Effects of genetic variation on the structure of RNA and protein

Changes in the structure of RNA and protein, have an important impact on biological functions and are even important determinants of disease pathogenesis and treatment. Some genetic variations, including copy number variation, single nucleotide variation, and so on, can lead to changes in biological function and increased susceptibility to certain diseases by changing the structure of RNA or protein. With the development of structural biology and sequencing technology, a large amount of RNA and protein structure data and genetic variation data resources has emerged to be used to explain biological processes. Here, we reviewed the effects of genetic variation on the structure of RNAs and proteins, and investigated their impact on several diseases. An online resource (http://www.onethird-lab.com/gems/) to support convenient retrieval of common tools is also built. Finally, the challenges and future development of the effects of genetic variation on RNA and protein were discussed.

Theoretical 3D electron diffraction electrostatic potential maps of proteins modeled with a multipolar pseudoatom data bank

The availability of atomic resolution experimental maps of electrostatic potential from 3D electron diffraction (3D ED) extends the possibility of investigating the electrostatic potential beyond the determination of non-H-atom positions. However, accurate tools to calculate this potential for macromolecules, without the use of expensive quantum calculations, are lacking. The University at Buffalo Data Bank (UBDB) gathers atom types that can be used to calculate accurate electrostatic potential maps via structure-factor calculations. Here, the transferable aspherical atom model (TAAM) is applied with UBDB to investigate theoretically obtained electrostatic potential maps of lysozyme and proteinase K, and compare them with experimental maps from 3D ED. UBDB better reproduces the molecular electrostatic potential of molecules within their entire volume compared with the neutral spherical models used in the popular independent atom model (IAM). Additionally, the theoretical electron-density maps of the studied proteins are shown and compared with the electrostatic potential maps. The atomic displacement parameters (B factors) may affect the electrostatic potential maps in a different way than in the case of electron-density maps. The computational method presented in this study could potentially facilitate the interpretation of the less resolved regions of cryo-electron microscopy density maps and pave the way for distinguishing between different ions/water molecules in the active sites of macromolecules in high-resolution structures, which is of interest for drug-design purposes.

PDBx/mmCIF Ecosystem: Foundational Semantic Tools for Structural Biology

PDBx/mmCIF, Protein Data Bank Exchange (PDBx) macromolecular Crystallographic Information Framework (mmCIF), has become the data standard for structural biology. With its early roots in the domain of small-molecule crystallography, PDBx/mmCIF provides an extensible data representation that is used for deposition, archiving, remediation, and public dissemination of experimentally determined three-dimensional (3D) structures of biological macromolecules by the Worldwide Protein Data Bank (wwPDB, wwpdb.org). Extensions of PDBx/mmCIF are similarly used for computed structure models by ModelArchive (modelarchive.org), integrative/hybrid structures by PDB-Dev (pdb-dev.wwpdb.org), small angle scattering data by Small Angle Scattering Biological Data Bank SASBDB (sasbdb.org), and for models computed generated with the AlphaFold 2.0 deep learning software suite (alphafold.ebi.ac.uk). Community-driven development of PDBx/mmCIF spans three decades, involving contributions from researchers, software and methods developers in structural sciences, data repository providers, scientific publishers, and professional societies. Having a semantically rich and extensible data framework for representing a wide range of structural biology experimental and computational results, combined with expertly curated 3D biostructure data sets in public repositories, accelerates the pace of scientific discovery. Herein, we describe the architecture of the PDBx/mmCIF data standard, tools used to maintain representations of the data standard, governance, and processes by which data content standards are extended, plus community tools/software libraries available for processing and checking the integrity of PDBx/mmCIF data. Use cases exemplify how the members of the Worldwide Protein Data Bank have used PDBx/mmCIF as the foundation for its pipeline for delivering Findable, Accessible, Interoperable, and Reusable (FAIR) data to many millions of users worldwide.

Fine Characterization of the Macromolecular Structure of Huainan Coal Using XRD, FTIR, 13C-CP/MAS NMR, SEM, and AFM Techniques

Research on the composition and structure of coal is the most important and complex basic research in the coal chemistry field. Various methods have been used to study the structure of coal from different perspectives. However, due to the complexity of coal and the limitations of research methods, research on the macromolecular structure of coal still lacks systematicness. Huainan coalfield is located in eastern China and is the largest coal production and processing base in the region. In this study, conventional proximate analysis and ultimate analysis, as well as advanced instrumental analysis methods, such as Fourier transform infrared spectroscopy (FITR), X-ray diffraction (XRD), ¹³C-CP/MAS NMR, and other methods (SEM and AFM), were used to analyze the molecular structure of Huainan coal (HNC) and the distribution characteristics of oxygen in different oxygen-containing functional groups (OCFGs) in an in-depth manner. On the basis of SEM observation, it could be concluded that the high-resolution morphology of HNC’s surface contains pores and fractures of different sizes. The loose arrangement pattern of HNC’s molecular structure could be seen from 3D AFM images. The XRD patterns show that the condensation degree of HNC’s aromatic ring is low, and the orientation degree of carbon network lamellae is poor. The calculated ratio of the diameter of aromatic ring lamellae to their stacking height (La/Lc = 1.05) and the effective stacking number of aromatic nuclei (Nave = 7.3) show that the molecular space structure of HNC is a cube formed of seven stacked aromatic lamellae. The FTIR spectra fitting results reveal that the aliphatic chains in HNC’s molecular structure are mainly methyne and methylene. Oxygen is mainly –O–, followed by –C=O, and contains a small amount of –OH, the ratio of which is about 8:1:2. The molar fraction of binding elements has the approximate molecular structure C₁₀₀H₇₆O₉N of organic matter in HNC. The results of the ¹³C NMR experiments show that the form of aromatic carbon atoms in HNC’s structure (the average structural size X_b of aromatic nucleus = 0.16) is mainly naphthalene with a condensation degree of 2, and the rest are aromatic rings composed of benzene rings and heteroatoms. In addition, HNC is relatively rich in ≡CH and –CH₂– structures.

Inhibitory Effects of Carrageenans on Endotoxin-Induced Inflammation

The inhibitory effects of carrageenans (CRGs) on lipopolysaccharide (LPS) induced inflammation in a mouse model of endotoxemia and in complex therapy of patients with enteric infections of Salmonella etiology were studied. The atomic force microscopy (AFM) examination of LPS and its mixture with CRGs showed that the LPS morphology is significantly changed under the action of κ- and κ/β-CRGs. CRGs were able to increase the synthesis of anti-inflammatory interleukin 10 (IL-10) in vitro, and, at low concentrations, their activity in the mixture with LPS was higher. The protective effect of CRGs against Escherichia coli LPS was studied in vivo by monitoring the biochemical and pathomorphological parameters. The κ- and κ/β-CRGs and food supplement "Carrageenan-FE" increased the nonspecific resistance of mice to E. coli LPS at the expense of the inhibition of processes of thymus involution, adrenals hypertrophy, thyroid atrophy, hypercorticoidism, glycogenolysis, and lactate acidosis. The estimation of the therapeutic action of food supplement Carrageenan-FE in complex therapy of patients with enteric infections of Salmonella etiology is given. Carrageenan-FE restores the system of hemostasis and corrects some biochemical indicators and parameters in the immune systems of patients. These results allow us to hope for the practical application of CRGs for lowering the endotoxemia level in patients under the development of the infectious process caused by Gram-negative bacteria.

Two-Component Sensing and Regulation: How Do Histidine Kinases Talk with Response Regulators at the Molecular Level?

Perceiving environmental and internal information and reacting in adaptive ways are essential attributes of living organisms. Two-component systems are relevant protein machineries from prokaryotes and lower eukaryotes that enable cells to sense and process signals. Implicating sensory histidine kinases and response regulator proteins, both components take advantage of protein phosphorylation and flexibility to switch conformations in a signal-dependent way. Dozens of two-component systems act simultaneously in any given cell, challenging our understanding about the means that ensure proper connectivity. This review dives into the molecular level, attempting to summarize an emerging picture of how histidine kinases and cognate response regulators achieve required efficiency, specificity, and directionality of signaling pathways, properties that rely on protein:protein interactions. α helices that carry information through long distances, the fine combination of loose and specific kinase/regulator interactions, and malleable reaction centers built when the two components meet emerge as relevant universal principles.

A structural view of bacterial DNA replication

DNA replication mechanisms are conserved across all organisms. The proteins required to initiate, coordinate, and complete the replication process are best characterized in model organisms such as Escherichia coli. These include nucleotide triphosphate-driven nanomachines such as the DNA-unwinding helicase DnaB and the clamp loader complex that loads DNA-clamps onto primer-template junctions. DNA-clamps are required for the processivity of the DNA polymerase III core, a heterotrimer of α, ε, and θ, required for leading- and lagging-strand synthesis. DnaB binds the DnaG primase that synthesizes RNA primers on both strands. Representative structures are available for most classes of DNA replication proteins, although there are gaps in our understanding of their interactions and the structural transitions that occur in nanomachines such as the helicase, clamp loader, and replicase core as they function. Reviewed here is the structural biology of these bacterial DNA replication proteins and prospects for future research.

Toward an Ensemble View of Chromatosome Structure: A Paradigm Shift from One to Many

There is renewed interest in linker histone (LH)-nucleosome binding and how LHs influence eukaryotic DNA compaction. For a long time, the goal was to uncover "the structure of the chromatosome," but recent studies of LH-nucleosome complexes have revealed an ensemble of structures. Notably, the reconstituted LH-nucleosome complexes used in experiments rarely correspond to the sequence combinations present in organisms. For a full understanding of the determinants of the distribution of the chromatosome structural ensemble, studies must include a complete description of the sequences and experimental conditions used, and be designed to enable systematic evaluation of sequence and environmental effects.

A convolutional neural network-based screening tool for X-ray serial crystallography

A new tool is introduced for screening macromolecular X-ray crystallography diffraction images produced at an X-ray free-electron laser light source. Based on a data-driven deep learning approach, the proposed tool executes a convolutional neural network to detect Bragg spots. Automatic image processing algorithms described can enable the classification of large data sets, acquired under realistic conditions consisting of noisy data with experimental artifacts. Outcomes are compared for different data regimes, including samples from multiple instruments and differing amounts of training data for neural network optimization.

RCSB Protein Data Bank: Sustaining a living digital data resource that enables breakthroughs in scientific research and biomedical education

The Protein Data Bank (PDB) is one of two archival resources for experimental data central to biomedical research and education worldwide (the other key Primary Data Archive in biology being the International Nucleotide Sequence Database Collaboration). The PDB currently houses >134,000 atomic level biomolecular structures determined by crystallography, NMR spectroscopy, and 3D electron microscopy. It was established in 1971 as the first open-access, digital-data resource in biology, and is managed by the Worldwide Protein Data Bank partnership (wwPDB; wwpdb.org). US PDB operations are conducted by the RCSB Protein Data Bank (RCSB PDB; RCSB.org; Rutgers University and UC San Diego) and funded by NSF, NIH, and DoE. The RCSB PDB serves as the global Archive Keeper for the wwPDB. During calendar 2016, >591 million structure data files were downloaded from the PDB by Data Consumers working in every sovereign nation recognized by the United Nations. During this same period, the RCSB PDB processed >5300 new atomic level biomolecular structures plus experimental data and metadata coming into the archive from Data Depositors working in the Americas and Oceania. In addition, RCSB PDB served >1 million RCSB.org users worldwide with PDB data integrated with ∼40 external data resources providing rich structural views of fundamental biology, biomedicine, and energy sciences, and >600,000 PDB101.rcsb.org educational website users around the globe. RCSB PDB resources are described in detail together with metrics documenting the impact of access to PDB data on basic and applied research, clinical medicine, education, and the economy.

A new parameter-rich structure-aware mechanistic model for amino acid substitution during evolution

Improvements in the description of amino acid substitution are required to develop better pseudo-energy-based protein structure-aware models for use in phylogenetic studies. These models are used to characterize the probabilities of amino acid substitution and enable better simulation of protein sequences over a phylogeny. A better characterization of amino acid substitution probabilities in turn enables numerous downstream applications, like detecting positive selection, ancestral sequence reconstruction, and evolutionarily-motivated protein engineering. Many existing Markov models for amino acid substitution in molecular evolution disregard molecular structure and describe the amino acid substitution process over longer evolutionary periods poorly. Here, we present a new model upgraded with a site-specific parameterization of pseudo-energy terms in a coarse-grained force field, which describes local heterogeneity in physical constraints on amino acid substitution better than a previous pseudo-energy-based model with minimum cost in runtime. The importance of each weight term parameterization in characterizing underlying features of the site, including contact number, solvent accessibility, and secondary structural elements was evaluated, returning both expected and biologically reasonable relationships between model parameters. This results in the acceptance of proposed amino acid substitutions that more closely resemble those observed site-specific frequencies in gene family alignments. The modular site-specific pseudo-energy function is made available for download through the following website: https://liberles.cst.temple.edu/Software/CASS/index.html.

The young person's guide to the PDB

The Protein Data Bank (PDB), created in 1971 when merely seven protein crystal structures were known, today holds over 120, 000 experimentally-determined three-dimensional models of macromolecules, including gigantic structures comprised of hundreds of thousands of atoms, such as ribosomes and viruses. Most of the deposits come from X-ray crystallography experiments, with important contributions also made by NMR spectroscopy and, recently, by the fast growing Cryo-Electron Microscopy. Although the determination of a macromolecular crystal structure is now facilitated by advanced experimental tools and by sophisticated software, it is still a highly complicated research process requiring specialized training, skill, experience and a bit of luck. Understanding the plethora of structural information provided by the PDB requires that its users (consumers) have at least a rudimentary initiation. This is the purpose of this educational overview.

Single-particle cryo-electron microscopy of macromolecular complexes

Recent technological breakthroughs in image acquisition have enabled single-particle cryo-electron microscopy (cryo-EM) to achieve near-atomic resolution structural information for biological complexes. The improvements in image quality coupled with powerful computational methods for sorting distinct particle populations now also allow the determination of compositional and conformational ensembles, thereby providing key insights into macromolecular function. However, the inherent instability and dynamic nature of biological assemblies remain a tremendous challenge that often requires tailored approaches for successful implementation of the methodology. Here, we briefly describe the fundamentals of single-particle cryo-EM with an emphasis on covering the breadth of techniques and approaches, including low- and high-resolution methods, aiming to illustrate specific steps that are crucial for obtaining structural information by this method.

Conformations of macromolecules and their complexes from heterogeneous datasets

We describe a new generation of algorithms capable of mapping the structure and conformations of macromolecules and their complexes from large ensembles of heterogeneous snapshots, and demonstrate the feasibility of determining both discrete and continuous macromolecular conformational spectra. These algorithms naturally incorporate conformational heterogeneity without resort to sorting and classification, or prior knowledge of the type of heterogeneity present. They are applicable to single-particle diffraction and image datasets produced by X-ray lasers and cryo-electron microscopy, respectively, and particularly suitable for systems not easily amenable to purification or crystallization.

Macromolecular ab initio phasing enforcing secondary and tertiary structure

Ab initio phasing of macromolecular structures, from the native intensities alone with no experimental phase information or previous particular structural knowledge, has been the object of a long quest, limited by two main barriers: structure size and resolution of the data. Current approaches to extend the scope of ab initio phasing include use of the Patterson function, density modification and data extrapolation. The authors' approach relies on the combination of locating model fragments such as polyalanine α-helices with the program PHASER and density modification with the program SHELXE. Given the difficulties in discriminating correct small substructures, many putative groups of fragments have to be tested in parallel; thus calculations are performed in a grid or supercomputer. The method has been named after the Italian painter Arcimboldo, who used to compose portraits out of fruit and vegetables. With ARCIMBOLDO, most collections of fragments remain a 'still-life', but some are correct enough for density modification and main-chain tracing to reveal the protein's true portrait. Beyond α-helices, other fragments can be exploited in an analogous way: libraries of helices with modelled side chains, β-strands, predictable fragments such as DNA-binding folds or fragments selected from distant homologues up to libraries of small local folds that are used to enforce nonspecific tertiary structure; thus restoring the ab initio nature of the method. Using these methods, a number of unknown macromolecules with a few thousand atoms and resolutions around 2 Å have been solved. In the 2014 release, use of the program has been simplified. The software mediates the use of massive computing to automate the grid access required in difficult cases but may also run on a single multicore workstation (http://chango.ibmb.csic.es/ARCIMBOLDO_LITE) to solve straightforward cases.

Fitting multimeric protein complexes into electron microscopy maps using 3D Zernike descriptors

A novel computational method for fitting high-resolution structures of multiple proteins into a cryoelectron microscopy map is presented. The method named EMLZerD generates a pool of candidate multiple protein docking conformations of component proteins, which are later compared with a provided electron microscopy (EM) density map to select the ones that fit well into the EM map. The comparison of docking conformations and the EM map is performed using the 3D Zernike descriptor (3DZD), a mathematical series expansion of three-dimensional functions. The 3DZD provides a unified representation of the surface shape of multimeric protein complex models and EM maps, which allows a convenient, fast quantitative comparison of the three-dimensional structural data. Out of 19 multimeric complexes tested, near native complex structures with a root-mean-square deviation of less than 2.5 Å were obtained for 14 cases while medium range resolution structures with correct topology were computed for the additional 5 cases.

Tonal interface to MacroMolecules (TIMMol): A textual and tonal tool for molecular visualization

We developed the three-dimensional visualization software, Tonal Interface to MacroMolecules or TIMMol, for studying atomic coordinates of protein structures. Key features include audio tones indicating x, y, z location, identification of the cursor location in one-dimensional and three-dimensional space, textual output that can be easily linked to speech or Braille output, and the ability to scroll along the main chain backbone of a protein structure. This program was initially designed for visually impaired users, and it already has shown its effectiveness in helping a blind researcher study X-ray crystal structure data. Subsequently, TIMMol has been enhanced with a graphical display to act as a bridge to ease communication between sighted and visually impaired users as well as to serve users with spatial visualization difficulties. We performed a pilot study to assess the efficacy of the program in conveying three-dimensional information about proteins with and without graphical output to a general scientific audience. Attitudes regarding using TIMMol were assessed using Rasmol, a common visualization package, for comparison. With the use of text and tones exclusively, a majority of users were able to identify specific secondary structure elements, three-dimensional relationships among atoms, and atoms coordinating a ligand. In addition, a majority of users saw benefits in using TIMMol and would recommend it to those having difficulty with standard tools.