Developments in x-ray crystallographic structure determination of biological macromolecules

Metal-Based Drug-DNA Interactions and Analytical Determination Methods

DNA structure has many potential places where endogenous compounds and xenobiotics can bind. Therefore, xenobiotics bind along the sites of the nucleic acid with the aim of changing its structure, its genetic message, and, implicitly, its functions. Currently, there are several mechanisms known to be involved in DNA binding. These mechanisms are covalent and non-covalent interactions. The covalent interaction or metal base coordination is an irreversible binding and it is represented by an intra-/interstrand cross-link. The non-covalent interaction is generally a reversible binding and it is represented by intercalation between DNA base pairs, insertion, major and/or minor groove binding, and electrostatic interactions with the sugar phosphate DNA backbone. In the present review, we focus on the types of DNA-metal complex interactions (including some representative examples) and on presenting the methods currently used to study them.

Single-Molecule Imaging of Integral Membrane Protein Dynamics and Function

Integral membrane proteins (IMPs) play central roles in cellular physiology and represent the majority of known drug targets. Single-molecule fluorescence and fluorescence resonance energy transfer (FRET) methods have recently emerged as valuable tools for investigating structure-function relationships in IMPs. This review focuses on the practical foundations required for examining polytopic IMP function using single-molecule FRET (smFRET) and provides an overview of the technical and conceptual frameworks emerging from this area of investigation. In this context, we highlight the utility of smFRET methods to reveal transient conformational states critical to IMP function and the use of smFRET data to guide structural and drug mechanism-of-action investigations. We also identify frontiers where progress is likely to be paramount to advancing the field.

A predicted model-aided reconstruction algorithm for X-ray free-electron laser single-particle imaging

Ultra-intense, ultra-fast X-ray free-electron lasers (XFELs) enable the imaging of single protein molecules under ambient temperature and pressure. A crucial aspect of structure reconstruction involves determining the relative orientations of each diffraction pattern and recovering the missing phase information. In this paper, we introduce a predicted model-aided algorithm for orientation determination and phase retrieval, which has been tested on various simulated datasets and has shown significant improvements in the success rate, accuracy and efficiency of XFEL data reconstruction.

Molecular Gas-Phase Conformational Ensembles

Accurately determining the global minima of a molecular structure is important in diverse scientific fields, including drug design, materials science, and chemical synthesis. Conformational search engines serve as valuable tools for exploring the extensive conformational space of molecules and for identifying energetically favorable conformations. In this study, we present a comparison of Auto3D, CREST, Balloon, and ETKDG (from RDKit), which are freely available conformational search engines, to evaluate their effectiveness in locating global minima. These engines employ distinct methodologies, including machine learning (ML) potential-based, semiempirical, and force field-based approaches. To validate these methods, we propose the use of collisional cross-section (CCS) values obtained from ion mobility-mass spectrometry studies. We hypothesize that experimental gas-phase CCS values can provide experimental evidence that we likely have the global minimum for a given molecule. To facilitate this effort, we used our gas-phase conformation library (GPCL) which currently consists of the full ensembles of 20 small molecules and can be used by the community to validate any conformational search engine. Further members of the GPCL can be readily created for any molecule of interest using our standard workflow used to compute CCS values, expanding the ability of the GPCL in validation exercises. These innovative validation techniques enhance our understanding of the conformational landscape and provide valuable insights into the performance of conformational generation engines. Our findings shed light on the strengths and limitations of each search engine, enabling informed decisions for their utilization in various scientific fields, where accurate molecular structure determination is crucial for understanding biological activity and designing targeted interventions. By facilitating the identification of reliable conformations, this study significantly contributes to enhancing the efficiency and accuracy of molecular structure determination, with particular focus on metabolite structure elucidation. The findings of this research also provide valuable insights for developing effective workflows for predicting the structures of unknown compounds with high precision.

One bead per residue can describe all-atom protein structures

Atomistic resolution is the standard for high-resolution biomolecular structures, but experimental structural data are often at lower resolution. Coarse-grained models are also used extensively in computational studies to reach biologically relevant spatial and temporal scales. This study explores the use of advanced machine learning networks for reconstructing atomistic models from reduced representations. The main finding is that a single bead per amino acid residue allows construction of accurate and stereochemically realistic all-atom structures with minimal loss of information. This suggests that lower resolution representations of proteins may be sufficient for many applications when combined with a machine learning framework that encodes knowledge from known structures. Practical applications include the rapid addition of atomistic detail to low-resolution structures from experiment or computational coarse-grained models. The application of rapid, deterministic all-atom reconstruction within multi-scale frameworks is further demonstrated with a rapid protocol for the generation of accurate models from cryo-EM densities close to experimental structures.

Aptamer-Protein Interactions: From Regulation to Biomolecular Detection

Serving as the basis of cell life, interactions between nucleic acids and proteins play essential roles in fundamental cellular processes. Aptamers are unique single-stranded oligonucleotides generated by in vitro evolution methods, possessing the ability to interact with proteins specifically. Altering the structure of aptamers will largely modulate their interactions with proteins and further affect related cellular behaviors. Recently, with the in-depth research of aptamer-protein interactions, the analytical assays based on their interactions have been widely developed and become a powerful tool for biomolecular detection. There are some insightful reviews on aptamers applied in protein detection, while few systematic discussions are from the perspective of regulating aptamer-protein interactions. Herein, we comprehensively introduce the methods for regulating aptamer-protein interactions and elaborate on the detection techniques for analyzing aptamer-protein interactions. Additionally, this review provides a broad summary of analytical assays based on the regulation of aptamer-protein interactions for detecting biomolecules. Finally, we present our perspectives regarding the opportunities and challenges of analytical assays for biological analysis, aiming to provide guidance for disease mechanism research and drug discovery.

X-ray driven and intrinsic dynamics in protein gels

We use X-ray photon correlation spectroscopy to investigate how structure and dynamics of egg white protein gels are affected by X-ray dose and dose rate. We find that both, changes in structure and beam-induced dynamics, depend on the viscoelastic properties of the gels with soft gels prepared at low temperatures being more sensitive to beam-induced effects. Soft gels can be fluidized by X-ray doses of a few kGy with a crossover from stress relaxation dynamics (Kohlrausch-Williams-Watts exponents [Formula: see text] to 2) to typical dynamical heterogeneous behavior ([Formula: see text]1) while the high temperature egg white gels are radiation-stable up to doses of 15 kGy with [Formula: see text]. For all gel samples we observe a crossover from equilibrium dynamics to beam induced motion upon increasing X-ray fluence and determine the resulting fluence threshold values [Formula: see text]. Surprisingly small threshold values of [Formula: see text] s[Formula: see text] nm[Formula: see text] can drive the dynamics in the soft gels while for stronger gels this threshold is increased to [Formula: see text] s[Formula: see text] nm[Formula: see text]. We explain our observations with the viscoelastic properties of the materials and can connect the threshold dose for structural beam damage with the dynamic properties of beam-induced motion. Our results suggest that soft viscoelastic materials can display pronounced X-ray driven motion even for low X-ray fluences. This induced motion is not detectable by static scattering as it appears at dose values well below the static damage threshold. We show that intrinsic sample dynamics can be separated from X-ray driven motion by measuring the fluence dependence of the dynamical properties.

Assessments of Variational Autoencoder in Protein Conformation Exploration

Molecular dynamics (MD) simulations have been extensively used to study protein dynamics and subsequently functions. However, MD simulations are often insufficient to explore adequate conformational space for protein functions within reachable timescales. Accordingly, many enhanced sampling methods, including variational autoencoder (VAE) based methods, have been developed to address this issue. The purpose of this study is to evaluate the feasibility of using VAE to assist in the exploration of protein conformational landscapes. Using three modeling systems, we showed that VAE could capture high-level hidden information which distinguishes protein conformations. These models could also be used to generate new physically plausible protein conformations for direct sampling in favorable conformational spaces. We also found that VAE worked better in interpolation than extrapolation and increasing latent space dimension could lead to a trade-off between performances and complexities.

Efficient Interrogation of the Kinetic Barriers Demarcating Catalytic States of a Tyrosine Kinase with Optimal Physical Descriptors and Mixture Models

Computer simulations are increasingly used to access thermo-kinetic information underlying structural transformation of protein kinases. Such information are necessary to probe their roles in disease progression and interactions with drug targets. However, the investigations are frequently challenged by forbiddingly high computational expense, and by the lack of standard protocols for the design of low dimensional physical descriptors that encode system features important for transitions. Here, we consider the demarcating characteristics of the different states of Abelson tyrosine kinase associated with distinct catalytic activity to construct a set of physically meaningful, orthogonal collective variables that preserve the slow modes of the system. Independent sampling of each metastable state is followed by the estimation of global partition function along the appropriate physical descriptors using the modified Expectation Maximized Molecular Dynamics method. The resultant free energy barriers are in excellent agreement with experimentally known rate-limiting dynamics and activation energy computed with conventional enhanced sampling methods. We discuss possible directions for further development and applications.

Smart de novo Macromolecular Structure Modeling from Cryo-EM Maps

The study of macromolecular structures has expanded our understanding of the amazing cell machinery and such knowledge has changed how the pharmaceutical industry develops new vaccines in recent years. Traditionally, X-ray crystallography has been the main method for structure determination, however, cryogenic electron microscopy (cryo-EM) has increasingly become more popular due to recent advancements in hardware and software. The number of cryo-EM maps deposited in the EMDataResource (formerly EMDatabase) since 2002 has been dramatically increasing and it continues to do so. De novo macromolecular complex modeling is a labor-intensive process, therefore, it is highly desirable to develop software that can automate this process. Here we discuss our automated, data-driven, and artificial intelligence approaches including map processing, feature extraction, modeling building, and target identification. Recently, we have enabled DNA/RNA modeling in our deep learning-based prediction tool, DeepTracer. We have also developed DeepTracer-ID, a tool that can identify proteins solely based on the cryo-EM map. In this paper, we will present our accumulated experiences in developing deep learning-based methods surrounding macromolecule modeling applications.

Epitope mapping of monoclonal antibodies: a comprehensive comparison of different technologies

Monoclonal antibodies have become an important class of therapeutics in the last 30 years. Because the mechanism of action of therapeutic antibodies is intimately linked to their binding epitopes, identification of the epitope of an antibody to the antigen plays a central role during antibody drug development. The gold standard of epitope mapping, X-ray crystallography, requires a high degree of proficiency with no guarantee of success. Here, we evaluated six widely used alternative methods for epitope identification (peptide array, alanine scan, domain exchange, hydrogen-deuterium exchange, chemical cross-linking, and hydroxyl radical footprinting) in five antibody-antigen combinations (pembrolizumab+PD1, nivolumab+PD1, ipilimumab+CTLA4, tremelimumab+CTLA4, and MK-5890+CD27). The advantages and disadvantages of each technique are demonstrated by our data and practical advice on when and how to apply specific epitope mapping techniques during the drug development process is provided. Our results suggest chemical cross-linking most accurately identifies the epitope as defined by crystallography.

Quantitative Cryo-Electron Tomography

The three-dimensional organization of biomolecules important for the functioning of all living systems can be determined by cryo-electron tomography imaging under native biological contexts. Cryo-electron tomography is continually expanding and evolving, and the development of new methods that use the latest technology for sample thinning is enabling the visualization of ever larger and more complex biological systems, allowing imaging across scales. Quantitative cryo-electron tomography possesses the capability of visualizing the impact of molecular and environmental perturbations in subcellular structure and function to understand fundamental biological processes. This review provides an overview of current hardware and software developments that allow quantitative cryo-electron tomography studies and their limitations and how overcoming them may allow us to unleash the full power of cryo-electron tomography.

Recent advances in RNA structurome

RNA structures are essential to support RNA functions and regulation in various biological processes. Recently, a range of novel technologies have been developed to decode genome-wide RNA structures and novel modes of functionality across a wide range of species. In this review, we summarize key strategies for probing the RNA structurome and discuss the pros and cons of representative technologies. In particular, these new technologies have been applied to dissect the structural landscape of the SARS-CoV-2 RNA genome. We also summarize the functionalities of RNA structures discovered in different regulatory layers-including RNA processing, transport, localization, and mRNA translation-across viruses, bacteria, animals, and plants. We review many versatile RNA structural elements in the context of different physiological and pathological processes (e.g., cell differentiation, stress response, and viral replication). Finally, we discuss future prospects for RNA structural studies to map the RNA structurome at higher resolution and at the single-molecule and single-cell level, and to decipher novel modes of RNA structures and functions for innovative applications.

Near-native state imaging by cryo-soft-X-ray tomography reveals remodelling of multiple cellular organelles during HSV-1 infection

Herpes simplex virus-1 (HSV-1) is a large, enveloped DNA virus and its assembly in the cell is a complex multi-step process during which viral particles interact with numerous cellular compartments such as the nucleus and organelles of the secretory pathway. Transmission electron microscopy and fluorescence microscopy are commonly used to study HSV-1 infection. However, 2D imaging limits our understanding of the 3D geometric changes to cellular compartments that accompany infection and sample processing can introduce morphological artefacts that complicate interpretation. In this study, we used soft X-ray tomography to observe differences in whole-cell architecture between HSV-1 infected and uninfected cells. To protect the near-native structure of cellular compartments we used a non-disruptive sample preparation technique involving rapid cryopreservation, and a fluorescent reporter virus was used to facilitate correlation of structural changes with the stage of infection in individual cells. We observed viral capsids and assembly intermediates interacting with nuclear and cytoplasmic membranes. Additionally, we observed differences in the morphology of specific organelles between uninfected and infected cells. The local concentration of cytoplasmic vesicles at the juxtanuclear compartment increased and their mean width decreased as infection proceeded, and lipid droplets transiently increased in size. Furthermore, mitochondria in infected cells were elongated and highly branched, suggesting that HSV-1 infection alters the dynamics of mitochondrial fission/fusion. Our results demonstrate that high-resolution 3D images of cellular compartments can be captured in a near-native state using soft X-ray tomography and have revealed that infection causes striking changes to the morphology of intracellular organelles.

Contour, a semi-automated segmentation and quantitation tool for cryo-soft-X-ray tomography

Cryo-soft-X-ray tomography is being increasingly used in biological research to study the morphology of cellular compartments and how they change in response to different stimuli, such as viral infections. Segmentation of these compartments is limited by time-consuming manual tools or machine learning algorithms that require extensive time and effort to train. Here we describe Contour, a new, easy-to-use, highly automated segmentation tool that enables accelerated segmentation of tomograms to delineate distinct cellular compartments. Using Contour, cellular structures can be segmented based on their projection intensity and geometrical width by applying a threshold range to the image and excluding noise smaller in width than the cellular compartments of interest. This method is less laborious and less prone to errors from human judgement than current tools that require features to be manually traced, and does not require training datasets as would machine-learning driven segmentation. We show that high-contrast compartments such as mitochondria, lipid droplets, and features at the cell surface can be easily segmented with this technique in the context of investigating herpes simplex virus 1 infection. Contour can extract geometric measurements from 3D segmented volumes, providing a new method to quantitate cryo-soft-X-ray tomography data. Contour can be freely downloaded at github.com/kamallouisnahas/Contour.

3D-printed equipment to decouple (powder) X-ray diffraction sample preparation and measurement

An alternative storage method to separate sample preparation from single-crystal and powder X-ray diffraction measurements at home source diffractometers is described. For single crystals, a setup is presented which allows storage of preselected crystals under cryogenic and ambient temperatures. For powders, a disposable sample holder is introduced. The method is suitable for the storage of air- and moisture-sensitive samples. Equipment made of biodegradable polylactic acid is produced by 3D printing and can be adapted to individual needs. As 3D printers are widely available at research institutions nowadays, models of the presented equipment are provided for the reader to allow easy reproduction.

Importance of Nuclear Quantum Effects for Molecular Cocrystals with Short Hydrogen Bonds

Many efforts have been recently devoted to the design and investigation of multicomponent pharmaceutical solids, such as salts and cocrystals. The experimental distinction between these solid forms is often challenging. Here, we show that the transformation of a salt into a cocrystal with a short hydrogen bond does not occur as a sharp phase transition but rather a smooth shift of the positional probability of the hydrogen atoms. A combination of solid-state NMR spectroscopy, X-ray diffraction, and diffuse reflectance measurements with density functional theory calculations that include nuclear quantum effects (NQEs) provides evidence of temperature-induced hydrogen atom shift in cocrystals with short hydrogen bonds. We demonstrate that for the predictions of the salt/cocrystal solid forms with short H-bonds, the computations have to include NQEs (particularly hydrogen nuclei delocalization) and temperature effects.

Structural validation and assessment of AlphaFold2 predictions for centrosomal and centriolar proteins and their complexes

Obtaining the high-resolution structures of proteins and their complexes is a crucial aspect of understanding the mechanisms of life. Experimental structure determination methods are time-consuming, expensive and cannot keep pace with the growing number of protein sequences available through genomic DNA sequencing. Thus, the ability to accurately predict the structure of proteins from their sequence is a holy grail of structural and computational biology that would remove a bottleneck in our efforts to understand as well as rationally engineer living systems. Recent advances in protein structure prediction, in particular the breakthrough with the AI-based tool AlphaFold2 (AF2), hold promise for achieving this goal, but the practical utility of AF2 remains to be explored. Focusing on proteins with essential roles in centrosome and centriole biogenesis, we demonstrate the quality and usability of the AF2 prediction models and we show that they can provide important insights into the modular organization of two key players in this process, CEP192 and CEP44. Furthermore, we used the AF2 algorithm to elucidate and then experimentally validate previously unknown prime features in the structure of TTBK2 bound to CEP164, as well as the Chibby1-FAM92A complex for which no structural information was available to date. These findings have important implications in understanding the regulation and function of these complexes. Finally, we also discuss some practical limitations of AF2 and anticipate the implications for future research approaches in the centriole/centrosome field.

Macrocyclic Tetramers-Structural Investigation of Peptide-Peptoid Hybrids

Outstanding affinity and specificity are the main characteristics of peptides, rendering them interesting compounds for basic and medicinal research. However, their biological applicability is limited due to fast proteolytic degradation. The use of mimetic peptoids overcomes this disadvantage, though they lack stereochemical information at the α-carbon. Hybrids composed of amino acids and peptoid monomers combine the unique properties of both parent classes. Rigidification of the backbone increases the affinity towards various targets. However, only little is known about the spatial structure of such constrained hybrids. The determination of the three-dimensional structure is a key step for the identification of new targets as well as the rational design of bioactive compounds. Herein, we report the synthesis and the structural elucidation of novel tetrameric macrocycles. Measurements were taken in solid and solution states with the help of X-ray scattering and NMR spectroscopy. The investigations made will help to find diverse applications for this new, promising compound class.

Analyzing Discrepancies in Chemical-Shift Predictions of Solid Pyridinium Fumarates

Highly accurate chemical-shift predictions in molecular solids are behind the success and rapid development of NMR crystallography. However, unusually large errors of predicted hydrogen and carbon chemical shifts are sometimes reported. An understanding of these deviations is crucial for the reliability of NMR crystallography. Here, recently reported large deviations of predicted hydrogen and carbon chemical shifts of a series of solid pyridinium fumarates are thoroughly analyzed. The influence of the geometry optimization protocol and of the computational level of NMR calculations on the accuracy of predicted chemical shifts is investigated. Periodic calculations with GGA, meta-GGA and hybrid functionals are employed. Furthermore, molecular corrections at the coupled-cluster singles-and-doubles (CCSD) level are calculated. The effect of nuclear delocalization on the structure and NMR shielding is also investigated. The geometry optimization with a computationally demanding hybrid functional leads to a substantial improvement in proton chemical-shift predictions.

Features and futures of X-ray free-electron lasers

Linear accelerator-based free-electron lasers (FELs) are the leading source of fully coherent X-rays with ultra-high peak powers and ultra-short pulse lengths. Current X-ray FEL facilities have proved their worth as useful tools for diverse scientific applications. In this paper, we present an overview of the features and future prospects of X-ray FELs, including the working principles and properties of X-ray FELs, the operational status of different FEL facilities worldwide, the applications supported by such facilities, and the current developments and outlook for X-ray FEL-based research.

X-ray fan beam coded aperture transmission and diffraction imaging for fast material analysis

X-ray transmission imaging has been used in a variety of applications for high-resolution measurements based on shape and density. Similarly, X-ray diffraction (XRD) imaging has been used widely for molecular structure-based identification of materials. Combining these X-ray methods has the potential to provide high-resolution material identification, exceeding the capabilities of either modality alone. However, XRD imaging methods have been limited in application by their long measurement times and poor spatial resolution, which has generally precluded combined, rapid measurements of X-ray transmission and diffraction. In this work, we present a novel X-ray fan beam coded aperture transmission and diffraction imaging system, developed using commercially available components, for rapid and accurate non-destructive imaging of industrial and biomedical specimens. The imaging system uses a 160 kV Bremsstrahlung X-ray source while achieving a spatial resolution of ≈ 1 × 1 mm² and a spectral accuracy of > 95% with only 15 s exposures per 150 mm fan beam slice. Applications of this technology are reported in geological imaging, pharmaceutical inspection, and medical diagnosis. The performance of the imaging system indicates improved material differentiation relative to transmission imaging alone at scan times suitable for a variety of industrial and biomedical applications.

Optimized High-Yield Purification of Obesity-Associated Melanocortin 4 Receptor

BACKGROUND

Obesity has emerged as a global public health challenge associated with increased risk of hyperlipidemia and hypertension. It contributes to high sympathetic activity and increased catecholamine levels. The hypothalamic melanocortin system is known to regulate the energy homeostasis. The role of melanocortin 4 receptor (MC4R) has been demonstrated pharmacologically and in animal studies, which showed that severe obesity in MC4R knockout mice was caused by increased food intake and decreased energy consumption. Over 70 multiple different mis- -sense and nonsense mutations in hMC4R have been found at a high frequency of 2-8% in severe early onset or hereditary obesity. The single amino acid variation (D90N) located in the second transmembrane domain (TM2) of MC4R results in accelerated growth and childhood onset obesity. Interestingly, the functional characterization of D90N hMC4R mutant TM2 (m-hMC4R-TM2) revealed normal cell surface expression and binding with agonist similar to the hMC4R wild-type TM2 (wt-hMC4R-TM2) but loss of signal transduction mediated via Gs/adenylyl cyclase activation. It is essential to delineate the three-dimensional structure of MC4Rs in order to elucidate their functional aspects.

OBJECTIVE

In this study, we demonstrate the optimized expression and isolation of wt/m-hMC4R-TM2 proteins under different chemical cleavage reaction times and purification procedures via SDS precipitation. The solid-state NMR spectroscopy was carried out to study the structure of wt/m-hMC4R- TM2 protein in the anisotropic phospholipid bicelles.

METHODS

The KSI-wt/m-hMC4R-TM2 fusion proteins developed in cell culture with LB medium. In order to isolate the expressed fusion protein from the cell, ultrasonication, Ni-NTA affinity chromatography, dialysis, and lyophilization techniques were used. Then, to obtain a protein with higher purity and higher yield, the CNBr chemical cleavage time was subdivided into 30 minutes, 1 h, 2 h, 3 h, and 4 h. Purification process was performed using FPLC, and 100 mM KCl and dialysis were used to remove the SDS. CD spectrometer, MALDI-TOF, solution-state NMR, and solid-state NMR were used to confirmed purity and structure of the wt/m-hMC4R-TM2.

RESULTS

The precipitation method was used to remove the SDS bound to proteins as KCl-SDS. We optimized the 2 h cleavage reaction times for both wt-hMC4R-TM2 and m-hMC4R-TM2 depending on the purity based on mass spectra and ¹H-¹⁵N HSQC spectra and the yield after final purification. The 1D ¹H-¹⁵N CP (Cross polarization) solid-state NMR spectra suggest that the wt/m-hMC4R- TM2 undergo rotational diffusion around a perpendicular axis along the bilayer normal.

CONCLUSION

We expressed wt/m-hMC4R-TM2 in E.coli and optimized the isolation and purification process, especially CNBr chemical cleavage time. The efficiency of KCl-SDS precipitation was confirmed via MALDI-TOF MS and the pure proteins obtained using this method were characterized by CD spectroscopy and solution-state NMR. The results of ¹H-¹⁵N HSQC spectra in solution- state NMR also show the probability for structural studies. The 1D ¹H-¹⁵N CP solid-state NMR spectra indicate that most of the residues in both the wt/m-hMC4R-TM2 peptides are integrated into the membrane.

Crosslinking mass spectrometry: A link between structural biology and systems biology

Protein structure underpins functional roles in all biological processes; therefore, improved understanding of protein structures is of fundamental importance in nearly all biological and biomedical research areas. Traditional techniques such as X-ray crystallography and more recently, cryo-EM, can reveal structural features on isolated proteins/protein complexes at atomic resolution level and have become indispensable tools for structural biology. Crosslinking mass spectrometry (XL-MS), on the other hand, is an emerging technique capable of capturing transient and dynamic information on protein interactions and assemblies in their native environment. The combination of XL-MS with traditional techniques holds potential for bridging the gap between structural biology and systems biology approaches. Such a combination will enable visualization of protein structures and interactions within the crowded macromolecular environment in living systems that can dramatically increase understanding of biological functions. In this review, we first discuss general strategies of XL-MS and then survey recent examples to show how qualitative and quantitative XL-MS studies can be integrated with available protein structural data to better understand biological function at systems level.

Influenza Hemagglutinin Structures and Antibody Recognition

Hemagglutinin (HA) is most abundant glycoprotein on the influenza virus surface. Influenza HA promotes viral entry by engaging the receptor and mediating virus-host membrane fusion. At the same time, HA is the major antigen of the influenza virus. HA antigenic shift can result in pandemics, whereas antigenic drift allows human circulating strains to escape herd immunity. Most antibody responses against HA are strain-specific. However, antibodies that have neutralizing activities against multiple strains or even subtypes have now been discovered and characterized. These broadly neutralizing antibodies (bnAbs) target conserved regions on HA, such as the receptor-binding site and the stem domain. Structural studies of such bnAbs have provided important insight into universal influenza vaccine and therapeutic design. This review discusses the HA functions as well as HA-antibody interactions from a structural perspective.

A Searchable Database of Crystallization Cocktails in the PDB: Analyzing the Chemical Condition Space

Nearly 90% of structural models in the Protein Data Bank (PDB), the central resource worldwide for three-dimensional structural information, are currently derived from macromolecular crystallography (MX). A major bottleneck in determining MX structures is finding conditions in which a biomolecule will crystallize. Here, we present a searchable database of the chemicals associated with successful crystallization experiments from the PDB. We use these data to examine the relationship between protein secondary structure and average molecular weight of polyethylene glycol and to investigate patterns in crystallization conditions. Our analyses reveal striking patterns of both redundancy of chemical compositions in crystallization experiments and extreme sparsity of specific chemical combinations, underscoring the challenges faced in generating predictive models for de novo optimal crystallization experiments.

Direct Detection of Lysozyme in Viscous Raw Hen Egg White Binding to Sodium Dodecyl Sulfonate by Reactive Wooden-tip Electrospray Ionization Mass Spectrometry

Direct characterization of native protein binding to ligands in raw biological samples is a challenging task, because the ligand solution might induce proteins to aggregation, flocculation and denaturation. In this work, we developed a reactive wooden-tip electrospray ionization mass spectrometry (ESI-MS) for formation and characterization of protein-ligand complexes upon rapid mixing in electrospray droplets. Raw viscous hen egg white (HEW) was directly loaded onto a wooden tip to induce spray ionization, and sodium dodecyl sulfonate (SDS) solution was directly loaded into the HEW spray by a pipette tip, and thus lysozyme-DS complexes were then formed in the electrospray droplets and were detected subsequently by mass spectrometry. The new approach was successfully applied to investigate interaction of SDS and native lysozyme in electrospray droplets of standard solution and raw egg white. Our results showed that wooden-tip ESI-MS is a promising method to form and characterize protein-ligand complexes.

The early history of cryo-cooling for macromolecular crystallography

This paper recounts the first successful cryo-cooling of protein crystals that demonstrated the reduction in X-ray damage to macromolecular crystals. The project was suggested by David C. Phillips in 1965 at the Royal Institution of Great Britain and continued in 1967 at the Weizmann Institute of Science, where the first cryo-cooling experiments were performed on lysozyme crystals, and was completed in 1969 at Purdue University on lactate dehydrogenase crystals. A 1970 publication in Acta Crystallographica described the cryo-procedures, the use of cryo-protectants to prevent ice formation, the importance of fast, isotropic cryo-cooling and the collection of analytical data showing more than a tenfold decrease in radiation damage in cryo-cooled lactate dehydrogenase crystals. This was the first demonstration of any method that reduced radiation damage in protein crystals, which provided crystallographers with suitable means to employ synchrotron X-ray sources for protein-crystal analysis. Today, fifty years later, more than 90% of the crystal structures deposited in the Protein Data Bank have been cryo-cooled.

High-throughput quantitative top-down proteomics

Top-down mass spectrometry (MS) analyzes intact proteins at the proteoform level, which allows researchers to better understand the functions of protein modifications. Recently, top-down proteomics has increased in popularity due to advancements in high-resolution mass spectrometers, increased efficiency in liquid chromatography (LC) separation, and advances in data analysis software. Some unique protein proteoforms, which have been distinguished using top-down MS, have even been shown to exhibit marked variation in biological function compared to similar proteoforms. However, the qualitative identification of a particular proteoform may not be enough to determine the biological relevance of that proteoform. Quantitative top-down MS methods have been notably applied to the study of the differing biological functions of protein proteoforms and have allowed researchers to explore proteomes at the proteoform, rather than the peptide, level. Here, we review the top-down MS methods that have been used to quantitatively identify intact proteins, discuss current applications of quantitative top-down MS analysis, and present new areas where quantitative top-down MS analysis may be implemented.

Liquid-phase electron microscopy imaging of cellular and biomolecular systems

Liquid-phase electron microscopy, a new method for real-time nanoscopic imaging in liquid, makes it possible to study cells or biomolecules with a singular combination of spatial and temporal resolution. We review the state of the art in biological research in this growing and promising field.

Synchrotron microcrystal native-SAD phasing at a low energy

De novo structural evaluation of native biomolecules from single-wavelength anomalous diffraction (SAD) is a challenge because of the weakness of the anomalous scattering. The anomalous scattering from relevant native elements - primarily sulfur in proteins and phospho-rus in nucleic acids - increases as the X-ray energy decreases toward their K-edge transitions. Thus, measurements at a lowered X-ray energy are promising for making native SAD routine and robust. For microcrystals with sizes less than 10 µm, native-SAD phasing at synchrotron microdiffraction beamlines is even more challenging because of difficulties in sample manipulation, diffraction data collection and data analysis. Native-SAD analysis from microcrystals by using X-ray free-electron lasers has been demonstrated but has required use of thousands of thousands of microcrystals to achieve the necessary accuracy. Here it is shown that by exploitation of anomalous microdiffraction signals obtained at 5 keV, by the use of polyimide wellmounts, and by an iterative crystal and frame-rejection method, microcrystal native-SAD phasing is possible from as few as about 1 200 crystals. Our results show the utility of low-energy native-SAD phasing with microcrystals at synchrotron microdiffraction beamlines.

X-Ray Free-Electron Lasers for the Structure and Dynamics of Macromolecules

X-ray free-electron lasers provide femtosecond-duration pulses of hard X-rays with a peak brightness approximately one billion times greater than is available at synchrotron radiation facilities. One motivation for the development of such X-ray sources was the proposal to obtain structures of macromolecules, macromolecular complexes, and virus particles, without the need for crystallization, through diffraction measurements of single noncrystalline objects. Initial explorations of this idea and of outrunning radiation damage with femtosecond pulses led to the development of serial crystallography and the ability to obtain high-resolution structures of small crystals without the need for cryogenic cooling. This technique allows the understanding of conformational dynamics and enzymatics and the resolution of intermediate states in reactions over timescales of 100 fs to minutes. The promise of more photons per atom recorded in a diffraction pattern than electrons per atom contributing to an electron micrograph may enable diffraction measurements of single molecules, although challenges remain.

Ab Initio Fragment Method for Calculating Molecular X-ray Diffraction

A fragment-based approach for the prediction of elastic X-ray scattering is presented. The total diffraction pattern is assembled from anisotropic form factors calculated for individual molecular fragments, optionally including corrections for pairwise interactions between fragments. The approach is evaluated against full ab initio scattering calculations in the peptide diphenylalanine, and the optimal selection of fragments is examined in the ethanol molecule. The approach is found to improve significantly on the independent atom model while remaining conceptually simple and computationally efficient. It is expected to be particularly useful for macromolecules with repeated subunits, such as peptides, proteins, DNA, or RNA and other polymers, where it is straightforward to define appropriate fragments.

Molecular methods for assessment of non-covalent metallodrug-DNA interactions

The binding of small molecule metallodrugs to discrete regions of nucleic acids is an important branch of medicinal chemistry and the nature of these interactions, allied with sequence selectivity, forms part of the backbone of modern medicinal inorganic chemistry research. In this tutorial review we describe a range of molecular methods currently employed within our laboratories to explore novel metallodrug-DNA interactions. At the outset, an introduction to DNA from a structural perspective is provided along with descriptions of non-covalent DNA recognition focusing on intercalation, insertion, and phosphate binding. Molecular methods, described from a non-expert perspective, to identify non-covalent and pre-associative nucleic acid recognition are then demonstrated using a variety of techniques including direct (non-optical) and indirect (optical) methods. Direct methods include: X-ray crystallography; NMR spectroscopy; mass spectrometry; and viscosity while indirect approaches detail: competitive inhibition experiments; fluorescence and absorbance spectroscopy; circular dichroism; and electrophoresis-based techniques. For each method described we provide an overview of the technique, a detailed examination of results obtained and relevant follow-on of advanced biophysical/analytical techniques. To achieve this, a selection of relevant copper(ii) and platinum(ii) complexes developed within our laboratories are discussed and are compared, where possible, to classical DNA binding agents. Applying these molecular methods enables us to determine structure-activity factors important to rational metallodrug design. In many cases, combinations of molecular methods are required to comprehensively elucidate new metallodrug-DNA interactions and, from a drug discovery perspective, coupling this data with cellular responses helps to inform understanding of how metallodrug-DNA binding interactions manifest cytotoxic action.

Bioinformatics Tools and Benchmarks for Computational Docking and 3D Structure Prediction of RNA-Protein Complexes

RNA-protein (RNP) interactions play essential roles in many biological processes, such as regulation of co-transcriptional and post-transcriptional gene expression, RNA splicing, transport, storage and stabilization, as well as protein synthesis. An increasing number of RNP structures would aid in a better understanding of these processes. However, due to the technical difficulties associated with experimental determination of macromolecular structures by high-resolution methods, studies on RNP recognition and complex formation present significant challenges. As an alternative, computational prediction of RNP interactions can be carried out. Structural models obtained by theoretical predictive methods are, in general, less reliable compared to models based on experimental measurements but they can be sufficiently accurate to be used as a basis for to formulating functional hypotheses. In this article, we present an overview of computational methods for 3D structure prediction of RNP complexes. We discuss currently available methods for macromolecular docking and for scoring 3D structural models of RNP complexes in particular. Additionally, we also review benchmarks that have been developed to assess the accuracy of these methods.

A pipeline for computational design of novel RNA-like topologies

Designing novel RNA topologies is a challenge, with important therapeutic and industrial applications. We describe a computational pipeline for design of novel RNA topologies based on our coarse-grained RNA-As-Graphs (RAG) framework. RAG represents RNA structures as tree graphs and describes RNA secondary (2D) structure topologies (currently up to 13 vertices, ≈260 nucleotides). We have previously identified novel graph topologies that are RNA-like among these. Here we describe a systematic design pipeline and illustrate design for six broad design problems using recently developed tools for graph-partitioning and fragment assembly (F-RAG). Following partitioning of the target graph, corresponding atomic fragments from our RAG-3D database are combined using F-RAG, and the candidate atomic models are scored using a knowledge-based potential developed for 3D structure prediction. The sequences of the top scoring models are screened further using available tools for 2D structure prediction. The results indicate that our modular approach based on RNA-like topologies rather than specific 2D structures allows for greater flexibility in the design process, and generates a large number of candidate sequences quickly. Experimental structure probing using SHAPE-MaP for two sequences agree with our predictions and suggest that our combined tools yield excellent candidates for further sequence and experimental screening.

High-throughput in situ X-ray screening of and data collection from protein crystals at room temperature and under cryogenic conditions

Protein crystallography has significantly advanced in recent years, with in situ data collection, in which crystals are placed in the X-ray beam within their growth medium, being a major point of focus. In situ methods eliminate the need to harvest crystals, a previously unavoidable drawback, particularly for often small membrane-protein crystals. Here, we present a protocol for the high-throughput in situ X-ray screening of and data collection from soluble and membrane-protein crystals at room temperature (20-25°C) and under cryogenic conditions. The Mylar in situ method uses Mylar-based film sandwich plates that are inexpensive, easy to make, and compatible with automated imaging, and that show very low background scattering. They support crystallization in microbatch and vapor-diffusion modes, as well as in lipidic cubic phases (LCPs). A set of 3D-printed holders for differently sized patches of Mylar sandwich films makes the method robust and versatile, allows for storage and shipping of crystals, and enables automated mounting at synchrotrons, as well as goniometer-based screening and data collection. The protocol covers preparation of in situ plates and setup of crystallization trials; 3D printing and assembly of holders; opening of plates, isolation of film patches containing crystals, and loading them onto holders; basic screening and data-collection guidelines; and unloading of holders, as well as reuse and recycling of them. In situ plates are prepared and assembled in 1 h; holders are 3D-printed and assembled in ≤90 min; and an in situ plate is opened, and a film patch containing crystals is isolated and loaded onto a holder in 5 min.

Hybrid Methods for Macromolecular Modeling by Molecular Mechanics Simulations with Experimental Data

Hybrid approaches for the modeling of macromolecular complexes that combine computational molecular mechanics simulations with experimental data are discussed. Experimental data for biological molecular structures are often low-resolution, and thus, do not contain enough information to determine the atomic positions of molecules. This is especially true when the dynamics of large macromolecules are the focus of the study. However, computational modeling can complement missing information. Significant increase in computational power, as well as the development of new modeling algorithms allow us to model structures of biological macromolecules reliably, using experimental data as references. We review the basics of molecular mechanics approaches, such as atomic model force field, and coarse-grained models, molecular dynamics simulation and normal mode analysis and describe how they could be used for flexible fitting hybrid modeling with experimental data, especially from cryo-EM and SAXS.

Magnetically textured powders—an alternative to single-crystal and powder X-ray diffraction methods

Structure determination of materials in their crystalline phase aids in the understanding and design of their functions.

Locking the Elbow: Improved Antibody Fab Fragments as Chaperones for Structure Determination

Antibody Fab fragments have been exploited with significant success to facilitate the structure determination of challenging macromolecules as crystallization chaperones and as molecular fiducial marks for single particle cryo-electron microscopy approaches. However, the inherent flexibility of the "elbow" regions, which link the constant and variable domains of the Fab, can introduce disorder and thus diminish their effectiveness. We have developed a phage display engineering strategy to generate synthetic Fab variants that significantly reduces elbow flexibility, while maintaining their high affinity and stability. This strategy was validated using previously recalcitrant Fab-antigen complexes where introduction of an engineered elbow region enhanced crystallization and diffraction resolution. Furthermore, incorporation of the mutations appears to be generally portable to other synthetic antibodies and may serve as a universal strategy to enhance the success rates of Fabs as structure determination chaperones.

A component analysis of the free energies of folding of 35 proteins: A consensus view on the thermodynamics of folding at the molecular level

What factors favor protein folding? This is a textbook question. Parsing the experimental free energies of folding/unfolding into diverse enthalpic and entropic components of solute and solvent favoring or disfavoring folding is not an easy task. In this study, we present a computational protocol for estimating the free energy contributors to protein folding semi-quantitatively using ensembles of unfolded and native states generated via molecular dynamics simulations. We tested the methodology on 35 proteins with diverse structural motifs and sizes and found that the calculated free energies correlate well with experiment (correlation coefficient ∼ 0.85), enabling us to develop a consensus view of the energetics of folding. As a more sensitive test of the methodology, we also investigated the free energies of folding of an additional 33 single point mutants and obtained a correlation coefficient of 0.8. A notable observation is that the folding free energy components appear to carry signatures of the fold (SCOP classification) of the protein. © 2017 Wiley Periodicals, Inc.