Determination of the site of incorporation of cobalt in CoZnPO-CZP by multiple-wavelength anomalous-dispersion crystallography

1999 ◽  
Vol 55 (3) ◽  
pp. 327-332 ◽  
Author(s):  
M. Helliwell ◽  
J. R. Helliwell ◽  
V. Kaucic ◽  
N. Zabukovec Logar ◽  
L. Barba ◽  
...  
Keyword(s):  
Metal Atom ◽  
Peak Height ◽  
Data Sets ◽  
White Line ◽  
Data Set ◽  
Small Peak ◽  
Multiple Wavelength ◽  
Subsequent Calculation ◽  
Difference Fourier ◽  
Two Peaks

Data were collected from a crystal of CoZnPO-CZP {sodium cobalt–zinc phosphate hydrate, Na6[Co0.2Zn0.8PO4]6.6H2O} using synchrotron radiation at ELETTRA at the inflection point and `white line' for both the cobalt and zinc K edges, and at 1.45 Å, a wavelength remote from the K edges of both metals. The data were processed using the programs DENZO and SCALEPACK. The CCP4 program suite was used for the scaling of data sets and the subsequent calculation of dispersive difference Fourier maps. Optimal scaling was achieved by using a subset of reflections with little or no contribution from the metal atoms (i.e. which were essentially wavelength independent in their intensities) and using weights based on the σ's to obtain an overall scale factor in each case. Phases were calculated with SHELXL97 based on the refined structure using a much higher resolution and complete Cu Kα data set. An occupancy of 100% by zinc at the two metal-atom sites was assumed. The dispersive difference Fourier map calculated for zinc gave two peaks above the background of similar heights at the expected metal-atom sites. The peak height at the Zn1 site was a little higher than at the Zn2 site. The dispersive difference Fourier map calculated for cobalt gave just one peak above the background, at the Zn1 site, and only a small peak at the Zn2 site, thus indicating that incorporation of cobalt takes place mainly at one site. Refinement of the zinc occupancies using MLPHARE reinforces this conclusion. The chemical environment of each site is discussed.

Crystal and Molecular Structure of Thiocarbonyl-ethoxo(tetraphenylporphyrinato)ruthenium(II), [Ru(TPP)(CS)(HOC2H5)]. A Case of Centrosymmetric–Noncentrosymmetric Ambiguity

1997 ◽  
Vol 53 (5) ◽  
pp. 767-772 ◽  
Author(s):  
T. J. Bartczak ◽  
K. Rachlewicz ◽  
L. Latos-Grażynski
Keyword(s):  
Crystal And Molecular Structure ◽  
Bond Angle ◽  
Data Sets ◽  
Alpha Radiation ◽  
Data Set ◽  
Fourier Methods ◽  
Space Group ◽  
Space Groups ◽  
The Mean ◽  
Difference Fourier

[Ru(TPP)(CS)(EtOH)] crystallizes in the triclinic system. Crystal data: C47H34N4ORuS, M r = 803.91, a = 10.607 (3), b = 11.308 (5), c = 17.699 (2) Å, \alpha = 77.53 (2), \beta = 73.17 (1), \gamma = 69.85 (3)°, V = 1891.6 (10) Å3, P\overline 1 (C^{1}_{i}, no. 2), Z = 2, F(000) = 824, D x = 1.410, D m = 1.39 Mg m−3 (by flotation in aqueous KI), \mu(Mo K\alpha) = 0.512 mm−1, R = 0.094, wR = 0.098, S = 2.28 for 4610 independent reflections with F o > 5\sigma(F o ). A second data set was collected using Cu K\alpha radiation. The structure was refined by standard least-squares and difference-Fourier methods in space groups P1 and P\overline 1 using both the Mo K\alpha and Cu K\alpha data sets. Both data sets favor space group P\overline 1, the Mo data giving a slightly better result than the Cu data. The two independent Ru atoms lie on the inversion centers ½,0,0 and ½,½,½ of space group P\overline 1. Consequently, the two independent molecules have crystallographically imposed \overline 1 symmetry, the CS and EtOH axial groups are disordered and the RuN4 portions of the molecules are planar. The deviations from planarity of the porphyrinato core are very small. The Ru—C—S groups are essentially linear with an average Ru—C—S bond angle of 174 (1)°. The mean Ru—C(CS) and Ru—O (Et) bond lengths are 1.92 (4) and 2.15 (3) Å, respectively.

Combining cross-crystal averaging and MRSAD to phase a 4354-amino-acid structure

2016 ◽  
Vol 72 (2) ◽  
pp. 182-191
Author(s):  
Jason Nicholas Busby ◽  
J. Shaun Lott ◽  
Santosh Panjikar
Keyword(s):  
Radiation Damage ◽  
Model Building ◽  
Data Sets ◽  
Low Resolution ◽  
Data Set ◽  
C Protein ◽  
Large Size ◽  
Anomalous Signal ◽  
Difference Fourier ◽  
Combined Data

The B and C proteins from the ABC toxin complex ofYersinia entomophagaform a large heterodimer that cleaves and encapsulates the C-terminal toxin domain of the C protein. Determining the structure of the complex formed by B and the N-terminal region of C was challenging owing to its large size, the non-isomorphism of different crystals and their sensitivity to radiation damage. A native data set was collected to 2.5 Å resolution and a non-isomorphous Ta6Br12-derivative data set was collected that showed strong anomalous signal at low resolution. The tantalum-cluster sites could be found, but the anomalous signal did not extend to a high enough resolution to allow model building. Selenomethionine (SeMet)-derivatized protein crystals were produced, but the high number (60) of SeMet sites and the sensitivity of the crystals to radiation damage made phasing using the SAD or MAD methods difficult. Multiple SeMet data sets were combined to provide 30-fold multiplicity, and the low-resolution phase information from the Ta6Br12data set was transferred to this combined data set by cross-crystal averaging. This allowed the Se atoms to be located in an anomalous difference Fourier map; they were then used inAuto-Rickshawfor multiple rounds of autobuilding and MRSAD.

scholarly journals Determination of zinc incorporation in the Zn-substituted gallophosphate ZnULM-5 by multiple wavelength anomalous dispersion techniques

2010 ◽  
Vol 66 (3) ◽  
pp. 345-357 ◽  
Author(s):  
M. Helliwell ◽  
J. R. Helliwell ◽  
V. Kaucic ◽  
N. Zabukovec Logar ◽  
S. J. Teat ◽  
...  
Keyword(s):  
Single Crystal ◽  
Metal Atom ◽  
Absorption Edge ◽  
Atom Type ◽  
Space Group ◽  
Multiple Wavelength ◽  
Single Crystal Study ◽  
Using Data ◽  
Difference Fourier

The location of isomorphously substituted zinc over eight crystallographically different gallium sites has been determined in a single-crystal study of the gallophosphate ZnULM-5, Ga_{(16-x)}Zn_x(PO4)14(HPO4)2(OH)2F7, [H3N{CH2}6NH3]4, 6H2O, in an 11 wavelength experiment, using data from Station 9.8, SRS Daresbury. The measurement of datasets around the K edges of both Ga and Zn, as well as two reference datasets away from each absorption edge, was utilized to selectively exploit dispersive differences of each metal atom type in turn, which allowed the major sites of Zn incorporation to be identified as the metal 1 and 3 sites, M1 and M3. The preferential substitution of Zn at these sites probably arises because they are located in double four-ring (D4R) building units which can relax to accommodate the incorporation of hetero atoms. As the crystal is non-centrosymmetric, with space group P21212, it was also possible to use anomalous differences to corroborate the results obtained from the dispersive differences. These results were obtained firstly from difference Fourier maps, calculated using a phase set from the refined structure from data measured at the Zr K edge. Also, refined dispersive and anomalous occupancies, on an absolute scale, could be obtained using the program MLPHARE, allowing estimates for the Zn incorporation of approximately 22 and 18 at. % at the M1 and M3 sites to be obtained. In addition, f′ and f′′ values for Ga and Zn at each wavelength could be estimated both from MLPHARE results, and by refinement in JANA2006. The fully quantitative determinations of the dispersive and anomalous coefficients for Ga and Zn at each wavelength, as well as metal atom occupancies over the eight metal atom sites made use of the CCP4's MLPHARE program as well as SHELXL and JANA2006. The results by these methods agree closely, and JANA2006 allowed the ready determination of standard uncertainties on the occupancy parameters, which were for M1 and M3, 20.6 (3) and 17.2 (3) at %, respectively.

scholarly journals Can I solve my structure by SAD phasing? Anomalous signal in SAD phasing

2016 ◽  
Vol 72 (3) ◽  
pp. 346-358 ◽  
Author(s):  
Thomas C. Terwilliger ◽  
Gábor Bunkóczi ◽  
Li-Wei Hung ◽  
Peter H. Zwart ◽  
Janet L. Smith ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Atomic Displacement ◽  
Peak Height ◽  
High Ratio ◽  
Data Set ◽  
High Data ◽  
Sad Phasing ◽  
Anomalous Signal ◽  
Displacement Factor ◽  
Difference Fourier

A key challenge in the SAD phasing method is solving a structure when the anomalous signal-to-noise ratio is low. A simple theoretical framework for describing measurements of anomalous differences and the resulting useful anomalous correlation and anomalous signal in a SAD experiment is presented. Here, the useful anomalous correlation is defined as the correlation of anomalous differences with ideal anomalous differences from the anomalous substructure. The useful anomalous correlation reflects the accuracy of the data and the absence of minor sites. The useful anomalous correlation also reflects the information available for estimating crystallographic phases once the substructure has been determined. In contrast, the anomalous signal (the peak height in a model-phased anomalous difference Fourier at the coordinates of atoms in the anomalous substructure) reflects the information available about each site in the substructure and is related to the ability to find the substructure. A theoretical analysis shows that the expected value of the anomalous signal is the product of the useful anomalous correlation, the square root of the ratio of the number of unique reflections in the data set to the number of sites in the substructure, and a function that decreases with increasing values of the atomic displacement factor for the atoms in the substructure. This means that the ability to find the substructure in a SAD experiment is increased by high data quality and by a high ratio of reflections to sites in the substructure, and is decreased by high atomic displacement factors for the substructure.

Anomalous dispersion analyses of the Ni-atom site in an aluminophosphate test crystal including the use of tuned synchrotron radiation

1996 ◽  
Vol 52 (3) ◽  
pp. 479-486 ◽  
Author(s):  
M. Helliwell ◽  
J. R. Helliwell ◽  
A. Cassetta ◽  
J. C. Hanson ◽  
T. Ericsson ◽  
...  
Keyword(s):  
Synchrotron Radiation ◽  
Data Sets ◽  
Acta Cryst ◽  
Data Set ◽  
Difference Map ◽  
Chemical Crystallography ◽  
Synchrotron Light ◽  
The Difference ◽  
Difference Fourier ◽  
Atom Position

Data were collected close to the Ni K edge, using synchrotron radiation at the National Synchrotron Light Source, and using a Mo Kα rotating anode, from a crystal of a nickel-containing aluminophosphate, NiAl3P4O18C4H21N4 (NiAPO). These data sets, along with an existing Cu Kα rotating anode data set, allowed the calculation of several f′ difference-Fourier maps exploiting the difference in f′ for Ni between the various wavelengths. These differences are expected to be 7.8, 4.5 and 3.3 e for Mo Kα data to SR (synchrotron radiation), Cu Kα to SR and Mo Kα to Cu Kα, respectively. The phases were calculated either excluding the Ni atom or with Al at the Ni-atom site. The f′ difference-Fourier maps revealed peaks at the Ni-atom site, whose height and distance from the refined Ni-atom position depended on the f' difference and the phase set used. The largest peak was located at a distance of only 0.025 Å from the refined Ni-atom site and was obtained from the f′ difference map calculated with the coefficients |F Mo Kα − F SR| , using phases calculated with Al at the Ni-atom site. In all cases, it was found that these phases gave optimal results without introducing bias into the maps. The results confirm and expand upon earlier results [Helliwell, Gallois, Kariuki, Kaučič & Helliwell (1993), Acta Cryst. B49, 420–428]. The techniques described are generally applicable to other systems containing anomalous scatterers in chemical crystallography.

scholarly journals The predictive power of data-processing statistics

IUCrJ ◽  
2020 ◽  
Vol 7 (2) ◽  
pp. 342-354
Author(s):  
Melanie Vollmar ◽  
James M. Parkhurst ◽  
Dominic Jaques ◽  
Arnaud Baslé ◽  
Garib N. Murshudov ◽  
...  
Keyword(s):  
Data Processing ◽  
Anomalous Dispersion ◽  
Data Sets ◽  
Predictive Tool ◽  
Data Set ◽  
X Ray Crystallography ◽  
Multiple Wavelength ◽  
Data Rates ◽  
Starting Point ◽  
Computational Resources

This study describes a method to estimate the likelihood of success in determining a macromolecular structure by X-ray crystallography and experimental single-wavelength anomalous dispersion (SAD) or multiple-wavelength anomalous dispersion (MAD) phasing based on initial data-processing statistics and sample crystal properties. Such a predictive tool can rapidly assess the usefulness of data and guide the collection of an optimal data set. The increase in data rates from modern macromolecular crystallography beamlines, together with a demand from users for real-time feedback, has led to pressure on computational resources and a need for smarter data handling. Statistical and machine-learning methods have been applied to construct a classifier that displays 95% accuracy for training and testing data sets compiled from 440 solved structures. Applying this classifier to new data achieved 79% accuracy. These scores already provide clear guidance as to the effective use of computing resources and offer a starting point for a personalized data-collection assistant.

Difference Fourier Analysis of Glucose Embedded and Frozen Hydrated Purple Membrane

1982 ◽  
Vol 40 ◽  
pp. 74-75
Author(s):  
Jules S. Jaffe ◽  
Robert M. Glaeser
Keyword(s):  
Purple Membrane ◽  
Data Set ◽  
High Resolution Data ◽  
X Ray ◽  
X Ray Crystallography ◽  
Fourier Techniques ◽  
Versus Protein ◽  
The Difference ◽  
Difference Fourier ◽  
Ideal Method

Although difference Fourier techniques are standard in X-ray crystallography it has only been very recently that electron crystallographers have been able to take advantage of this method. We have combined a high resolution data set for frozen glucose embedded Purple Membrane (PM) with a data set collected from PM prepared in the frozen hydrated state in order to visualize any differences in structure due to the different methods of preparation. The increased contrast between protein-ice versus protein-glucose may prove to be an advantage of the frozen hydrated technique for visualizing those parts of bacteriorhodopsin that are embedded in glucose. In addition, surface groups of the protein may be disordered in glucose and ordered in the frozen state. The sensitivity of the difference Fourier technique to small changes in structure provides an ideal method for testing this hypothesis.

The social wasp Vespula germanica (Fabricius) (Hymenoptera: Vespidae) population dynamics in England over 39 years.

2018 ◽  
Vol 154 (2) ◽  
pp. 149-155
Author(s):  
Michael Archer
Keyword(s):  
Population Dynamics ◽  
Population Dynamic ◽  
Ecological Factors ◽  
Social Wasp ◽  
Data Sets ◽  
Data Set ◽  
Vespula Germanica ◽  
The Social ◽  
Minimum Number ◽  
Suction Traps

1. Yearly records of worker Vespula germanica (Fabricius) taken in suction traps at Silwood Park (28 years) and at Rothamsted Research (39 years) are examined. 2. Using the autocorrelation function (ACF), a significant negative 1-year lag followed by a lesser non-significant positive 2-year lag was found in all, or parts of, each data set, indicating an underlying population dynamic of a 2-year cycle with a damped waveform. 3. The minimum number of years before the 2-year cycle with damped waveform was shown varied between 17 and 26, or was not found in some data sets. 4. Ecological factors delaying or preventing the occurrence of the 2-year cycle are considered.

Predictive and Descriptive CoMFA Models: The Effect of Variable Selection

2018 ◽  
Vol 21 (2) ◽  
pp. 117-124 ◽  
Author(s):  
Bakhtyar Sepehri ◽  
Nematollah Omidikia ◽  
Mohsen Kompany-Zareh ◽  
Raouf Ghavami
Keyword(s):  
Variable Selection ◽  
Predictive Power ◽  
Selection Method ◽  
Data Sets ◽  
Data Set ◽  
Comfa Model ◽  
Variable Selection Method

Aims & Scope: In this research, 8 variable selection approaches were used to investigate the effect of variable selection on the predictive power and stability of CoMFA models. Materials & Methods: Three data sets including 36 EPAC antagonists, 79 CD38 inhibitors and 57 ATAD2 bromodomain inhibitors were modelled by CoMFA. First of all, for all three data sets, CoMFA models with all CoMFA descriptors were created then by applying each variable selection method a new CoMFA model was developed so for each data set, 9 CoMFA models were built. Obtained results show noisy and uninformative variables affect CoMFA results. Based on created models, applying 5 variable selection approaches including FFD, SRD-FFD, IVE-PLS, SRD-UVEPLS and SPA-jackknife increases the predictive power and stability of CoMFA models significantly. Result & Conclusion: Among them, SPA-jackknife removes most of the variables while FFD retains most of them. FFD and IVE-PLS are time consuming process while SRD-FFD and SRD-UVE-PLS run need to few seconds. Also applying FFD, SRD-FFD, IVE-PLS, SRD-UVE-PLS protect CoMFA countor maps information for both fields.

Human Activity Recognition using Fourier Transform Inspired Deep Learning Combination Model

2019 ◽  
Vol 9 (1) ◽  
pp. 16-31
Author(s):  
Kyungkoo Jun
Keyword(s):  
Fourier Transform ◽  
Deep Learning ◽  
Short Term Memory ◽  
Window Size ◽  
Sensor Data ◽  
Data Sets ◽  
Data Set ◽  
Proposed Model ◽  
Testing Data ◽  
Labeling Scheme

Background & Objective: This paper proposes a Fourier transform inspired method to classify human activities from time series sensor data. Methods: Our method begins by decomposing 1D input signal into 2D patterns, which is motivated by the Fourier conversion. The decomposition is helped by Long Short-Term Memory (LSTM) which captures the temporal dependency from the signal and then produces encoded sequences. The sequences, once arranged into the 2D array, can represent the fingerprints of the signals. The benefit of such transformation is that we can exploit the recent advances of the deep learning models for the image classification such as Convolutional Neural Network (CNN). Results: The proposed model, as a result, is the combination of LSTM and CNN. We evaluate the model over two data sets. For the first data set, which is more standardized than the other, our model outperforms previous works or at least equal. In the case of the second data set, we devise the schemes to generate training and testing data by changing the parameters of the window size, the sliding size, and the labeling scheme. Conclusion: The evaluation results show that the accuracy is over 95% for some cases. We also analyze the effect of the parameters on the performance.

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