Structure data base

S. E. DeVoe, M. Storms, and K. Haraki, A.ntibiotics Properties and Structures Data Base, maintained at the Medical Research Division, American... 

A relatively complete listing of all surface geometries determined by LEED can be found in the NIST surface structure data base [2.250]. 

After the spectral matching process has been completed, the list of compounds with the top matching daughter spectra are identified and retrieved for each daughter spectrum in the reference compound. The molecular structures of the compounds with best matching spectra are drawn and compared for common substructures. The common substructures yield candidate spectrum/substructure correlations. Additional compounds are then tested to confirm or modify each correlation. Once the daughter spectrum is correlated with one or more substructures, this daughter spectrum is stored in the spectrum data base and is linked to the associated substructures stored in the structure data base. 

Inorganic Crystal Structure Data Base, FIZ Karlsruhe, 2002.. 

Molecular structure data bases are particularly useful in the analysis and engineering of zinc coordination polyhedra, and statistical results from the Brookhaven Protein Data Bank (Bernstein et al., 1977) and the Cambridge Structural Database (Allen et al., 1983) are presented... 

Recent research on the Cambridge structural data base shows139 11 alkenes (and 2 alkynes) which are involved in interactions with the —OH group, with distance H- C of olefin <2.4 A. 66 is an instance of intramolecular hydrogen bonding interactions140. Intermolecular hydrogen bonds can be observed in 67141 and 68142. 

The text has been substantially revised, many new examples incorporated and errors corrected. A substantial new chapter dealing with supramolecular chemistry has been incorporated. Once again, a deliberate decision was made to try to limit references to the secondary rather than the primary literature. Where structural data have been presented, the use of the files of the Cambridge Crystallographic Data Centre and the Brookhaven Protein Structure Data Base are gratefully acknowledged. 

Cambridge Structural Data Base (CSD). Cambridge Crystallographic Data Centre, University Chemical Laboratory, Cambridge, England. 

Inorganic Crystal Structural Data Base (ICSD). Fachinformationszentrum Karlsruhe, Germany. 

Muller K. Molecular modeling and structural data bases in pharmaceutical research. In Jensen B, Jorgensen FS, Kofod H, eds. Frontiers in Drug Research—Crystallographic and Computational Methods. Alfred Benzon Symposium No. 28, Jun 11-15, 1989, Copenhagen Munksgaard, 1990 210-221. 

Kovari, Z., Bocskei, Zs., Kassai, Cs., Fogassy, E., and Kozma, D. Investigation of the structural background of stereo- and enantioselectivity of 0,0 -dibenzoyl-(2/ ,3R)-tartaric acid-alcohol supramolecular compound formation, Chirality 2003, submitted for publication. Crystal data are deposited at the Cambridge Crystal Structure Data Base under the following numbers CCDC 181497, 181498, 181499,181500, 181501, 181502, 181503, 181504,181505. 

Experimental structures are often the basis for computational studies they are used as input structures for structure optimizations and conformational searches, for the parameterization and validation of force fields and for analyzing the effects of crystal lattices. More than 200,000 experimental structures have been reported, and the majority are found in the Cambridge Structural Data Base (CSD, small molecular structures which include carbon atoms) the Inorganic Crystals Structure Database (ICSD) and the Protein Data Base (PDB this database includes X-ray as well as optimized structures based on NMR data). 

A simultaneously performed search in the Cambridge Structural Data Base revealed that expanded X-C-C bond angles are more or less common (see Table 1) [13-15]. 

Since this structural data consists of atomic parameters which describe the interatomic vectors in three dimensions, the simultaneous evolvement of computer graphics has played an important role in the way the data can be used. The data base which is the particular source for the hydrogen bond data analyzed in this monograph is the Cambridge Crystallographic Structure Data Base [39, 40]. There is also a vast amount of structural information in the protein and nucleic acid data... 

Of all the physical sciences, Crystallography has benefited the most from the spectacular advances in computer technology in the past decade. The Cambridge Crytallographic Crystal Structure Data Base contains the results of the published crystal structure analyses of organic and organo-metallic compounds. The Protein... 

The possibility of errors in deposited structures must be considered. Errors in chirality may be prevalent in high resolution small molecule structures. For example, the small molecule structure of streptogramin A is represented by its enantiomer in the Cambridge Structural Data Base. The effort to solve the structure of streptogramin A bound to the ribosome was initially hindered by relying on that incorrect small molecule structure. Likewise, the structure of anisomycin is incorrectly diagrammed as its enantiomer in most of the ribosomal literature. Fortunately, these chirality errors were identified when solving structures of these antibiotics bound to macromolecules. In fact, the identification of these errors may increase confidence in the reliability of these structures of complexes between ribosomes and antibiotics. 

In Sect. C, the band structure data based on self-consistent relativistic augmented-plane-wave calculations performed by the author " are presented. Besides the electronic bands and the densities of states, the nature of the chemical bond is discussed. In Sect. D the electronic states in Zintl phases are compared with those having the B2 type of structure. As shown in Sect. B the B2 structure is closely related to the B32 structure. For intermetallic compounds the B2 structure seems to be the more natural because in this lattice all nearest neighbours of an atom A are B atoms. The reason why the compounds mentioned above crystallize in the B32 structure whereas similar compounds like LiTl and KTl form B2 phases has been frequently discussed in the literature 5 ... 

For a given surface structure, it is common to find many repeat determinations of the same system. For example, Ni(100)c(2x2)-0 has been the subject of no fewer than twenty independent determinations. Rather than list the raw results of all the determinations, we have taken a more discriminating, but less comprehensive, approach and have attempted to select just one, representative, determination for each distinct surface structure. The primary criteria used in selecting a particular determination were that it be recent, of relatively high accuracy, and represent a consensus of several contemporary determinations. Inevitably this means that some currently controversial, but correct, surface structures may have been omitted from this survey. For this reason, the reader wishing to obtain detailed information about one particular surface structure is encouraged to consult one of the surface structural data-bases or review articles listed in the selected bibliography found at the end of this chapter. 

One of the principal aims of this series of books is to collate and order up-to-date experimental data bases on cohesion and structure in order to reveal underlying trends that subsequent theoretical chapters might help elucidate. In this volume we consider the cohesion and structure of surfaces. During the past fifteen years there has been a dramatic increase in the number of different surfaces whose structures have been determined experimentally. For example, whereas in 1979 there were only 25 recorded adsorption structures, to date there are more than 250. In Chapter I Philip Rous presents a timely compilation of this structural data base on surfaces within a series of tables that allows easy direct comparison of structural parameters for related systems. Experimental structural trends amongst both clean surfaces and adsorbate systems are highlighted and discussed. 

S. J. Wodak and M. J, Rooman, Nature (London), 335,45(1988). Identification of Predictive Sequence Motifs Limited by Protein Structure Data Base Size. 

Bond distances are influenced by coordination environment and, secondarily, by the nature of the substituents (electronegativity and size). A least-squares analysis of approximately two-hundred silicon compounds taken from the Cambridge structural data base has provided a consistent set of reference values for bonds between silicon and various nonmetals and these values are shown in Table 3, as well as the values expected for single bonds to silicon corrected for electronegativity differences. 

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