Two-dimensional substructures

The structure of Np(Np02)2(Se03)3 is extraordinarily complex as it contains three crystallographically unique Np centers with three different coordination environments in two different oxidation states. Two of the Np centers are +V and one is +IV. The Np(V) centers are found as both NpOy pentagonal bipyramids and NpOs hexagonal bipyramids. The Np(IV) center is found as a distorted NpOs dodecahedron. Cation-cation interactions (CCTs), exist between both the neptunyl units, and these units also coordinate the Np(IV) center creating a two-dimensional substructure. There are three crystallographically unique selenite anions. 

Fourth, we have noted that the computational demands of three-dimensional substructure searching are much greater than those for conventional two-dimensional substructure searching. It is possible that recent developments in parallel computer hardware ° may provide a simple way of increasing the efficiency of three-dimensional substructure searching, and there have already been several reports of the use of parallel processing techniques for two-... 

Hagadone, T.R. Molecular substructure similarity searching efficient retrieval in two-dimensional structure databases. 

In contrast to DNA, RNAs do not form extended double helices. In RNAs, the base pairs (see p.84) usually only extend over a few residues. For this reason, substructures often arise that have a finger shape or clover-leaf shape in two-dimensional representations. In these, the paired stem regions are linked by loops. Large RNAs such as ribosomal 16S-rRNA (center) contain numerous stem and loop regions of this type. These sections are again folded three-dimensionally—i.e., like proteins, RNAs have a tertiary structure (see p.86). However, tertiary structures are only known of small RNAs, mainly tRNAs. The diagrams in Fig. B and on p.86 show that the clover-leaf structure is not recognizable in a three-dimensional representation. 

Hagadone, T. R. (1992) Molecular substructure similarity searching Efficient retrieval in two-dimensional structure databases../. Chem. Inf. Comput. Sci. 32, 515-521. 

Key experiments useful for substructure determination by NMR include the DEPT sequence (c.. Figs. 2.44-2.46) for analysis of CH multiplicities, as well as the two-dimensional CH correlation for identification of all CH bonds (e.g. Fig. 2.55 and Table 2.2) and localization of individual proton shifts. If, in addition, vicinal and longer-range proton-proton coupling relationships are known, all CH substructures of the sample molecule can be derived. Classical identification of homonuclear proton coupling relationships involves homonuclear proton decoupling. A two-dimensional proton-proton shift correlation would be an alternative and the complementary experiment to carbon-proton shift correlation. Several methods exist [68], Of those, the COSTsequence abbreviated from Correlation spectroscopy [69] is illustrated in Fig. 2.56. 

Fig. 2.57. Two-dimensional carbon-proton and proton-proton shift correlation for substructure determination of sample compound C9Hi5N03 (a) Carbon-proton shift correlation with proton broadband and gated decoupled IJCNMR spectra on top (b) COSY-45 proton-proton shift correlation with H-NMR spectra for reference (400.1 MHz 20 mg in 0.4 mL of tetradeuterio-methanol at 30 °C measuring times (a) 50 min (b) 25 min transform times for (a) and (b) 25 min).

Fig. 5.17. Carbon-13 signal assignment of aflatoxin B, [603] by two-dimensional carbon-proton shift correlation (30 mg in 0.4 mL of hexadeuteriodimethyl sulfoxide, 30 C, 100.576 MHz for 13C, 400.133 MHz for H full and strong contours correlations via one-bond couplings empty and weaker contours correlations via two- and Lhree-bond couplings). Boldface printed substructures in Lhe formula can be directly derived from this figure the carbon nucleus at 91.4 ppm, for example, is correlated with the proton at 6.72 ppm via one-bond coupling this proton is additionally correlated with the adjacent carbon nuclei at 165.1, 161.4, 107.2, and 103.5 ppm as indicated by correlation signals via two- and three-bond couplings.

The cover displays a stacked plot of a two-dimensional carbon-proton shift correlation. The plot is reprinted here with its numerical data. Isopinocampheoxyisoprene in deute-riochloroform is the sample. The aliphatic carbon and proton shift ranges are shown. All carbon-proton connectivities of the bicyclic substructure can be clearly derived, For example, the carbon atom whose signal occurs at 35.6 ppm is attached to the protons with signals at 1.76 and 2.37 ppm. These signals make up an AB system in the proton NMR spectrum and overlap with other proton signals in the one-dimensional spectrum. 

By observing sequential neutral losses, further information is obtained to determine the sequence of substructures or molecular connectivity within the analyte (Lee et al., 1996). This procedure is analogous to two-dimensional nuclear magnetic resonanse (NMR) techniques used to sequentially connect substructures. A familiar example of molecular connectivity is the determination of the amino acid sequence of a peptide. Specific neutral losses are diagnostic of specific amino acids, and the sequence of these losses identifies the peptide (Roepstorff and Fohlman, 1984). 

The structure may be described as molybdate clusters linked through copper octahedra into one-dimensional chains which are in turn cross-linked by ethylene-diphosphonate subunits into a two-dimensional network. The (Cu(bpy)(Mo40i2) (H20)2 2+ substructure is shown in Figure 18b. 

While four phases exhibit binuclear molybdate building blocks, three involve edge-sharing octahedra, but the fourth is an unusual example of a face-sharing binuclear unit. A curious feature of these structures is that two exhibit two-dimensional phosphomolybdate substructures, 12 and 16, while two contain onedimensional phosphomolybdate components, 10 and 11. 

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