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Natalia G Esipova

Publications and source records attributed to Natalia G Esipova.

4 recordsLinked to original sources

Study and prediction of secondary structure for membrane proteins.

In this paper we present a novel approach to membrane protein secondary structure prediction based on the statistical stepwise discriminant analysis method. A new aspect of our approach is the possibility to derive physical-chemical properties that may affect the formation of membrane protein secondary structure. The certain physical-chemical properties of protein chains can be used to clarify the formation of the secondary structure types under consideration. Another aspect of our approach is that the results of multiple sequence alignment, or the other kinds of sequence alignment, are not used in the frame of the method. Using our approach, we predicted the formation of three main secondary structure types (alpha-helix, beta-structure and coil) with high accuracy, that is Q(3) = 76%. Predicting the formation of alpha-helix and non-alpha-helix states we reached the accuracy which was measured as Q(2) = 86%. Also we have identified certain protein chain properties that affect the formation of membrane protein secondary structure. These protein properties include hydrophobic properties of amino acid residues, presence of Gly, Ala and Val amino acids, and the location of protein chain end.

Amino Acid Sequence↗

A tetrapeptide-based method for polyproline II-type secondary structure prediction.

We describe a new method for polyproline II-type (PPII) secondary structure prediction based on tetrapeptide conformation properties using data obtained from all globular proteins in the Protein Data Bank (PDB). This is the first method for PPII prediction with a relatively high level of accuracy (approximately 60%). Our method uses only frequencies of different conformations among oligopeptides without any additional parameters. We also attempted to predict alpha-helices and beta-strands using the same approach. We find that the application of our method reveals interrelation between sequence and structure even for very short oligopeptides (tetrapeptides).

Databases, Protein↗

Analysis of forces that determine helix formation in alpha-proteins.

A model for prediction of alpha-helical regions in amino acid sequences has been tested on the mainly-alpha protein structure class. The modeling represents the construction of a continuous hypothetical alpha-helical conformation for the whole protein chain, and was performed using molecular mechanics tools. The positive prediction of alpha-helical and non-alpha-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 alpha-helical conformation for 85% of the native alpha-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 alpha-helices. Hydrogen bonds remain at constant energy independently whether alpha-helix or non-alpha-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 chi-angles of alpha-helical residues.

Amino Acid Sequence↗

Use of molecular mechanics for secondary structure prediction. Is it possible to reveal alpha-helix?

A new approach to predicting protein standard conformations is suggested. The idea consists in modeling by molecular mechanics tools a continuous alpha-helical conformation for the whole protein. The profile of energy along the model alpha-helix reveals minima corresponding to real alpha-helical segments in the native protein. The 3/10-helices and beta-turns including a local alpha-helical conformation may be detected as well. All alpha-helical segments in the test sample are delineated; mean residue by residue accuracy Q(3alpha) is 79%. This non-statistical approach can shed light on the physical grounds of alpha-helix formation.

Carrier Proteins↗