The three dimensional structure and biological domains of the p53 C-terminus.

It was expected that there are a coil (289 similar to 325) and two a helix (alpha(1)368 similar to 373, alpha(2)381 similar to 388) structures in p53 protein C-terminal region based on its mRNA secondary structure template and Chou-Fasman's protein secondary structure principle of prediction. The result was conformed by the other four methods of protein secondary structure prediction that are based on the multiple sequence alignment (accuracy = 73.20%). Combine with the 31 amino acids crystal structure of the oligomerization, the three dimensional conformation of p53 C-terminal 108 residues was built using the SGI INDIGO(2) computer. This structure further expounds the relationship among those biological function domains of p53 C- terminus at three-dimensional level.

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.

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.

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.

Benchmarking secondary structure prediction for fold recognition

If secondary structure predictions are to be incorporated into fold recognition methods, an assessment of the effect of specific types of errors in predicted secondary structures on the sensitivity of fold recognition should be carried out. Here, we present a systematic comparison of different secondary structure prediction methods by measuring frequencies of specific types of error. We carry out an evaluation of the effect of specific types of error on secondary structure element alignment (SSEA), a baseline fold recognition method. The results of this evaluation indicate that missing out whole helix or strand elements, or predicting the wrong type of element, is more detrimental than predicting the wrong lengths of elements or overpredicting helix or strand. We also suggest that SSEA scoring is an effective method for assessing accuracy of secondary structure prediction and perhaps may also provide a more appropriate assessment of the “usefulness” and quality of predicted secondary structure, if secondary structure alignments are to be used in fold recognition.