While experimental and computational methods are often considered as two different and separate approaches, the power and utility of combining both is undeniable. The integration of the experimental data with computational techniques can assist and enrich the interpretation, providing new detailed molecular understanding of the systems. Here, we briefly describe the basic principles of how experimental data can be combined with computational methods to obtain insights into the molecular mechanism and expand the interpretation through the generation of detailed models.