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Author

Vladimir G. Tumanyan

Bio: Vladimir G. Tumanyan is an academic researcher from Engelhardt Institute of Molecular Biology. The author has contributed to research in topics: Protein structure & Protein structure prediction. The author has an hindex of 17, co-authored 81 publications receiving 1040 citations. Previous affiliations of Vladimir G. Tumanyan include Moscow Institute of Physics and Technology & Russian Academy of Sciences.


Papers
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Journal ArticleDOI
TL;DR: The PSIC approach has been applied to profile extraction and to the fold family assignment of protein sequences with known structures and was shown to be very productive in finding distantly related sequences and more powerful than Hidden Markov Models or the profile methods in WiseTools and PSI-BLAST in many cases.
Abstract: Sequence weighting techniques are aimed at balancing redundant observed information from subsets of similar sequences in multiple alignments. Traditional approaches apply the same weight to all positions of a given sequence, hence equal efficiency of phylogenetic changes is assumed along the whole sequence. This restrictive assumption is not required for the new method PSIC (position-specific independent counts) described in this paper. The number of independent observations (counts) of an amino acid type at a given alignment position is calculated from the overall similarity of the sequences that share the amino acid type at this position with the help of statistical concepts. This approach allows the fast computation of position-specific sequence weights even for alignments containing hundreds of sequences. The PSIC approach has been applied to profile extraction and to the fold family assignment of protein sequences with known structures. Our method was shown to be very productive in finding distantly related sequences and more powerful than Hidden Markov Models or the profile methods in WiseTools and PSI-BLAST in many cases. The profile extraction routine is available on the WWW (http://www.bork.embl-heidelberg. de/PSIC or http://www.imb.ac.ru/PSIC).

221 citations

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TL;DR: The complete process of the spider silk assembly is modeled using two new recombinant analogs of spidroins 1 and 2, and artificial structures with characteristics that are perspective for further biomedical applications, such as producing three-dimensional matrices for tissue engineering and drug delivery are obtained.
Abstract: Spider dragline silk possesses impressive mechanical and biochemical properties. It is synthesized by a couple of major ampullate glands in spiders and comprises of two major structural proteins—spidroins 1 and 2. The relationship between structure and mechanical properties of spider silk is not well understood. Here, we modeled the complete process of the spider silk assembly using two new recombinant analogs of spidroins 1 and 2. The artificial genes sequence of the hydrophobic core regions of spidroin 1 and 2 have been designed using computer analysis of existing databases and mathematical modeling. Both proteins were expressed in Pichia pastoris and purified using a cation exchange chromatography. Despite the absence of hydrophilic N- and C-termini, both purified proteins spontaneously formed the nanofibrils and round micelles of about 1 μm in aqueous solutions. The electron microscopy study has revealed the helical structure of a nanofibril with a repeating motif of 40 nm. Using the electrospinning, the thin films with an antiparallel β-sheet structure were produced. In summary, we were able to obtain artificial structures with characteristics that are perspective for further biomedical applications, such as producing three-dimensional matrices for tissue engineering and drug delivery.

75 citations

Journal ArticleDOI
TL;DR: Criteria allowing to specify conditions of preferred applicability for the local and the global alignment algorithms depending on positions and relative lengths of the cores and nonhomologous parts of the sequences to be aligned are revealed.
Abstract: Algorithms of sequence alignment are the key instruments for computer-assisted studies of biopolymers. Obviously, it is important to take into account the "quality" of the obtained alignments, i.e. how closely the algorithms manage to restore the "gold standard" alignment (GS-alignment), which superimposes positions originating from the same position in the common ancestor of the compared sequences. As an approximation of the GS-alignment, a 3D-alignment is commonly used not quite reasonably. Among the currently used algorithms of a pair-wise alignment, the best quality is achieved by using the algorithm of optimal alignment based on affine penalties for deletions (the Smith-Waterman algorithm). Nevertheless, the expedience of using local or global versions of the algorithm has not been studied. Using model series of amino acid sequence pairs, we studied the relative "quality" of results produced by local and global alignments versus (1) the relative length of similar parts of the sequences (their "cores") and their nonhomologous parts, and (2) relative positions of the core regions in the compared sequences. We obtained numerical values of the average quality (measured as accuracy and confidence) of the global alignment method and the local alignment method for evolutionary distances between homologous sequence parts from 30 to 240 PAM and for the core length making from 10% to 70% of the total length of the sequences for all possible positions of homologous sequence parts relative to the centers of the sequences. We revealed criteria allowing to specify conditions of preferred applicability for the local and the global alignment algorithms depending on positions and relative lengths of the cores and nonhomologous parts of the sequences to be aligned. It was demonstrated that when the core part of one sequence was positioned above the core of the other sequence, the global algorithm was more stable at longer evolutionary distances and larger nonhomologous parts than the local algorithm. On the contrary, when the cores were positioned asymmetrically, the local algorithm was more stable at longer evolutionary distances and larger nonhomologous parts than the global algorithm. This opens a possibility for creation of a combined method allowing generation of more accurate alignments.

62 citations

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TL;DR: An exhaustive statistical analysis of the amino acid sequences at the carboxyl (C) and amino (N) termini of proteins and of coding nucleic acid sequence at the 5' side of the stop codons found peculiarities at N-termini.
Abstract: An exhaustive statistical analysis of the amino acid sequences at the carboxyl (C) and amino (N) termini of proteins and of coding nucleic acid sequences at the 5' side of the stop codons was undertaken. At the N ends, Met and Ala residues are over-represented at the first (+1) position whereas at positions 2 and 5 Thr is preferred. These peculiarities at N-termini are most probably related to the mechanism of initiation of translation (for Met) and to the mechanisms governing the life-span of proteins via regulation of their degradation (for Ala and Thr). We assume that the C-terminal bias facilitates fixation of the C ends on the protein globule by a preference for charged and Cys residues. The terminal biases, a novel feature of protein structure, have to be taken into account when molecular evolution, three-dimensional structure, initiation and termination of translation, protein folding and life-span are concerned. In addition, the bias of protein termini composition is an important feature which should be considered in protein engineering experiments.

49 citations

Journal ArticleDOI
TL;DR: The Bayesian estimator, which is applicable for both short and long segments, is used to obtain the measure of homogeneity and an exact optimal segmentation is found via the dynamic programming technique.
Abstract: 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.

42 citations


Cited by
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Journal ArticleDOI
TL;DR: PolyPhen‐2 (Polymorphism Phenotyping v2), available as software and via a Web server, predicts the possible impact of amino acid substitutions on the stability and function of human proteins using structural and comparative evolutionary considerations.
Abstract: PolyPhen-2 (Polymorphism Phenotyping v2), available as software and via a Web server, predicts the possible impact of amino acid substitutions on the stability and function of human proteins using structural and comparative evolutionary considerations. It performs functional annotation of single-nucleotide polymorphisms (SNPs), maps coding SNPs to gene transcripts, extracts protein sequence annotations and structural attributes, and builds conservation profiles. It then estimates the probability of the missense mutation being damaging based on a combination of all these properties. PolyPhen-2 features include a high-quality multiple protein sequence alignment pipeline and a prediction method employing machine-learning classification. The software also integrates the UCSC Genome Browser's human genome annotations and MultiZ multiple alignments of vertebrate genomes with the human genome. PolyPhen-2 is capable of analyzing large volumes of data produced by next-generation sequencing projects, thanks to built-in support for high-performance computing environments like Grid Engine and Platform LSF.

2,681 citations

Journal ArticleDOI
TL;DR: A World Wide Web server is presented to predict the effect of an nsSNP on protein structure and function and the dependence of selective pressure on the structural and functional properties of proteins is studied.
Abstract: Human single nucleotide polymorphisms (SNPs) represent the most frequent type of human population DNA variation. One of the main goals of SNP research is to understand the genetics of the human phenotype variation and especially the genetic basis of human complex diseases. Non-synonymous coding SNPs (nsSNPs) comprise a group of SNPs that, together with SNPs in regulatory regions, are believed to have the highest impact on phenotype. Here we present a World Wide Web server to predict the effect of an nsSNP on protein structure and function. The prediction method enabled analysis of the publicly available SNP database HGVbase, which gave rise to a dataset of nsSNPs with predicted functionality. The dataset was further used to compare the effect of various structural and functional characteristics of amino acid substitutions responsible for phenotypic display of nsSNPs. We also studied the dependence of selective pressure on the structural and functional properties of proteins. We found that in our dataset the selection pressure against deleterious SNPs depends on the molecular function of the protein, although it is insensitive to several other protein features considered. The strongest selective pressure was detected for proteins involved in transcription regulation.

2,276 citations

Journal ArticleDOI
TL;DR: A web server to predict the functional effect of single or multiple amino acid substitutions, insertions and deletions using the prediction tool PROVEAN, which provides rapid analysis of protein variants from any organisms, and also supports high-throughput analysis for human and mouse variants at both the genomic and protein levels.
Abstract: Summary: We present a web server to predict the functional effect of single or multiple amino acid substitutions, insertions and deletions using the prediction tool PROVEAN. The server provides rapid analysis of protein variants from any organisms, and also supports high-throughput analysis for human and mouse variants at both the genomic and protein levels. Availability and implementation: The web server is freely available and open to all users with no login requirements at http://provean.jcvi.org. Contact: gro.ivcj@nahca Supplementary information: Supplementary data are available at Bioinformatics online.

1,886 citations

Journal ArticleDOI
TL;DR: This work has developed a straightforward and reliable method based on physical and comparative considerations that estimates the impact of an amino acid replacement on the three-dimensional structure and function of the protein.
Abstract: Single nucleotide polymorphisms (SNPs) constitute the bulk of human genetic variation, occurring with an average density of approximately 1/1000 nucleotides of a genotype. SNPs are either neutral allelic variants or are under selection of various strengths, and the impact of SNPs on fitness remains unknown. Identification of SNPs affecting human phenotype, especially leading to risks of complex disorders, is one of the key problems of medical genetics. SNPs in protein-coding regions that cause amino acid variants (non-synonymous cSNPs) are most likely to affect phenotypes. We have developed a straightforward and reliable method based on physical and comparative considerations that estimates the impact of an amino acid replacement on the three-dimensional structure and function of the protein. We estimate that approximately 20% of common human non-synonymous SNPs damage the protein. The average minor allele frequency of such SNPs in our data set was two times lower than that of benign non-synonymous SNPs. The average human genotype carries approximately 10(3) damaging non-synonymous SNPs that together cause a substantial reduction in fitness.

1,051 citations