Downloads & Free Reading Options - Results

Journal of Applied Crystallography was a journal covering the earth science, specifically cryststallography. It was established in 1968 and is published bi-monthly by Wiley-Blackwell Publishing Ltd. until 2016. Journal of Applied Crystallography was aimed at crystallographers and researchers using crystallography techniques in their work. Themes covered included synthesis and the molecular structures of various compounds, spectral studies, reports into uses and the application of crystallographic techniques.

In accordance with this URIP program, the following equipment has been acquired and installed: a FPS-164 MAX scientific computer with 1M words of memory, a matrix algebra accelerator, and FPS-164 MAX D64 disk subsystem with two drives. The scientific computing facility based on this equipment is now operational. It is housed in a specially constructed computer room in close proximity to the four principal departments involved in this activity. From the outset, the facility has been actively used for a range of research projects, including: (1) Methods for the solution of differential/algebraic equations with particular applications to sheet-metal forming and related problems in solid mechanics, (2) Development of computable error estimates of solutions of nonlinear boundary value problems for partial differential equations by finite element techniques, (3) Computational research in crystallography involving principally the determination of three-dimensional structures of biological macromolecules at atomic resolution by x-ray diffraction, (4) Computational methods for solution of parameterized equations with particular emphasis on bifurcation phenomena. (Author)

In accordance with this URIP program, the following equipment has been acquired and installed: a FPS-164 MAX scientific computer with 1M words of memory, a matrix algebra accelerator, and FPS-164 MAX D64 disk subsystem with two drives. The scientific computing facility based on this equipment is now operational. It is housed in a specially constructed computer room in close proximity to the four principal departments involved in this activity. From the outset, the facility has been actively used for a range of research projects, including: (1) Methods for the solution of differential/algebraic equations with particular applications to sheet-metal forming and related problems in solid mechanics, (2) Development of computable error estimates of solutions of nonlinear boundary value problems for partial differential equations by finite element techniques, (3) Computational research in crystallography involving principally the determination of three-dimensional structures of biological macromolecules at atomic resolution by x-ray diffraction, (4) Computational methods for solution of parameterized equations with particular emphasis on bifurcation phenomena. (Author)

This article is from PLoS ONE , volume 9 . Abstract Many bioscience fields employ high-throughput methods to screen multiple biochemical conditions. The analysis of these becomes tedious without a degree of automation. Crystallization, a rate limiting step in biological X-ray crystallography, is one of these fields. Screening of multiple potential crystallization conditions (cocktails) is the most effective method of probing a proteins phase diagram and guiding crystallization but the interpretation of results can be time-consuming. To aid this empirical approach a cocktail distance coefficient was developed to quantitatively compare macromolecule crystallization conditions and outcome. These coefficients were evaluated against an existing similarity metric developed for crystallization, the C6 metric, using both virtual crystallization screens and by comparison of two related 1,536-cocktail high-throughput crystallization screens. Hierarchical clustering was employed to visualize one of these screens and the crystallization results from an exopolyphosphatase-related protein from Bacteroides fragilis, (BfR192) overlaid on this clustering. This demonstrated a strong correlation between certain chemically related clusters and crystal lead conditions. While this analysis was not used to guide the initial crystallization optimization, it led to the re-evaluation of unexplained peaks in the electron density map of the protein and to the insertion and correct placement of sodium, potassium and phosphate atoms in the structure. With these in place, the resulting structure of the putative active site demonstrated features consistent with active sites of other phosphatases which are involved in binding the phosphoryl moieties of nucleotide triphosphates. The new distance coefficient, CDcoeff, appears to be robust in this application, and coupled with hierarchical clustering and the overlay of crystallization outcome, reveals information of biological relevance. While tested with a single example the potential applications related to crystallography appear promising and the distance coefficient, clustering, and hierarchal visualization of results undoubtedly have applications in wider fields.

This article is from PLoS ONE , volume 9 . Abstract Many bioscience fields employ high-throughput methods to screen multiple biochemical conditions. The analysis of these becomes tedious without a degree of automation. Crystallization, a rate limiting step in biological X-ray crystallography, is one of these fields. Screening of multiple potential crystallization conditions (cocktails) is the most effective method of probing a proteins phase diagram and guiding crystallization but the interpretation of results can be time-consuming. To aid this empirical approach a cocktail distance coefficient was developed to quantitatively compare macromolecule crystallization conditions and outcome. These coefficients were evaluated against an existing similarity metric developed for crystallization, the C6 metric, using both virtual crystallization screens and by comparison of two related 1,536-cocktail high-throughput crystallization screens. Hierarchical clustering was employed to visualize one of these screens and the crystallization results from an exopolyphosphatase-related protein from Bacteroides fragilis, (BfR192) overlaid on this clustering. This demonstrated a strong correlation between certain chemically related clusters and crystal lead conditions. While this analysis was not used to guide the initial crystallization optimization, it led to the re-evaluation of unexplained peaks in the electron density map of the protein and to the insertion and correct placement of sodium, potassium and phosphate atoms in the structure. With these in place, the resulting structure of the putative active site demonstrated features consistent with active sites of other phosphatases which are involved in binding the phosphoryl moieties of nucleotide triphosphates. The new distance coefficient, CDcoeff, appears to be robust in this application, and coupled with hierarchical clustering and the overlay of crystallization outcome, reveals information of biological relevance. While tested with a single example the potential applications related to crystallography appear promising and the distance coefficient, clustering, and hierarchal visualization of results undoubtedly have applications in wider fields.