Incorporation of a S-glycosidic linkage into a glyconucleoside changes the conformational preference of both furanose sugars

A glyconucleoside containing a thioglycoside linkage, namely 1-(3-S-beta-D-ribofuranosyl-2,3-dideoxy-3-thio-beta-D-ribofuranosyl)-thy mine, has been prepared through condensation of a suitably protected derivative of 3'-thiothymidine with an activated ribose sugar. NMR has been used to study the conformation of the S-disaccharide and the unmodified O-disaccharide. A full pseudorotational analysis showed that for the S-disaccharide, the ribose and deoxy ribose sugars have a preference for the south and north pucker, respectively; which is the reverse of what is seen for the O-disaccharide. (c) 2006 Elsevier Ltd. All rights reserved.

Predicting metal-binding site residues in low-resolution structural models

The accurate prediction of the biochemical function of a protein is becoming increasingly important, given the unprecedented growth of both structural and sequence databanks. Consequently, computational methods are required to analyse such data in an automated manner to ensure genomes are annotated accurately. Protein structure prediction methods, for example, are capable of generating approximate structural models on a genome-wide scale. However, the detection of functionally important regions in such crude models, as well as structural genomics targets, remains an extremely important problem. The method described in the current study, MetSite, represents a fully automatic approach for the detection of metal-binding residue clusters applicable to protein models of moderate quality. The method involves using sequence profile information in combination with approximate structural data. Several neural network classifiers are shown to be able to distinguish metal sites from non-sites with a mean accuracy of 94.5%. The method was demonstrated to identify metal-binding sites correctly in LiveBench targets where no obvious metal-binding sequence motifs were detectable using InterPro. Accurate detection of metal sites was shown to be feasible for low-resolution predicted structures generated using mGenTHREADER where no side-chain information was available. High-scoring predictions were observed for a recently solved hypothetical protein from Haemophilus influenzae, indicating a putative metal-binding site.

Genotypic differences in the growth of bananas (Musa spp.) infected with migratory endoparasitic nematodes. 1. Roots

The effects of nematodes on root morphology and the association of root characteristics with resistance to nematodes of seven banana varieties were investigated in two experiments. Banana plants were grown in controlled conditions within polytunnels and harvested on three occasions for the measurement of root morpholopy, and biomass. Varieties differed in their resistance to nematodes, from resistant (Yg Km5, FHIA 17, FHIA 03) and partly resistant (FHIA 01, FHIA 25) to not resistant ((FHIA 23, Williams). Nematodes reduced the root dry weight of FHIA 01, FHIA 17 and FHIA 23 at some harvests. Primary root number was on average 9.5% lower in nematode-infected plants than controls, with no differences among the varieties. Thus, there was no simple association between the resistance of these varieties and their tolerance to nematodes. Varieties differed in root morphology. Root dry weight was greatest for resistant varieties Yg Km5 and FHIA 03, and least for non-resistant varieties FHIA 23 and Williams. Thus, resistance to nematodes was associated with varieties with greater root mass and more and larger primary roots.