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.     

A tour of structural genomics

Structural genomics projects aim to provide an experimental or computational three-dimensional model structure for all of the tractable macromolecules that are encoded by complete genomes. To this end, pilot centres worldwide are now exploring the feasibility of large-scale structure determination. Their experimental structures and computational models are expected to yield insight into the molecular function and mechanism of thousands of proteins. The pervasiveness of this information is likely to change the use of structure in molecular biology and biochemistry.     

Structure determination of biological macromolecules in solution using nuclear magnetic resonance spectroscopy

A detailed understanding of the function of a biological macromolecule requires knowledge of its three-dimensional structure. Most atomic-resolution structures of biological macromolecules have been solved either by X-ray diffraction in single crystals or by nuclear magnetic resonance (NMR) in solution. This review surveys the method of NMR structure determination. First, a brief introduction to NMR and its basic concepts is presented. The main part of the article deals with the individual steps necessary for an NMR structure determination. At the end, the discussion turns to considerations on the influence of the molecular size of the macromolecules on the structure determination by NMR. New techniques are discussed that greatly enhance the possibilities of applying NMR to large molecular systems.     

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.     

Shaker pore structure as predicted by annealed atomic simulation using symmetry and novel geometric restraints

Recent studies making use of channel-blocking peptides as molecular calipers have revealed the architecture of the pore-forming region of Shaker-type potassium channels. Here we show that the low-resolution, experimentally derived geometric information can be incorporated as restraints within the context of an annealed molecular dynamics simulation to predict an atomic structure for the channel pore which, by virtue of restraints, conforms to the experimental evidence. The simulation is reminiscent of the computational method employed by nuclear magnetic resonance (NMR) spectroscopists to resolve solution structures of biological macromolecules, but in lieu of restraints conventionally derived from NMR spectra, novel restraints are developed that include side-chain orientation of amino acid residues and assumed symmetry of protein subunits. The method presented here offers the possibility of expanding cooperation between simulation and experiment in developing structural models, especially for systems such as ion channels whose three-dimensional structures may not be amenable to determination by direct methods at the present time.     

MOLMOL: A program for display and analysis of macromolecular structures

MOLMOL is a molecular graphics program for display, analysis, and manipulation of three-dimensional structures of biological macromolecules, with special emphasis on nuclear magnetic resonance (NMR) solution structures of proteins and nucleic acids. MOLMOL has a graphical user interface with menus, dialog boxes, and on-line help. The display possibilities include conventional presentation, as well as novel schematic drawings, with the option of combining different presentations in one view of a molecule. Covalent molecular structures can be modified by addition or removal of individual atoms and bonds, and three-dimensional structures can be manipulated by interactive rotation about individual bonds. Special efforts were made to allow for appropriate display and analysis of the sets of typically 20–40 conformers that are conventionally used to represent the result of an NMR structure determination, using functions for superimposing sets of conformers, calculation of root mean square distance (RMSD) values, identification of hydrogen bonds, checking and displaying violations of NMR constraints, and identification and listing of short distances between pairs of hydrogen atoms.     

Recent developments in structural proteomics for protein structure determination

The major challenges in structural proteomics include identifying all the proteins on the genome-wide scale, determining their structure-function relationships, and outlining the precise three-dimensional structures of the proteins. Protein structures are typically determined by experimental approaches such as X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. However, the knowledge of three-dimensional space by these techniques is still limited. Thus, computational methods such as comparative and de novo approaches and molecular dynamic simulations are intensively used as alternative tools to predict the three-dimensional structures and dynamic behavior of proteins. This review summarizes recent developments in structural proteomics for protein structure determination; including instrumental methods such as X-ray crystallography and NMR spectroscopy, and computational methods such as comparative and de novo structure prediction and molecular dynamics simulations.     

Trajectory analysis of NMR structure calculations

Summary NMR as well as X-ray crystallography are used to determine the three-dimensional structures of macromolecules at atomic resolution. Structure calculation generates coordinates that are compatible with NMR data from randomly generated initial structures. We analyzed the trajectory taken by structures during NMR structure calculation in conformational space, assuming that the distance between two structures in conformational space is the root-mean-square deviation between the two structures. The coordinates of a structure in conformational space were obtained by applying the metric multidimensional scaling method. As an example, we used a 22-residue peptide, -Conotoxin GIIIA, and a simulated annealing protocol of XPLOR. We found that the three-dimensional solution of the multidimensional scaling analysis is sufficient to describe the overall configuration of the trajectories in conformational space. By comparing the trajectories of the entire calculation with those of the converged calculation, random sampling of conformational space is readily discernible. Trajectory analysis can also be used for optimization of protocols of NMR structure calculation, by examining individual trajectories.Abbreviations MD molecular dynamics - MDS multidimensional scaling - rmsd root-mean-square deviation - armsd angular rmsd - R multiple correlation coefficient - YASAP yet another simulated annealing protocol - PCA principal component analysis     

Conjoined Use of EM and NMR in RNA Structure Refinement

More than 40% of the RNA structures have been determined using nuclear magnetic resonance (NMR) technique. NMR mainly provides local structural information of protons and works most effectively on relatively small biomacromolecules. Hence structural characterization of large RNAs can be difficult for NMR alone. Electron microscopy (EM) provides global shape information of macromolecules at nanometer resolution, which should be complementary to NMR for RNA structure determination. Here we developed a new energy term in Xplor-NIH against the density map obtained by EM. We conjointly used NMR and map restraints for the structure refinement of three RNA systems — U2/U6 small-nuclear RNA, genome-packing motif (Ψ^CD)₂ from Moloney murine leukemia virus, and ribosome-binding element from turnip crinkle virus. In all three systems, we showed that the incorporation of a map restraint, either experimental or generated from known PDB structure, greatly improves structural precision and accuracy. Importantly, our method does not rely on an initial model assembled from RNA duplexes, and allows full torsional freedom for each nucleotide in the torsion angle simulated annealing refinement. As increasing number of macromolecules can be characterized by both NMR and EM, the marriage between the two techniques would enable better characterization of RNA three-dimensional structures.     

生物大分子质谱电离技术的突破及核磁共振三维结构测定方法的建立——2002年诺贝尔化学奖简介

2002年诺贝尔化学奖授予了质谱和核磁共振领域的三位科学家以表彰他们对生物大分子鉴定及结构分析方法做出的贡献．其中两位科学家J．B．Fenn和K．Tanaka分别发展了生物大分子质谱分析的软解吸电离方法;另一科学家K．Wüthrich则将核磁共振技术成功地应用于生物大分子如蛋白质的溶液三维结构测定．他们的研究成果已使质谱和核磁共振技术成为生物大分子强有力的研究手段,极大地促进了生物大分子的研究进程,必将对整个生命科学研究产生深远的影响．     

Macromolecular NMR spectroscopy for the non-spectroscopist

NMR spectroscopy is a powerful tool for studying the structure, function and dynamics of biological macromolecules. However, non-spectroscopists often find NMR theory daunting and data interpretation nontrivial. As the first of two back-to-back reviews on NMR spectroscopy aimed at non-spectroscopists, the present review first provides an introduction to the basics of macromolecular NMR spectroscopy, including a discussion of typical sample requirements and what information can be obtained from simple NMR experiments. We then review the use of NMR spectroscopy for determining the 3D structures of macromolecules and examine how to judge the quality of NMR-derived structures.     

Structure and flexibility of individual immunoglobulin G molecules in solution

In contrast to averaging methods of determining structure, such as X-ray diffraction, NMR, and single-particle tomography, cryo-electron tomography allows three-dimensional imaging of an individual object in solution. The method has previously been used to study cells and very large macromolecules. We have used cryo-electron tomography to analyze a monoclonal IgG, with a molecular weight of only 150 kDa. Tomograms reveal y-shaped IgG molecules with three protruding subunits. Docking X-ray structures enabled us to recognize the three subunits as two ellipsoidal Fab arms and a heart-shaped Fc stem. Each subunit has a similar structure in the tomograms and in the X-ray map. Notably, the positions of the Fab arms relative to the Fc stem differed greatly from one molecule to another. The large flexibility of IgG in solution is most likely of functional significance in antigen recognition. This distribution of individual structures provides a qualitative insight into the system dynamics.     

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.     

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.     

Version 1.2 of the Crystallography and NMR system

Version 1.2 of the software system, termed Crystallography and NMR system (CNS), for crystallographic and NMR structure determination has been released. Since its first release, the goals of CNS have been (i) to create a flexible computational framework for exploration of new approaches to structure determination, (ii) to provide tools for structure solution of difficult or large structures, (iii) to develop models for analyzing structural and dynamical properties of macromolecules and (iv) to integrate all sources of information into all stages of the structure determination process. Version 1.2 includes an improved model for the treatment of disordered solvent for crystallographic refinement that employs a combined grid search and least-squares optimization of the bulk solvent model parameters. The method is more robust than previous implementations, especially at lower resolution, generally resulting in lower R values. Other advances include the ability to apply thermal factor sharpening to electron density maps. Consistent with the modular design of CNS, these additions and changes were implemented in the high-level computing language of CNS.     

From proteomic inventory to architecture

Electron tomography can provide three-dimensional reconstructions of large pleomorphic structures at molecular resolution. While the principles of electron tomography have been known for decades, its use has gathered momentum only in recent years. Technological advances have made it possible to apply it to ice-embedded biological material (cryotomography), thereby ensuring a close-to-life preservation of the samples. In combination with advanced computational methods, such as molecular identification based on pattern recognition, it is a promising approach to comprehensively map macromolecular architecture inside organelles and cells and to visualize macromolecules at work in their natural environment.     

Modeling nucleic acids

Nucleic acids are an important class of biological macromolecules that carry out a variety of cellular roles. For many functions, naturally occurring DNA and RNA molecules need to fold into precise three-dimensional structures. Due to their self-assembling characteristics, nucleic acids have also been widely studied in the field of nanotechnology, and a diverse range of intricate three-dimensional nanostructures have been designed and synthesized. Different physical terms such as base-pairing and stacking interactions, tertiary contacts, electrostatic interactions and entropy all affect nucleic acid folding and structure. Here we review general computational approaches developed to model nucleic acid systems. We focus on four key areas of nucleic acid modeling: molecular representation, potential energy function, degrees of freedom and sampling algorithm. Appropriate choices in each of these key areas in nucleic acid modeling can effectively combine to aid interpretation of experimental data and facilitate prediction of nucleic acid structure.     

NMR methodology for the study of nucleic acids.

During the past few years, NMR methodology for the study of nucleic acids has benefited from new developments that greatly improved state-of-the-art technology for the precise determination of three-dimensional structures. Substantial progress has been made in designing experimental protocols for the measurement of residual dipolar couplings, in sensitivity optimization of triple-resonance experiments and in detection of hydrogen bonds and in developing computational methods for structure refinement using NMR restraints.     

An assignment of intrinsically disordered regions of proteins based on NMR structures

Intrinsically disordered proteins (IDPs) do not adopt stable three-dimensional structures in physiological conditions, yet these proteins play crucial roles in biological phenomena. In most cases, intrinsic disorder manifests itself in segments or domains of an IDP, called intrinsically disordered regions (IDRs), but fully disordered IDPs also exist. Although IDRs can be detected as missing residues in protein structures determined by X-ray crystallography, no protocol has been developed to identify IDRs from structures obtained by Nuclear Magnetic Resonance (NMR). Here, we propose a computational method to assign IDRs based on NMR structures. We compared missing residues of X-ray structures with residue-wise deviations of NMR structures for identical proteins, and derived a threshold deviation that gives the best correlation of ordered and disordered regions of both structures. The obtained threshold of 3.2 Å was applied to proteins whose structures were only determined by NMR, and the resulting IDRs were analyzed and compared to those of X-ray structures with no NMR counterpart in terms of sequence length, IDR fraction, protein function, cellular location, and amino acid composition, all of which suggest distinct characteristics. The structural knowledge of IDPs is still inadequate compared with that of structured proteins. Our method can collect and utilize IDRs from structures determined by NMR, potentially enhancing the understanding of IDPs.     

Inference of Euler angles for single-particle analysis by means of evolutionary algorithms

Single-particle analysis is one of the methods for structural studies of protein and macromolecules; it requires advanced image analysis of electron micrographics. Reconstructing three-dimensional (3D) structure from microscope images is not an easy analysis because of the low image resolution of images and lack of the directional information of images in 3D structure. To improve the resolution, different projections are aligned, classified, and averaged. Inferring the orientations of these images is so difficult that the task of reconstructing 3D structures depends upon the experience of researchers. But recently, a method to reconstruct 3D structures was automatically devised. In this paper, we propose a new method for determining Euler angles of projections by applying genetic algorithms. We empirically show that the proposed approach has improved the previous one in terms of computational time and acquired precision.