Ab initio structure determination of n-diamond.
Ontology highlight
ABSTRACT:
SUBMITTER: Li D
PROVIDER: S-EPMC4547140 | biostudies-literature | 2015 Aug
REPOSITORIES: biostudies-literature
Publications
Ab initio structure determination of n-diamond.
Li Da D Tian Fubo F Chu Binhua B Duan Defang D Sha Xiaojing X Lv Yunzhou Y Zhang Huadi H Lu Nan N Liu Bingbing B Cui Tian T
Scientific reports 20150824
A systematic computational study on the crystal structure of n-diamond has been performed using first-principle methods. A novel carbon allotrope with hexagonal symmetry R32 space group has been predicted. We name it as HR-carbon. HR-carbon composed of lonsdaleite layers and unique C3 isosceles triangle rings, is stable over graphite phase above 14.2 GPa. The simulated x-ray diffraction pattern, Raman, and energy-loss near-edge spectrum can match the experimental results very well, indicating th ...[more]
Similar Datasets
Project description:Fluctuation X-ray scattering (FXS) is an emerging experimental technique in which X-ray solution scattering data are collected from particles in solution using ultrashort X-ray exposures generated by a free-electron laser (FEL). FXS experiments overcome the low data-to-parameter ratios associated with traditional solution scattering measurements by providing several orders of magnitude more information in the final processed data. Here we demonstrate the practical feasibility of FEL-based FXS on a biological multiple-particle system and describe data-processing techniques required to extract robust FXS data and significantly reduce the required number of snapshots needed by introducing an iterative noise-filtering technique. We showcase a successful ab initio electron density reconstruction from such an experiment, studying the Paramecium bursaria Chlorella virus (PBCV-1).
| S-EPMC6243272 | biostudies-literature
Project description:Electrons, because of their strong interaction with matter, produce high-resolution diffraction patterns from tiny 3D crystals only a few hundred nanometers thick in a frozen-hydrated state. This discovery offers the prospect of facile structure determination of complex biological macromolecules, which cannot be coaxed to form crystals large enough for conventional crystallography or cannot easily be produced in sufficient quantities. Two potential obstacles stand in the way. The first is a phenomenon known as dynamical scattering, in which multiple scattering events scramble the recorded electron diffraction intensities so that they are no longer informative of the crystallized molecule. The second obstacle is the lack of a proven means of de novo phase determination, as is required if the molecule crystallized is insufficiently similar to one that has been previously determined. We show with four structures of the amyloid core of the Sup35 prion protein that, if the diffraction resolution is high enough, sufficiently accurate phases can be obtained by direct methods with the cryo-EM method microelectron diffraction (MicroED), just as in X-ray diffraction. The success of these four experiments dispels the concern that dynamical scattering is an obstacle to ab initio phasing by MicroED and suggests that structures of novel macromolecules can also be determined by direct methods.
| S-EPMC5056061 | biostudies-literature
Project description:Serial electron diffraction (SerialED), which applies a snapshot data acquisition strategy for each crystal, was introduced to tackle the problem of radiation damage in the structure determination of beam-sensitive materials by three-dimensional electron diffraction (3DED). The snapshot data acquisition in SerialED can be realized using both transmission and scanning transmission electron microscopes (TEM/STEM). However, the current SerialED workflow based on STEM setups requires special external devices and software, which limits broader adoption. Here, we present a simplified experimental implementation of STEM-based SerialED on Thermo Fisher Scientific STEMs using common proprietary software interfaced through Python scripts to automate data collection. Specifically, we utilize TEM Imaging and Analysis (TIA) scripting and TEM scripting to access the STEM functionalities of the microscope, and DigitalMicrograph scripting to control the camera for snapshot data acquisition. Data analysis adapts the existing workflow using the software CrystFEL, which was developed for serial X-ray crystallography. Our workflow for STEM SerialED can be used on any Gatan or Thermo Fisher Scientific camera. We apply this workflow to collect high-resolution STEM SerialED data from two aluminosilicate zeolites, zeolite Y and ZSM-25. We demonstrate, for the first time, ab initio structure determination through direct methods using STEM SerialED data. Zeolite Y is relatively stable under the electron beam, and STEM SerialED data extend to 0.60 Å. We show that the structural model obtained using STEM SerialED data merged from 358 crystals is nearly identical to that using continuous rotation electron diffraction data from one crystal. This demonstrates that accurate structures can be obtained from STEM SerialED. Zeolite ZSM-25 is very beam-sensitive and has a complex structure. We show that STEM SerialED greatly improves the data resolution of ZSM-25, compared with serial rotation electron diffraction (SerialRED), from 1.50 to 0.90 Å. This allows, for the first time, the use of standard phasing methods, such as direct methods, for the ab initio structure determination of ZSM-25.
| S-EPMC10833385 | biostudies-literature
Project description:With the rapid growth of energy demand and the depletion of existing energy resources, the new materials with superior performances, low costs and environmental friendliness for energy production and storage are explored. Di-p-tolyl disulfide (p-Tol2S2) is a typical lubricating material, which has been applied in the field of energy storage. The conformational properties and phase transformations of p-Tol2S2 have been studied by pioneers, but their polymorphs and the polymorphism induced crystal structure changes require further analysis. In this study, we perform the crystal structural screening, prediction and optimization of p-Tol2S2 crystal with quantum mechanical calculations, i.e., density functional theory (DFT) and second-order Møller-Plesset perturbation (MP2) methods. A series of crystal structures with different molecular arrangements are generated based on the crystal structure screening. As compared to long-established lattice energy calculation, we take an advantage of using more accurate technique, which is Gibbs free energy calculation. It considers the effects of entropy and temperature to predict the crystal structures and energy landscape. By comparing the Gibbs free energies between predicted and experimental structures, we found that phase α is the most stable structure for p-Tol2S2 crystal at ambient temperature and standard atmospheric pressure. Furthermore, we provide an efficient method to discriminate different polymorphs that are otherwise difficult to be identified based on the Raman/IR spectra. The proposed work enable us to evaluate the quality of various crystal polymorphs rapidly.
| S-EPMC8007795 | biostudies-literature
Project description:Neural-network quantum states have been successfully used to study a variety of lattice and continuous-space problems. Despite a great deal of general methodological developments, representing fermionic matter is however still early research activity. Here we present an extension of neural-network quantum states to model interacting fermionic problems. Borrowing techniques from quantum simulation, we directly map fermionic degrees of freedom to spin ones, and then use neural-network quantum states to perform electronic structure calculations. For several diatomic molecules in a minimal basis set, we benchmark our approach against widely used coupled cluster methods, as well as many-body variational states. On some test molecules, we systematically improve upon coupled cluster methods and Jastrow wave functions, reaching chemical accuracy or better. Finally, we discuss routes for future developments and improvements of the methods presented.
| S-EPMC7217823 | biostudies-literature
Project description:Ferrihydrite is a poorly crystalline iron oxyhydroxide nanomineral that serves a critical role as the most bioavailable form of ferric iron for living systems. However, its atomic structure and composition remain unclear due in part to ambiguities in interpretation of X-ray scattering results. Prevailing models so far have not considered the prospect that at the level of individual nanoparticles multiple X-ray indistinguishable phases could coexist. Using ab initio thermodynamics we show that ferrihydrite is likely a nanocomposite of distinct structure types whose distribution depends on particle size, temperature, and hydration. Nanoparticles of two contrasting single-phase ferrihydrite models of Michel and Manceau are here shown to be thermodynamically equivalent across a wide range of temperature and pressure conditions despite differences in their structural water content. Higher temperature and water pressure favor the formation of the former, while lower temperature and water pressure favor the latter. For aqueous suspensions at ambient conditions, their coexistence is maximal for particle sizes up to 12 nm. The predictions inform and help resolve different observations in various experiments.
| S-EPMC9814694 | biostudies-literature
Project description: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.
| S-EPMC4285884 | biostudies-literature
Project description:Molecular averaging, including noncrystallographic symmetry (NCS) averaging, is a powerful method for ab initio phase determination and phase improvement. Applications of the cross-crystal averaging (CCA) method have been shown to be effective for phase improvement after initial phasing by molecular replacement, isomorphous replacement, anomalous dispersion or combinations of these methods. Here, a two-step process for phase determination in the X-ray structural analysis of a new coat protein from a betanodavirus, Grouper nervous necrosis virus, is described in detail. The first step is ab initio structure determination of the T = 3 icosahedral virus-like particle using NCS averaging (NCSA). The second step involves structure determination of the protrusion domain of the viral molecule using cross-crystal averaging. In this method, molecular averaging and solvent flattening constrain the electron density in real space. To quantify these constraints, a new, simple and general indicator, free fraction (ff), is introduced, where ff is defined as the ratio of the volume of the electron density that is freely changed to the total volume of the crystal unit cell. This indicator is useful and effective to evaluate the strengths of both NCSA and CCA. Under the condition that a mask (envelope) covers the target molecule well, an ff value of less than 0.1, as a new rule of thumb, gives sufficient phasing power for the successful construction of new structures.
| S-EPMC4932916 | biostudies-literature
Project description:Fragment assembly using structural motifs excised from other solved proteins has shown to be an efficient method for ab initio protein-structure prediction. However, how to construct accurate fragments, how to derive optimal restraints from fragments, and what the best fragment length is are the basic issues yet to be systematically examined. In this work, we developed a gapless-threading method to generate position-specific structure fragments. Distance profiles and torsion angle pairs are then derived from the fragments by statistical consistency analysis, which achieved comparable accuracy with the machine-learning-based methods although the fragments were taken from unrelated proteins. When measured by both accuracies of the derived distance profiles and torsion angle pairs, we come to a consistent conclusion that the optimal fragment length for structural assembly is around 10, and at least 100 fragments at each location are needed to achieve optimal structure assembly. The distant profiles and torsion angle pairs as derived by the fragments have been successfully used in QUARK for ab initio protein structure assembly and are provided by the QUARK online server at http://zhanglab.ccmb. med.umich.edu/QUARK/.
| S-EPMC3551984 | biostudies-literature
Project description:BackgroundMicroRNAs (miRNAs) are short, non-coding RNA molecules that are directly involved in post-transcriptional regulation of gene expression. The mature miRNA sequence binds to more or less specific target sites on the mRNA. Both their small size and sequence specificity make the detection of completely new miRNAs a challenging task. This cannot be based on sequence information alone, but requires structure information about the miRNA precursor. Unlike comparative genomics approaches, ab initio approaches are able to discover species-specific miRNAs without known sequence homology.ResultsMiRPred is a novel method for ab initio prediction of miRNAs by genome scanning that only relies on (predicted) secondary structure to distinguish miRNA precursors from other similar-sized segments of the human genome. We apply a machine learning technique, called linear genetic programming, to develop special classifier programs which include multiple regular expressions (motifs) matched against the secondary structure sequence. Special attention is paid to scanning issues. The classifiers are trained on fixed-length sequences as these occur when shifting a window in regular steps over a genome region. Various statistical and empirical evidence is collected to validate the correctness of and increase confidence in the predicted structures. Among other things, we propose a new criterion to select miRNA candidates with a higher stability of folding that is based on the number of matching windows around their genome location. An ensemble of 16 motif-based classifiers achieves 99.9 percent specificity with sensitivity remaining on an acceptable high level when requiring all classifiers to agree on a positive decision. A low false positive rate is considered more important than a low false negative rate, when searching larger genome regions for unknown miRNAs. 117 new miRNAs have been predicted close to known miRNAs on human chromosome 19. All candidate structures match the free energy distribution of miRNA precursors which is significantly shifted towards lower free energies. We employed a human EST library and found that around 75 percent of the candidate sequences are likely to be transcribed, with around 35 percent located in introns.ConclusionOur motif finding method is at least competitive to state-of-the-art feature-based methods for ab initio miRNA discovery. In doing so, it requires less previous knowledge about miRNA precursor structures while programs and motifs allow a more straightforward interpretation and extraction of the acquired knowledge.
| S-EPMC2238772 | biostudies-literature