Three-dimensional Macromolecular Structures Research Articles

CCP4 Cloud for structure determination and project management in macromolecular crystallography.

Nowadays, progress in the determination of three-dimensional macromolecular structures from diffraction images is achieved partly at the cost of increasing data volumes. This is due to the deployment of modern high-speed, high-resolution detectors, the increased complexity and variety of crystallographic software, the use of extensive databases and high-performance computing. This limits what can be accomplished with personal, offline, computing equipment in terms of both productivity and maintainability. There is also an issue of long-term data maintenance and availability of structure-solution projects as the links between experimental observations and the final results deposited in the PDB. In this article, CCP4 Cloud, a new front-end of the CCP4 software suite, is presented which mitigates these effects by providing an online, cloud-based environment for crystallographic computation. CCP4 Cloud was developed for the efficient delivery of computing power, database services and seamless integration with web resources. It provides a rich graphical user interface that allows project sharing and long-term storage for structure-solution projects, and can be linked to data-producing facilities. The system is distributed with the CCP4 software suite version 7.1 and higher, and an online publicly available instance of CCP4 Cloud is provided by CCP4.

Slurryability and Influencing Mechanism of Hydrophobic Structures in Additive-Coal-Water Ternary System.

This study investigates the effects of additive adsorption onto coal particles on surface properties, hydrophobic groups on the slurryability, and the moisture occurrence form on the performance of coal water slurry (CWS). Mechanisms related to the different hydrophobic structures of the additives are proposed. The adsorption method of sulfonated acetone formaldehyde enhances the adsorption capacity of coal surfaces but is not conducive to slurrying. Sodium lignin sulfonate has hydrophobic ends with nonpolar aromatic groups, three-dimensional macromolecular structures, and complex branched chains, which provide CWS with good stability and slurryability. Naphthalenesulfonate formaldehyde has a double benzene ring structure and provides the thick but nonuniform adsorption layers on coal surfaces. The many amorphous structures and low molecular weights of sodium humic sulfonate lead to nonuniform hydration films and poor slurryability. The results of this paper provide guidance for improving synergism in coal–water–additive systems and enhancing slurry performance.

RCSB Protein Data Bank: Celebrating 50 years of the PDB with new tools for understanding and visualizing biological macromolecules in 3D.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the US National Science Foundation, National Institutes of Health, and Department of Energy, has served structural biologists and Protein Data Bank (PDB) data consumers worldwide since 1999. RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, is the US data center for the global PDB archive housing biomolecular structure data. RCSB PDB is also responsible for the security of PDB data, as the wwPDB-designated Archive Keeper. Annually, RCSB PDB serves tens of thousands of three-dimensional (3D) macromolecular structure data depositors (using macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction) from all inhabited continents. RCSB PDB makes PDB data available from its research-focused RCSB.org web portal at no charge and without usage restrictions to millions of PDB data consumers working in every nation and territory worldwide. In addition, RCSB PDB operates an outreach and education PDB101.RCSB.org web portal that was used by more than 800,000 educators, students, and members of the public during calendar year 2020. This invited Tools Issue contribution describes (i) how the archive is growing and evolving as new experimental methods generate ever larger and more complex biomolecular structures; (ii) the importance of data standards and data remediation in effective management of the archive and facile integration with more than 50 external data resources; and (iii) new tools and features for 3D structure analysis and visualization made available during the past year via the RCSB.org web portal.

Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix.

Diffraction (X-ray, neutron and electron) and electron cryo-microscopy are powerful methods to determine three-dimensional macromolecular structures, which are required to understand biological processes and to develop new therapeutics against diseases. The overall structure-solution workflow is similar for these techniques, but nuances exist because the properties of the reduced experimental data are different. Software tools for structure determination should therefore be tailored for each method. Phenix is a comprehensive software package for macromolecular structure determination that handles data from any of these techniques. Tasks performed with Phenix include data-quality assessment, map improvement, model building, the validation/rebuilding/refinement cycle and deposition. Each tool caters to the type of experimental data. The design of Phenix emphasizes the automation of procedures, where possible, to minimize repetitive and time-consuming manual tasks, while default parameters are chosen to encourage best practice. A graphical user interface provides access to many command-line features of Phenix and streamlines the transition between programs, project tracking and re-running of previous tasks.

Iterative screen optimization maximizes the efficiency of macromolecular crystallization.

Advances in X-ray crystallography have streamlined the process of determining high-resolution three-dimensional macromolecular structures. However, a rate-limiting step in this process continues to be the generation of crystals that are of sufficient size and quality for subsequent diffraction experiments. Here, iterative screen optimization (ISO), a highly automated process in which the precipitant concentrations of each condition in a crystallization screen are modified based on the results of a prior crystallization experiment, is described. After designing a novel high-throughput crystallization screen to take full advantage of this method, the value of ISO is demonstrated by using it to successfully crystallize a panel of six diverse proteins. The results suggest that ISO is an effective method to obtain macromolecular crystals, particularly for proteins that crystallize under a narrow range of precipitant concentrations.

Decoding disease-causing mechanisms of missense mutations from supramolecular structures

The inheritance modes of pathogenic missense mutations are known to be highly associated with protein structures; recessive mutations are mainly observed in the buried region of protein structures, whereas dominant mutations are significantly enriched in the interfaces of molecular interactions. However, the differences in phenotypic impacts among various dominant mutations observed in individuals are not fully understood. In the present study, the functional effects of pathogenic missense mutations on three-dimensional macromolecular complex structures were explored in terms of dominant mutation types, namely, haploinsufficiency, dominant-negative, or toxic gain-of-function. The major types of dominant mutation were significantly associated with the different types of molecular interactions, such as protein-DNA, homo-oligomerization, or intramolecular domain-domain interactions, affected by mutations. The dominant-negative mutations were biased toward molecular interfaces for cognate protein or DNA. The haploinsufficiency mutations were enriched on the DNA interfaces. The gain-of-function mutations were localized to domain-domain interfaces. Our results demonstrate a novel use of macromolecular complex structures for predicting the disease-causing mechanisms through inheritance modes.

Demonstrating the value of three-dimensional macromolecular structures

Demonstrating the value of three-dimensional macromolecular structures

From polyelectrolyte complexes to polyelectrolyte multilayers: Electrostatic assembly, nanostructure, dynamics, and functional properties

Polyelectrolyte complexes (PECs) are three-dimensional macromolecular structures formed by association of oppositely charged polyelectrolytes in solution. Polyelectrolyte multilayers (PEMs) can be considered a special case of PECs prepared by layer-by-layer (LbL) assembly that involves sequential deposition of molecular-thick polyelectrolyte layers with nanoscale control over the size, shape, composition and internal organization. Although many functional PEMs with novel physical and chemical characteristics have been developed, the current practical applications of PEMs are limited to those that require only a few bilayers and are relatively easy to prepare. The viability of such engineered materials can be realized only after overcoming the scientific and engineering challenges of understanding the kinetics and transport phenomena involved in the multilayer growth and the factors governing their final structure, composition, and response to external stimuli. There is a great need to model PEMs and to connect PEM behavior with the characteristics of the PEC counterparts to allow for prediction of performance and better design of multilayered materials. This review focuses on the relationship between PEMs and PECs. The constitutive interactions, the thermodynamics and kinetics of polyelectrolyte complexation and PEM formation, PEC phase behavior, PEM growth, the internal structure and stability in PEMs and PECs, and their response to external stimuli are presented. Knowledge of such interactions and behavior can guide rapid fabrication of PEMs and can aid their applications as nanocomposites, coatings, nano-sized reactors, capsules, drug delivery systems, and in electrochemical and sensing devices. The challenges and opportunities in future research directions are also discussed.

Editorial: Function and Flexibility: Friend or Foe?

Editorial: Function and Flexibility: Friend or Foe?

Dendrimers in Medicine: Therapeutic Concepts and Pharmaceutical Challenges.

Dendrimers are three-dimensional macromolecular structures originating from a central core molecule and surrounded by successive addition of branching layers (generation). These structures exhibit a high degree of molecular uniformity, narrow molecular weight distribution, tunable size and shape characteristics, as well as multivalency. Collectively, these physicochemical characteristics together with advancements in design of biodegradable backbones have conferred many applications to dendrimers in formulation science and nanopharmaceutical developments. These have included the use of dendrimers as pro-drugs and vehicles for solubilization, encapsulation, complexation, delivery, and site-specific targeting of small-molecule drugs, biopharmaceuticals, and contrast agents. We briefly review these advances, paying particular attention to attributes that make dendrimers versatile for drug formulation as well as challenging issues surrounding the future development of dendrimer-based medicines.

Study of the development of the mouse thoracic aorta three-dimensional macromolecular structure using two-photon microscopy.

Using the intrinsic optical properties of collagen and elastin, two-photon microscopy was applied to evaluate the three-dimensional (3D) macromolecular structural development of the mouse thoracic aorta from birth to 60 days old. Baseline development was established in the Scavenger Receptor Class B Type I-Deficient, Hypomorphic Apolipoprotein ER61 (SR-BI KO/ApoeR61(h/h)) mouse in preparation for modeling atherosclerosis. Precise dissection enabled direct observation of the artery wall in situ. En-face, optical sectioning of the aorta provided a novel assessment of the macromolecular structural development. During aortic development, the undulating lamellar elastin layers compressed consistent with the increases in mean aortic pressure with age. In parallel, a net increase in overall wall thickness (p<0.05, in day 60 compared with day 1 mice) occurred with age whereas the ratio of the tunicas adventitia and media to full aortic thickness remained nearly constant across age groups (~1:2.6, respectively). Histochemical analyses by brightfield microscopy and ultrastructure validated structural proteins and lipid deposition findings derived from two-photon microscopy. Development was associated with decreased decorin but not biglycan proteoglycan expression. This non-destructive 3D in situ approach revealed the aortic wall microstructure development. Coupling this approach with the intrinsic optical properties of the macromolecules may provide unique vascular wall 3D structure in many pathological conditions, including aortic atherosclerosis, dissections and aneurysms.

Expanding our knowledge of the protein universe: Modelling of protein structures

Computational modeling and prediction of three-dimensional macromolecular structures and complexes from their sequence has been a long standing goal in structural biology. Over the last two decades, a paradigm shift has occurred: starting from a large "knowledge gap" between the huge number of protein sequences compared to a small number of experimentally known structures, today, some form of structural information – either experimental or computational – is available for the majority of amino acids encoded by common model organism genomes. Methods for structure modeling and prediction have made substantial progress of the last decades, and template based homology modeling techniques have matured to a point where they are now routinely used to complement experimental techniques. However, computational modeling and prediction techniques often fall short in accuracy compared to high-resolution experimental structures, and it is often difficult to convey the expected accuracy and structural variability of a specific model. Retrospectively assessing the quality of blind structure prediction in comparison to experimental reference structures allows benchmarking the state-of-the-art in structure prediction and identifying areas which need further development. The Critical Assessment of Structure Prediction (CASP) experiment has for the last 20 years assessed the progress in the field of protein structure modeling based on predictions for ca. 100 blind prediction targets per experiment which are carefully evaluated by human experts. The "Continuous Model EvaluatiOn" (CAMEO) project aims to provide a fully automated blind assessment for prediction servers based on weekly pre-released sequences of the Protein Data Bank PDB. CAMEO has been made possible by the development of novel scoring methods such as lDDT, which are robust against domain movements to allow for automated continuous structure comparison without human intervention.

Mechanism of Macromolecular Structure Evolution in Self-Assembled Lipid Nanoparticles for siRNA Delivery

Lipid nanoparticles (LNPs) are a leading platform for therapeutic delivery of small interfering RNAs (siRNAs). Optimization of LNPs as therapeutic products is enabled by the development of structure-activity relationships (SAR) linking LNP physiochemical and macromolecular properties to bioperformance. Methods by which LNP properties can be rationally manipulated are thus critical enablers of this fundamental knowledge build. In this work, we present a mechanistic study of LNP self-assembly via a rapid antisolvent precipitation process and identify critical physiochemical and kinetic parameters governing the evolution of LNP three-dimensional macromolecular structure as a biorelevant SAR feature. Using small-angle X-ray scattering, LNPs are shown to undergo a temporal evolution in macromolecular structure during self-assembly, rearranging from initially disordered phases after precipitation into well-ordered structures following a necessary annealing stage of the assembly sequence. The ability of LNPs to undergo structural reorganization is shown to be effected by the chemical nature of the aqueous antisolvent used for precipitation. Antisolvents of varying buffering species differentially influence LNP macromolecular features, revealing a new participatory role of buffer ions in LNP self-assembly. Furthermore, the formation of macromolecular structure in LNPs is shown to improve the efficiency of siRNA encapsulation, thereby offering a simple, nonchemical route for preparation of high-payload LNPs that minimize the dose of lipid excipients. The developed LNP precipitation process and mechanistic understanding of self-assembly are shown to be generalizable, enabling the production of LNPs with a tunable range of macromolecular features, as evidenced by the cubic, hexagonal, and oligo-lamellar phase LNPs exemplarily generated.

Two practical Java software tools for small-angle X-ray scattering analysis of biomolecules

Small-angle X-ray scattering has established itself as a common technique in structural biology research. Here, two novel Java applications to aid modelling of three-dimensional macromolecular structures based on small-angle scattering data are described.MolScatis an application that computes small-angle scattering intensities from user-provided three-dimensional models. The program can fit the theoretical scattering intensities to experimental X-ray scattering data.SAFIRis a program for interactive rigid-body modelling into low-resolution shapes restored from small-angle scattering data. The program has been designed with an emphasis on ease of use and intuitive handling. An embedded version ofMolScatis used to enable quick evaluation of the fit between the model and experimental scattering data.SAFIRalso provides options to refine macromolecular complexes with optional user-specified restraints against scattering data by means of a Monte Carlo approach.

Accurate macromolecular structures using minimal measurements from X-ray free-electron lasers

X-ray free-electron laser (XFEL) sources enable the use of crystallography to solve three-dimensional macromolecular structures under native conditions and without radiation damage. Results to date, however, have been limited by the challenge of deriving accurate Bragg intensities from a heterogeneous population of microcrystals, while at the same time modeling the X-ray spectrum and detector geometry. Here we present a computational approach designed to extract meaningful high-resolution signals from fewer diffraction measurements.

Macromolecular Imaging Agents Containing Lanthanides: Can Conceptual Promise Lead to Clinical Potential?

Macromolecular magnetic resonance imaging (MRI) contrast agents are increasingly being used to improve the resolution of this noninvasive diagnostic technique. All clinically-approved T1 contrast agents are small molecule chelates of gadolinium [Gd(III)] that affect bound water proton relaxivity. Both the small size and monomeric nature of these agents ultimately limits the image resolution enhancement that can be achieved for both contrast enhancement and pharmacokinetic/biodistribution reasons. The multimeric nature of macromolecules, such as polymers, dendrimers, and noncovalent complexes of small molecule agents with proteins, have been shown to significantly increase the image contrast and resolution due to their large size and ability to incorporate multiple Gd(III) chlelation sites. Also, macromolecular agents are advantageous as they have the ability to be designed to be nontoxic, hydrophilic, easily purified, aggregation-resistant, and have controllable three-dimensional macromolecular structure housing the multiple lanthanide chelation sites. For these reasons, large molecule diagnostics have the ability to significantly increase the relaxivity of water protons within the targeted tissues and thus the image resolution for many diagnostic applications. The FDA approval of a contrast agent that consists of a reversible, non-covalent coupling of a small Gd(III) chelate with serum albumin for blood pool imaging (marketed under the trade names of Vasovist and Ablivar) proved to be one of the first diagnostic agent to capitalize on these benefits from macromolecular association in humans. However, much research and development is necessary to optimize the safety of these unique agents for in vivo use and potential clinical development. To this end, recent work in the field of polymer, dendrimer, and noncovalent complex-based imaging agents are reviewed herein and the future outlook of this field is discussed.

MIPS: metal interactions in protein structures

MIPS (metal interactions in protein structures) is a database of metals in the three-dimensional macromolecular structures available in the Protein Data Bank. Bound metal ions in proteins have both catalytic and structural functions. The proposed database serves as an open resource for the analysis and visualization of all metals and their interactions with macromolecular (protein and nucleic acid) structures. MIPS can be searchedviaa user-friendly interface, and the interactions between metals and protein molecules, and the geometric parameters, can be viewed in both textual and graphical format using the freely available graphics plug-inJmol. MIPS is updated regularly, by means of programmed scripts to find metal-containing proteins from newly released protein structures. The database is useful for studying the properties of coordination between metals and protein molecules. It also helps to improve understanding of the relationship between macromolecular structure and function. This database is intended to serve the scientific community working in the areas of chemical and structural biology, and is freely available to all users, around the clock, at http://dicsoft2.physics.iisc.ernet.in/mips/.

Rapid Methods for Comparing Protein Structures and Scanning Structure Databases

Databases of three-dimensional macromolecular structures became so large that fast search tools and comparison methods were needed and were actually designed. All of them employ simplified representations of the threedimensional structure: strings of characters of variable length, which can be handled with procedures that were designed for sequence analysis; fixed dimension arrays that can be processed with standard statistical methods; ensembles of secondary structural elements, which are much less numerous than the atoms/residues of the protein; and continuous representations of the backbone, through stereochemical figures. Some of these computational procedures were developed long ago, when computers were too slow, and others have been designed recently, with the specific aim of handling large amount of information. The present article is focused on the algorithms that allow fast structure comparison, particularly suitable to handle large databases, and should provide a comprehensive picture, useful for the development and the assessment of novel tools. Keywords: Protein structure, structural alignment, structure comparison, structure database

Noise bias in the refinement of structures derived from single particles

One of the main goals in the determination of three-dimensional macromolecular structures from electron microscope images of individual molecules and complexes (single particles) is a sufficiently high spatial resolution, about 4Å, at which the interpretation with an atomic model becomes possible. To reach high resolution, an iterative refinement procedure using an expectation maximization algorithm is often used that leads to a more accurate alignment of the positional and orientational parameters for each particle. We show here the results of refinement algorithms that use a phase residual, a linear correlation coefficient, or a weighted correlation coefficient to align individual particles. The algorithms were applied to computer-generated data sets that contained projections from model structures, as well as noise. The algorithms show different degrees of over-fitting, especially at high resolution where the signal is weak. We demonstrate that the degree of over-fitting is reduced with a weighting scheme that depends on the signal-to-noise ratio in the data. The weighting also improves the accuracy of resolution measurement by the commonly used Fourier shell correlation. The performance of the refinement algorithms is compared to that using a maximum likelihood approach. The weighted correlation coefficient was implemented in the computer program FREALIGN.

The 2003 Nobel Prize for MRI: significance and impact.

The 2003 Nobel Prize for MRI: significance and impact.