A novel short neurotoxin, cobrotoxin c, from monocellate cobra (Naja kaouthia) venom: isolation and purification, primary and secondary structure determination, and tertiary structure modeling

A novel short neurotoxin, cobrotoxin c (CBT C) was isolated from the venom of monocellate cobra (Naja kaouthia) using a combination of ion-exchange chromatography and FPLC. Its primary structure was determined by Edman degradation. CBT C is composed of 61 amino acid residues. It differs from cobrotoxin b (CBT B) by only two amino acid substitutions, Thr/Ala11 and Arg/Thr56, which are not located on the functionally important regions by sequence similarity. However, the LD50 is 0.08 mg/g to mice, i.e. approximately five-fold higher than for CBT B. Strikingly, a structure-function relationship analysis suggests the existence of a functionally important domain on the outside of Loop III of CBT C. The functionally important basic residues on the outside of Loop III might have a pairwise interaction with alpha subunit, instead of gamma or delta subunits of the nicotinic acetylcholine receptor (nAChR). (C) 2002 Elsevier Science Inc. All rights reserved.

Phylogenetic analyses of Fringillidae (Aves : Passeriformes) using mitochondrial tRNA gene sequences and secondary structure

Fringillidae is a large and diverse family of Passeriformes. So far, however, Fringillidae relationships deduced from morphological features and by a number of molecular approaches have remained unproven. Recently, much attention has been attracted to mitochondrial tRNA genes, whose sequence and secondary structural characteristics have shown to be useful for Acrodont Lizards and deep-branch phylogenetic studies. In order to identify useful phylogenetic markers and test Fringillidae relationships, we have sequenced three major clusters of mitochondrial tRNA genes from 15 Fringillidae, taxa. A coincident tree, with coturnix as outgroup, was obtained through Maximum-likelihood method using combined dataset of 11 mitochondrial tRNA gene sequences. The result was similar to that through Neighbor-joining but different from Maximum-parsimony methods. Phylogenetic trees constructed with stem-region sequences of 11 genes had many different topologies and lower confidence than with total sequences. On the other hand, some secondary structural characteristics may provide phylogenetic information on relatively short internal branches at under-genus level. In summary, our data indicate that mitochondrial tRNA genes can achieve high confidence on Fringillidae phylogeny at subfamily level, and stem-region sequences may be suitable only at above-family level. Secondary structural characteristics may also be useful to resolve phylogenetic relationship between different genera of Fringillidae with good performance.

Secondary structure of yeast genomic downstream region and polyadenylation signals

Polyadenylation of 3 ' -forming in eukaryote concerns three elements located in precursor mRNA downstream region: efficiency element (EE), position element (PE) and the actual site for cleavage and polyadenylation. Several base sequences of EE and PE have

Phylogenetic analysis of the family Thermaceae with an emphasis on signature position and secondary structure of 16S rRNA

The sequences of the 16S rRNA genes from 38 strains of the family Thermaceae were compared by alignment analysis. The genus-specific and species-specific base substitutions or base deletions (signature positions) were found in three hypervariable regions (in the helices 6, 10 and 17). The differentiation of secondary structures of the high variable regions in the 5' end (38-497) containing several signature positions further supported the concept. Based on the comparisons of the secondary structures in the segments of 16S rRNAs, a key to the species of the family Thermaceae was proposed. (C) 2003 Published by Elsevier Science B.V. on behalf of the Federation of European Microbiological Societies.

The relation between translation speed and protein secondary structure

Based on the statistical analysis of 119 human and 92 E. coli proteins it was found that for both human and E. coli, the mRNA sequences consisting of tri-codon and tetra-codon with high translation speed preferably code for alpha helices more than for coils. For beta strand, the preference/ avoidance oscillates with the translation speed. Moreover, the non-homogeneous usages of tri-codon and tetra-codon with different translation speeds in a given secondary structure have also been found. These results cannot be simply explained by the effect of stochastic fluctuation.

Statistical correlation between protein secondary structure and messenger RNA stem-loop structure

Anew integrated sequence-structure database, called IADE (Integrated ASTRAL-DSSP-EMBL), incorporating matching mRNA sequence, amino acid sequence, and protein secondary structural data, is constructed. It includes 648 protein domains. Based on the IADE database, we studied the relation between RNA stem-loop frequencies and protein secondary structure. It was found that the alpha-helices and beta-strands on proteins tend to be preferably "coded" by mRNA stem region, while the coils on proteins tend to be preferably "coded" by mRNA loop region. These tendencies are more obvious if we observe the structural words (SWs). An SW is defined by a four-amino-acid-fragment that shows the pronounced secondary structural (alpha-helix or beta-strand) propensity. It is demonstrated that the deduced correlation between protein and mRNA structure can hardly be explained as the stochastic fluctuation effect. (C) 2003 Wiley Periodicals, Inc.

Variation patterns of the mitochondrial 16S rRNA gene with secondary structure constraints and their application to phylogeny of cyprinine fishes (Teleostei : Cypriniformes)

The mitochondrial 16S ribosomal RNA (rRNA) gene sequences from 93 cyprinid fishes were examined to reconstruct the phylogenetic relationships within the diverse and economically important subfamily Cyprininae. Within the subfamily a biased nucleotide composition (A > T, C > G) was observed in the loop regions of the gene, and in stem regions apparent selective pressures of base pairing showed a bias in favor of G over C and T over A. The bias may be associated with transition-transversion bias. Rates of nucleotide substitution were lower in stems than in loops. Analysis of compensatory substitutions across these taxa demonstrates 68% covariation in the gene and a logical weighting factor to account for dependence in mutations for phylogenetic inference should be 0.66. Comparisons of varied stem-loop weighting schemes indicate that the down-weightings for stem regions could improve the phylogenetic analysis and the degree of non-independence of stem substitutions was not as important as expected. Bayesian inference under four models of nucleotide substitution indicated that likelihood-based phylogenetic analyses were more effective in improving the phylogenetic performance than was weighted parsimony analysis. In Bayesian analyses, the resolution of phylogenies under the 16-state models for paired regions, incorporating GTR + G + I models for unpaired regions was better than those under other models. The subfamily Cyprininae was resolved as a monophyletic group, as well as tribe Labein and several genera. However, the monophyly of the currently recognized tribes, such as Schizothoracin, Barbin, Cyprinion + Onychostoma lineages, and some genera was rejected. Furthermore, comparisons of the parsimony and Bayesian analyses and results of variable length bootstrap analysis indicates that the mitochondrial 16S rRNA gene should contain important character variation to recover well-supported phylogeny of cyprinid taxa whose divergences occurred within the recent 8 MY, but could not provide resolution power for deep phylogenies spanning 10-19 MYA. (c) 2008 Published by Elsevier Inc.

Determination of the secondary structure of the king cobra neurotoxin CM-11

The king cobra neuotoxin CM-11 is a small protein with 72 amino acid residues. After its complete assignments of H-1-NMR resonance's were obtained using various 2D-NMR technologies, including of DQF-COSY, clean-TOCSY AND NOESY, the secondary structure was analysed by studying the various NOEs extracted from the NOESY spectra and the distribution of chemical shifts. The secondary structure was finally determined by MCD as follows: a triple-strand antiparallel beta sheet with I20-W36, R37-A43 and V53--S59 as its beta strands, a short alpha helix formed by W30-G35 and four turns formed by P7-K10, C14-G17, K50-V53 and D61-N64.

Secondary structure effects on DNA hybridization kinetics: a solution versus surface comparison

The hybridization kinetics for a series of designed 25mer probe�target pairs having varying degrees of secondary structure have been measured by UV absorbance and surface plasmon resonance (SPR) spectroscopy in solution and on the surface, respectively. Kinetic rate constants derived from the resultant data decrease with increasing probe and target secondary structure similarly in both solution and surface environments. Specifically, addition of three intramolecular base pairs in the probe and target structure slow hybridization by a factor of two. For individual strands containing four or more intramolecular base pairs, hybridization cannot be described by a traditional two-state model in solution-phase nor on the surface. Surface hybridization rates are also 20- to 40-fold slower than solution-phase rates for identical sequences and conditions. These quantitative findings may have implications for the design of better biosensors, particularly those using probes with deliberate secondary structure.

Algorithmic computation of knot polynomials of secondary structure elements of proteins

The classification of protein structures is an important and still outstanding problem. The purpose of this paper is threefold. First, we utilize a relation between the Tutte and homfly polynomial to show that the Alexander-Conway polynomial can be algorithmically computed for a given planar graph. Second, as special cases of planar graphs, we use polymer graphs of protein structures. More precisely, we use three building blocks of the three-dimensional protein structure-alpha-helix, antiparallel beta-sheet, and parallel beta-sheet-and calculate, for their corresponding polymer graphs, the Tutte polynomials analytically by providing recurrence equations for all three secondary structure elements. Third, we present numerical results comparing the results from our analytical calculations with the numerical results of our algorithm-not only to test consistency, but also to demonstrate that all assigned polynomials are unique labels of the secondary structure elements. This paves the way for an automatic classification of protein structures.