Structural attributes of nucleotide sequences in promoter regions of supercoiling-sensitive genes: how to relate microarray expression data with genomic sequences

The level of supercoiling in the chromosome can affect gene expression. To clarify the basis of supercoiling sensitivity, we analyzed the structural features of nucleotide sequences in the vicinity of promoters for the genes with expression enhanced and decreased in response to loss of chromosomal supercoiling in E. coli. Fourier analysis of promoter sequences for supercoiling-sensitive genes reveals the tendency in selection of sequences with helical periodicities close to 10 nt for relaxation-induced genes and to 11 nt for relaxation-repressed genes. The helical periodicities in the subsets of promoters recognized by RNA polymerase with different sigma factors were also studied. A special procedure was developed for study of correlations between the intensities of periodicities in promoter sequences and the expression levels of corresponding genes. Significant correlations of expression with the AT content and with AT periodicities about 10, 11, and 50 nt indicate their role in regulation of supercoiling-sensitive genes.Comment: 38 pages, 12 figure

Representation of amino acid sequences in terms of interaction energy in protein globules

AbstractWe suggest a new simple approach for comparing the primary structure of proteins and their spatial structure. It relies on the one-to-one correspondence between each residue of the polypeptide chain and the energy of van der Waals interactions between the regions of the native globule flanking this residue. The method obviates the sophisticated geometrical criteria for estimating similarity between spatial structures. Besides, it permits one to analyze structural units of different scale

Hierarchy of regions of amino acid sequence with respect to their role in the protein spatial structure

The method of the representation of amino acid sequence by graph of the interactions energy between parts of spatial structure has been elaborated. Our method provides the possibility to establish the compatibility between each point of a polypeptide chain and the Van der Waals interactions energy of regions of a native globule adjacent to this amino acid residue. We have undertaken an exhaustive analysis of a set of proteins. Boundaries of domain and module structures have been found. Nonequivalence of different parts of sequences in respect to their contribution to stabilization of the spatial structure of the protein macromolecules has been revealed. On the basis of the number of energetic levels which are necessary to identify all independent parts of the globule, the contribution from each part of the sequence to stabilization of the spatial structure of the globule is de � ned. Thus, it has been found that the sequence of amino acid residues coincides with the sequence of the numerical values which can be used in turn in formal procedures, such as an alignment, a search of consensus, the recognition of composition peculiarities, etc. An example of the comparison of proteins with various sequence identities is considered to demonstrate the scheme of an alignment procedure. Key words: protein spatial structure, protein folding, interaction energy, hierarchy of domain structure, sequence alignment

Analysis of forces that determine helix formation in α-proteins

A model for prediction of α-helical regions in amino acid sequences has been tested on the mainly-α protein structure class. The modeling represents the construction of a continuous hypothetical α-helical conformation for the whole protein chain, and was performed using molecular mechanics tools. The positive prediction of α-helical and non-α-helical pentapeptide fragments of the proteins is 79%. The model considers only local interactions in the polypeptide chain without the influence of the tertiary structure. It was shown that the local interaction defines the α-helical conformation for 85% of the native α-helical regions. The relative energy contributions to the energy of the model were analyzed with the finding that the van der Waals component determines the formation of α-helices. Hydrogen bonds remain at constant energy independently whether α-helix or non-α-helix occurs in the native protein, and do not determine the location of helical regions. In contrast to existing methods, this approach additionally permits the prediction of conformations of side chains. The model suggests the correct values for ~60% of all χ-angles of α-helical residues

Core Promoter Regions of Antisense and Long Intergenic Non-Coding RNAs

RNA polymerase II (POL II) is responsible for the transcription of messenger RNAs (mRNAs) and long non-coding RNAs (lncRNAs). Previously, we have shown the evolutionary invariance of the structural features of DNA in the POL II core promoters of the precursors of mRNAs. In this work, we have analyzed the POL II core promoters of the precursors of lncRNAs in Homo sapiens and Mus musculus genomes. Structural analysis of nucleotide sequences in positions −50, +30 bp in relation to the TSS have shown the extremely heterogeneous 3D structure that includes two singular regions - hexanucleotide “INR” around the TSS and octanucleotide “TATA-box” at around ~−28 bp upstream. Thus, the 3D structure of core promoters of lncRNA resembles the architecture of the core promoters of mRNAs; however, textual analysis revealed differences between promoters of lncRNAs and promoters of mRNAs, which lies in their textual characteristics; namely, the informational entropy at each position of the nucleotide text of lncRNA core promoters (by the exception of singular regions) is significantly higher than that of the mRNA core promoters. Another distinguishing feature of lncRNA is the extremely rare occurrence in the TATA box of octanucleotides with the consensus sequence. These textual differences can significantly affect the efficiency of the transcription of lncRNAs

Structural coordinates: A novel approach to predict protein backbone conformation

Motivation Local protein structure is usually described via classifying each peptide to a unique class from a set of pre-defined structures. These classifications may differ in the number of structural classes, the length of peptides, or class attribution criteria. Most methods that predict the local structure of a protein from its sequence first rely on some classification and only then proceed to the 3D conformation assessment. However, most classification methods rely on homologous proteins' existence, unavoidably lose information by attributing a peptide to a single class or suffer from a suboptimal choice of the representative classes. Results To alleviate the above challenges, we propose a method that constructs a peptide's structural representation from the sequence, reflecting its similarity to several basic representative structures. For 5-mer peptides and 16 representative structures, we achieved the Q16 classification accuracy of 67.9%, which is higher than what is currently reported in the literature. Our prediction method does not utilize information about protein homologues but relies only on the amino acids' physicochemical properties and the resolved structures' statistics. We also show that the 3D coordinates of a peptide can be uniquely recovered from its structural coordinates, and show the required conditions under various geometric constraints