Protein structural class identification directly from NMR spectra using averaged chemical shifts

Knowledge of the three-dimensional structure of proteins is integral to understanding their functions, and a necessity in the era of proteomics. A wide range of computational methods is employed to estimate the secondary, tertiary, and quaternary structures of proteins. Comprehensive experimental methods, on the other hand, are limited to nuclear magnetic resonance (NMR) and X-ray crystallography. The full characterization of individual structures, using either of these techniques, is extremely time intensive. The demands of high throughput proteomics necessitate the development of new, faster experimental methods for providing structural information. As a first step toward such a method, we explore the possibility of determining the structural classes of proteins directly from their NMR spectra, prior to resonance assignment, using averaged chemical shifts. This is achieved by correlating NMR-based information with empirical structure-based information available in widely used electronic databases. The results are analyzed statistically for their significance. The robustness of the method as a structure predictor is probed by applying it to a set of proteins of unknown structure. Our results show that this NMR-based method can be used as a low-resolution tool for protein structural class identification.     

Integrative Structural Biology in the Era of Accurate Structure Prediction

Characterizing the three-dimensional structure of macromolecules is central to understanding their function. Traditionally, structures of proteins and their complexes have been determined using experimental techniques such as X-ray crystallography, NMR, or cryo-electron microscopy—applied individually or in an integrative manner. Meanwhile, however, computational methods for protein structure prediction have been improving their accuracy, gradually, then suddenly, with the breakthrough advance by AlphaFold2, whose models of monomeric proteins are often as accurate as experimental structures. This breakthrough foreshadows a new era of computational methods that can build accurate models for most monomeric proteins. Here, we envision how such accurate modeling methods can combine with experimental structural biology techniques, enhancing integrative structural biology. We highlight the challenges that arise when considering multiple structural conformations, protein complexes, and polymorphic assemblies. These challenges will motivate further developments, both in modeling programs and in methods to solve experimental structures, towards better and quicker investigation of structure–function relationships.     

Solid-state NMR structures of integral membrane proteins

Abstract

Solid-state NMR is unique for its ability to obtain three-dimensional structures and to measure atomic-resolution structural and dynamic information for membrane proteins in native lipid bilayers. An increasing number and complexity of integral membrane protein structures have been determined by solid-state NMR using two main methods. Oriented sample solid-state NMR uses macroscopically aligned lipid bilayers to obtain orientational restraints that define secondary structure and global fold of embedded peptides and proteins and their orientation and topology in lipid bilayers. Magic angle spinning (MAS) solid-state NMR uses unoriented rapidly spinning samples to obtain distance and torsion angle restraints that define tertiary structure and helix packing arrangements. Details of all current protein structures are described, highlighting developments in experimental strategy and other technological advancements. Some structures originate from combining solid- and solution-state NMR information and some have used solid-state NMR to refine X-ray crystal structures. Solid-state NMR has also validated the structures of proteins determined in different membrane mimetics by solution-state NMR and X-ray crystallography and is therefore complementary to other structural biology techniques. By continuing efforts in identifying membrane protein targets and developing expression, isotope labelling and sample preparation strategies, probe technology, NMR experiments, calculation and modelling methods and combination with other techniques, it should be feasible to determine the structures of many more membrane proteins of biological and biomedical importance using solid-state NMR. This will provide three-dimensional structures and atomic-resolution structural information for characterising ligand and drug interactions, dynamics and molecular mechanisms of membrane proteins under physiological lipid bilayer conditions.     

Structural analysis of intrinsically disordered proteins by small-angle X-ray scattering

Small-angle scattering of X-rays (SAXS) is an established method to study the overall structure and structural transitions of biological macromolecules in solution. For folded proteins, the technique provides three-dimensional low resolution structures ab initio or it can be used to drive rigid-body modeling. SAXS is also a powerful tool for the quantitative analysis of flexible systems, including intrinsically disordered proteins (IDPs), and is highly complementary to the high resolution methods of X-ray crystallography and NMR. Here we present the basic principles of SAXS and review the main approaches to the characterization of IDPs and flexible multidomain proteins using SAXS. Together with the standard approaches based on the analysis of overall parameters, a recently developed Ensemble Optimization Method (EOM) is now available. The latter method allows for the co-existence of multiple protein conformations in solution compatible with the scattering data. Analysis of the selected ensembles provides quantitative information about flexibility and also offers insights into structural features. Examples of the use of SAXS and combined approaches with NMR, X-ray crystallography, and computational methods to characterize completely or partially disordered proteins are presented.     

Combination of NMR spectroscopy and X-ray crystallography offers unique advantages for elucidation of the structural basis of protein complex assembly

NMR spectroscopy and X-ray crystallography are two premium methods for determining the atomic structures of macro-biomolecular complexes. Each method has unique strengths and weaknesses. While the two techniques are highly complementary, they have generally been used separately to address the structure and functions of biomolecular complexes. In this review, we emphasize that the combination of NMR spectroscopy and X-ray crystallography offers unique power for elucidating the structures of complicated protein assemblies. We demonstrate, using several recent examples from our own laboratory, that the exquisite sensitivity of NMR spectroscopy in detecting the conformational properties of individual atoms in proteins and their complexes, without any prior knowledge of conformation, is highly valuable for obtaining the high quality crystals necessary for structure determination by X-ray crystallography. Thus NMR spectroscopy, in addition to answering many unique structural biology questions that can be addressed specifically by that technique, can be exceedingly powerful in modern structural biology when combined with other techniques including X-ray crystallography and cryo-electron microscopy.     

Residual dipolar couplings: Synergy between NMR and structural genomics

Structural genomics is on a quest for the structure and function of a significant fraction of gene products. Current efforts are focusing on structure determination of single-domain proteins, which can readily be targeted by X-ray crystallography, NMR spectroscopy and computational homology modeling. However, comprehensive association of gene products with functions also requires systematic determination of more complex protein structures and other biomolecules participating in cellular processes such as nucleic acids, and characterization of biomolecular interactions and dynamics relevant to function. Such NMR investigations are becoming more feasible, not only due to recent advances in NMR methodology, but also because structural genomics is providing valuable structural information and new experimental and computational tools. The measurement of residual dipolar couplings in partially oriented systems and other new NMR methods will play an important role in this synergistic relationship between NMR and structural genomics. Both an expansion in the domain of NMR application, and important contributions to future structural genomics efforts can be anticipated.     

Structural proteomics by NMR spectroscopy

Structural proteomics is one of the powerful research areas in the postgenomic era, elucidating structure-function relationships of uncharacterized gene products based on the 3D protein structure. It proposes biochemical and cellular functions of unannotated proteins and thereby identifies potential drug design and protein engineering targets. Recently, a number of pioneering groups in structural proteomics research have achieved proof of structural proteomic theory by predicting the 3D structures of hypothetical proteins that successfully identified the biological functions of those proteins. The pioneering groups made use of a number of techniques, including NMR spectroscopy, which has been applied successfully to structural proteomics studies over the past 10 years. In addition, advances in hardware design, data acquisition methods, sample preparation and automation of data analysis have been developed and successfully applied to high-throughput structure determination techniques. These efforts ensure that NMR spectroscopy will become an important methodology for performing structural proteomics research on a genomic scale. NMR-based structural proteomics together with x-ray crystallography will provide a comprehensive structural database to predict the basic biological functions of hypothetical proteins identified by the genome projects.     

Validation of macromolecular flexibility in solution by small-angle X-ray scattering (SAXS)

The dynamics of macromolecular conformations are critical to the action of cellular networks. Solution X-ray scattering studies, in combination with macromolecular X-ray crystallography (MX) and nuclear magnetic resonance (NMR), strive to determine complete and accurate states of macromolecules, providing novel insights describing allosteric mechanisms, supramolecular complexes, and dynamic molecular machines. This review addresses theoretical and practical concepts, concerns, and considerations for using these techniques in conjunction with computational methods to productively combine solution-scattering data with high-resolution structures. I discuss the principal means of direct identification of macromolecular flexibility from SAXS data followed by critical concerns about the methods used to calculate theoretical SAXS profiles from high-resolution structures. The SAXS profile is a direct interrogation of the thermodynamic ensemble and techniques such as, for example, minimal ensemble search (MES), enhance interpretation of SAXS experiments by describing the SAXS profiles as population-weighted thermodynamic ensembles. I discuss recent developments in computational techniques used for conformational sampling, and how these techniques provide a basis for assessing the level of the flexibility within a sample. Although these approaches sacrifice atomic detail, the knowledge gained from ensemble analysis is often appropriate for developing hypotheses and guiding biochemical experiments. Examples of the use of SAXS and combined approaches with X-ray crystallography, NMR, and computational methods to characterize dynamic assemblies are presented.     

Recent advances in RNA-protein recognition

The past few years have witnessed remarkable progress in knowledge of the structure and function of RNA-binding proteins and their RNA complexes. X-ray crystallography and NMR spectroscopy have provided structures for all major classes of RNA-binding proteins, both alone and complexed with RNA. New computational and experimental tools have provided unprecedented insight into the molecular basis of RNA recognition.     

Free-energy calculations highlight differences in accuracy between X-ray and NMR structures and add value to protein structure prediction

BACKGROUND: While X-ray crystallography structures of proteins are considerably more reliable than those from NMR spectroscopy, it has been difficult to assess the inherent accuracy of NMR structures, particularly the side chains. RESULTS: For 15 small single-domain proteins, we used a molecular mechanics-/dynamics-based free-energy approach to investigate native, decoy, and fully extended alpha conformations. Decoys were all less energetically favorable than native conformations in nine of the ten X-ray structures and in none of the five NMR structures, but short 150 ps molecular dynamics simulations on the experimental structures caused them to have the lowest predicted free energy in all 15 proteins. In addition, a strong correlation exists (r(2) = 0.86) between the predicted free energy of unfolding, from native to fully extended conformations, and the number of residues. CONCLUSIONS: This work suggests that the approximate treatment of solvent used in solving NMR structures can lead NMR model conformations to be less reliable than crystal structures. This conclusion was reached because of the considerably higher calculated free energies and the extent of structural deviation during aqueous dynamics simulations of NMR models compared to those determined by X-ray crystallography. Also, the strong correlation found between protein length and predicted free energy of unfolding in this work suggests, for the first time, that a free-energy function can allow for identification of the native state based on calculations on an extended state and in the absence of an experimental structure.     

Structure-based functional discovery of proteins: structural proteomics

The discovery of biochemical and cellular functions of unannotated gene products begins with a database search of proteins with structure/sequence homologues based on known genes. Very recently, a number of frontier groups in structural biology proposed a new paradigm to predict biological functions of an unknown protein on the basis of its three-dimensional structure on a genomic scale. Structural proteomics (genomics), a research area for structure-based functional discovery, aims to complete the protein-folding universe of all gene products in a cell. It would lead us to a complete understanding of a living organism from protein structure. Two major complementary experimental techniques, X-ray crystallography and NMR spectroscopy, combined with recently developed high throughput methods have played a central role in structural proteomics research; however, an integration of these methodologies together with comparative modeling and electron microscopy would speed up the goal for completing a full dictionary of protein folding space in the near future.     

Optimal atomic-resolution structures of prion AGAAAAGA amyloid fibrils

X-ray crystallography is a powerful tool to determine the protein 3D structure. However, it is time-consuming and expensive, and not all proteins can be successfully crystallized, particularly for membrane proteins. Although nuclear magnetic resonance (NMR) spectroscopy is indeed a very powerful tool in determining the 3D structures of membrane proteins, it is also time-consuming and costly. To the best of the authors' knowledge, there is little structural data available on the AGAAAAGA palindrome in the hydrophobic region (113-120) of prion proteins due to the noncrystalline and insoluble nature of the amyloid fibril, although many experimental studies have shown that this region has amyloid fibril forming properties and plays an important role in prion diseases. In view of this, the present study is devoted to address this problem from computational approaches such as global energy optimization, simulated annealing, and structural bioinformatics. The optimal atomic-resolution structures of prion AGAAAAGA amyloid fibils reported in this paper have a value to the scientific community in its drive to find treatments for prion diseases.     

Molecular dynamics simulations of proteins in lipid bilayers

With recent advances in X-ray crystallography of membrane proteins promising many new high-resolution structures, molecular dynamics simulations will become increasingly valuable for understanding membrane protein function, as they can reveal the dynamic behavior concealed in the static structures. Dramatic increases in computational power, in synergy with more efficient computational methodologies, now allow us to carry out molecular dynamics simulations of any structurally known membrane protein in its native environment, covering timescales of up to 0.1 micros. At the frontiers of membrane protein simulations are ion channels, aquaporins, passive and active transporters, and bioenergetic proteins.     

Studying DNA-protein interactions using NMR.

NMR spectroscopy is emerging as a powerful tool in molecular biology and biotechnology; one aspect of which is the use of one- and two-dimensional NMR methodologies to investigate the interactions of proteins with DNA. The dynamic and structural information which NMR can provide, on the changes in conformation and molecular flexibility, complements X-ray crystallography data and enables mechanistic models of DNA-protein interactions to be formulated.     

Relative stability of protein structures determined by X-ray crystallography or NMR spectroscopy: a molecular dynamics simulation study

The relative stability of protein structures determined by either X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy has been investigated by using molecular dynamics simulation techniques. Published structures of 34 proteins containing between 50 and 100 residues have been evaluated. The proteins selected represent a mixture of secondary structure types including all alpha, all beta, and alpha/beta. The proteins selected do not contain cysteine-cysteine bridges. In addition, any crystallographic waters, metal ions, cofactors, or bound ligands were removed before the systems were simulated. The stability of the structures was evaluated by simulating, under identical conditions, each of the proteins for at least 5 ns in explicit solvent. It is found that not only do NMR-derived structures have, on average, higher internal strain than structures determined by X-ray crystallography but that a significant proportion of the structures are unstable and rapidly diverge in simulations.     

Structure determination of α-helical membrane proteins by solution-state NMR: Emphasis on retinal proteins

The biochemical processes of living cells involve a numerous series of reactions that work with exceptional specificity and efficiency. The tight control of this intricate reaction network stems from the architecture of the proteins that drive the chemical reactions and mediate protein–protein interactions. Indeed, the structure of these proteins will determine both their function and interaction partners. A detailed understanding of the proximity and orientation of pivotal functional groups can reveal the molecular mechanistic basis for the activity of a protein. Together with X-ray crystallography and electron microscopy, NMR spectroscopy plays an important role in solving three-dimensional structures of proteins at atomic resolution. In the challenging field of membrane proteins, retinal-binding proteins are often employed as model systems and prototypes to develop biophysical techniques for the study of structural and functional mechanistic aspects. The recent determination of two 3D structures of seven-helical trans-membrane retinal proteins by solution-state NMR spectroscopy highlights the potential of solution NMR techniques in contributing to our understanding of membrane proteins. This review summarizes the multiple strategies available for expression of isotopically labeled membrane proteins. Different environments for mimicking lipid bilayers will be presented, along with the most important NMR methods and labeling schemes used to generate high-quality NMR spectra. The article concludes with an overview of types of conformational restraints used for generation of high-resolution structures of membrane proteins. This article is part of a Special Issue entitled: Retinal Proteins — You can teach an old dog new tricks.     

The dynamic duo: Combining NMR and small angle scattering in structural biology

Structural biology provides essential information for elucidating molecular mechanisms that underlie biological function. Advances in hardware, sample preparation, experimental methods, and computational approaches now enable structural analysis of protein complexes with increasing complexity that more closely represent biologically entities in the cellular environment. Integrated multidisciplinary approaches are required to overcome limitations of individual methods and take advantage of complementary aspects provided by different structural biology techniques. Although X‐ray crystallography remains the method of choice for structural analysis of large complexes, crystallization of flexible systems is often difficult and does typically not provide insights into conformational dynamics present in solution. Nuclear magnetic resonance spectroscopy (NMR) is well‐suited to study dynamics at picosecond to second time scales, and to map binding interfaces even of large systems at residue resolution but suffers from poor sensitivity with increasing molecular weight. Small angle scattering (SAS) methods provide low resolution information in solution and can characterize dynamics and conformational equilibria complementary to crystallography and NMR. The combination of NMR, crystallography, and SAS is, thus, very useful for analysis of the structure and conformational dynamics of (large) protein complexes in solution. In high molecular weight systems, where NMR data are often sparse, SAS provides additional structural information and can differentiate between NMR‐derived models. Scattering data can also validate the solution conformation of a crystal structure and indicate the presence of conformational equilibria. Here, we review current state‐of‐the‐art approaches for combining NMR, crystallography, and SAS data to characterize protein complexes in solution.     

Three-dimensional models of HDL apoA-I: implications for its assembly and function

The purpose of this review is to highlight recent advances toward the refinement of a three-dimensional structure for lipid-bound apolipoprotein A-I (apoA-I) on recombinant HDL. Recently, X-ray crystallography has yielded a new structure for full-length, lipid-free apoA-I. Although this approach has not yet been successful in solving the three-dimensional structure of lipid-bound apoA-I, analysis of the X-ray structures has been of immense help in the interpretation of structural data obtained from other methods that yield structural information. Recent studies emphasize the use of mass spectrometry to unambiguously identify cross-linked peptides or to quantify solvent accessibility using hydrogen-deuterium exchange. The combination of mass spectrometry, molecular modeling, molecular dynamic analysis, and small-angle X-ray diffraction has provided additional structural information on apoA-I folding that complements previous approaches.     

A polynomial-time algorithm for de novo protein backbone structure determination from nuclear magnetic resonance data.

We describe an efficient algorithm for protein backbone structure determination from solution Nuclear Magnetic Resonance (NMR) data. A key feature of our algorithm is that it finds the conformation and orientation of secondary structure elements as well as the global fold in polynomial time. This is the first polynomial-time algorithm for de novo high-resolution biomacromolecular structure determination using experimentally recorded data from either NMR spectroscopy or X-ray crystallography. Previous algorithmic formulations of this problem focused on using local distance restraints from NMR (e.g., nuclear Overhauser effect [NOE] restraints) to determine protein structure. This approach has been shown to be NP-hard, essentially due to the local nature of the constraints. In practice, approaches such as molecular dynamics and simulated annealing, which lack both combinatorial precision and guarantees on running time and solution quality, are used routinely for structure determination. We show that residual dipolar coupling (RDC) data, which gives global restraints on the orientation of internuclear bond vectors, can be used in conjunction with very sparse NOE data to obtain a polynomial-time algorithm for structure determination. Furthermore, an implementation of our algorithm has been applied to six different real biological NMR data sets recorded for three proteins. Our algorithm is combinatorially precise, polynomialtime, and uses much less NMR data to produce results that are as good or better than previous approaches in terms of accuracy of the computed structure as well as running time.