V. G. Tumanyan

DNA segmentation through the Bayesian approach.

We present a new approach to DNA segmentation into compositionally homogeneous blocks. The Bayesian estimator, which is applicable for both short and long segments, is used to obtain the measure of homogeneity. An exact optimal segmentation is found via the dynamic programming technique. After completion of the segmentation procedure, the sequence composition on different scales can be analyzed with filtration of boundaries via the partition function approach.

Comprehensive statistical analysis of residues interaction specificity at protein–protein interfaces

We calculated interchain contacts on the atomic level for nonredundant set of 4602 protein‐protein interfaces using an unbiased Voronoi‐Delaune tessellation method, and made 20×20 residue contact matrixes both for homodimers and heterocomplexes. The area of contacts and the distance distribution for these contacts were calculated on both the residue and the atomic levels. We analyzed residue area distribution and showed the existence of two types of interresidue contacts: stochastic and specific. We also derived formulas describing the distribution of contact area for stochastic and specific interactions in parametric form. Maximum pairing preference index was found for Cys‐Cys contacts and for oppositely charged interactions. A significant difference in residue contacts was observed between homodimers and heterocomplexes. Interfaces in homodimers were enriched with contacts between residues of the same type due to the effects of structure symmetry. Proteins 2007.

Hierarchy of the Interaction Energy Distribution in the Spatial Structure of Globular Proteins and the Problem of Domain Definition

An algorithm for determining of protein domain structure is proposed. Domain structures resulted from the algorithm application have been obtained and compared with available data. The method is based on entirely physical model of van der Waals interactions that reflects as illustrated in this work the distribution of electron density. Various levels of hierarchy in the protein spatial structure are discerned by analysis of the energy interaction between structural units of different scales. Thus the level of energy hierarchy plays role of sole parameter, and the method obviates the use of complicated geometrical criteria with numerous fitting parameters. The algorithm readily and accurately locates domains formed by continuous segments of the protein chain as well as those comprising non-sequential segments, sets no limit to the number of segments in a domain. We have analyzed 309 protein structures. Among 277 structures for which our results could be compared with the domain definitions made in other works, 243 showed complete or partial coincidence, and only in 34 cases the domain structures proved substantially different. The domains delineated with our approach may coincide with reference definition at different levels of the globule hierarchy. Along with defining the domain structure, our approach allows one to consider the protein spatial structure in terms of the spatial distribution of the interaction energy in order to establish the correspondence between the hierarchy of energy distribution and the hierarchy of structural elements.

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

We 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.

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.

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 (∼60%). Our method uses only frequencies of different conformations among oligopeptides without any additional parameters. We also attempted to predict α‐helices and β‐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). Proteins 2005.

Are knowledge‐based potentials derived from protein structure sets discriminative with respect to amino acid types?

The parametric description of residue environments through solvent accessibility, backbone conformation, or pairwise residue–residue distances is the key to the comparison between amino acid types at protein sequence positions and residue locations in structural templates (condition of protein sequence–structure match). For the first time, the research results presented in this study clarify and allow to quantify, on a rigorous statistical basis, to what extent the amino acid type‐specific distributions of commonly used environment parameters are discriminative with respect to the 20 amino acid types. Relying on the Bahadur theory, we estimate the probability of error in a single‐sequence–structure alignment based on weak or absent discriminative power in a learning database of protein structure. We present the results for many residue environment variables and demonstrate that each fold description parameter is sensitive with respect to only a few amino acid types while indifferent to most of the other amino acid types. Even complex structural characteristics combining solvent‐accessible surface area, backbone conformation, and pairwise distances distinguish only some amino acid types, whereas the others remain nondiscriminated. We find that the knowledge‐based potentials currently in use treat especially Ala, Asp, Gln, His, Ser, Thr, and Tyr as essentially “average” amino acids. Thus, highly discriminative amino acid types define the alignment register in gapless sequence–structure alignments. The introduction of gaps leads to alignment ambiguities at sequence positions occupied by nondiscriminated amino acid types. Therefore, local sequence–structure alignments produced by techniques with gaps cannot be reliable. Conceptionally new and more sensitive environment parameters must be invented. Proteins 31:225–246, 1998.

COOH-terminal decamers in proteins are non-random

© 1997 Federation of European Biochemical Societies.

Coexistence of different base periodicities in prokaryotic genomes as related to DNA curvature, supercoiling, and transcription

We analyzed the periodic patterns in E. coli promoters and compared the distributions of the corresponding patterns in promoters and in the complete genome to elucidate their function. Except the three-base periodicity, coincident with that in the coding regions and growing stronger in the region downstream from the transcriptions start (TS), all other salient periodicities are peaked upstream of TS. We found that helical periodicities with the lengths about B-helix pitch ~10.2-10.5 bp and A-helix pitch ~10.8-11.1 bp coexist in the genomic sequences. We mapped the distributions of stretches with A-, B-, and Z-like DNA periodicities onto E. coli genome. All three periodicities tend to concentrate within non-coding regions when their intensity becomes stronger and prevail in the promoter sequences. The comparison with available experimental data indicates that promoters with the most pronounced periodicities may be related to the supercoiling-sensitive genes.

On the optimal folding of protein molecules

The process of formation of a globular structure by a long molecular chain has been examined. In this process, various regions of the chain interact with one another. We classify the contacts thus formed as “correct” and “erroneous” ones. The correct contacts are those characteristic of the final native globular structure. All other contacts can be treated as erroneous. It is demonstrated that globule formation may proceed actually without formation and subsequent decay of erroneous contacts. Our model permits avoiding examination of numerous erroneous variants inasmuch as the regions of the chain that form correct contacts enter “long-range” interactions that at the same time can be highly selective. The existence of interactions of this kind facilitates the mutual approach and interaction of just those regions of the chain that yield correct contacts. Based on database analysis, it is shown that the model is valid not only for abstract structures but also for real polypeptide chains capable of forming protein globules and helical fibrils.