Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Natalya S. Bogatyreva is active.

Publication


Featured researches published by Natalya S. Bogatyreva.


Molecular Biology | 2008

Radius of gyration as an indicator of protein structure compactness

M. Yu. Lobanov; Natalya S. Bogatyreva; Oxana V. Galzitskaya

Identification and study of the main principles underlying the kinetics and thermodynamics of protein folding generate a new insight into the factors that control this process. Statistical analysis of the radius of gyration for 3769 protein domains of four major classes (α, β, α/β, and α + β) showed that each class has a characteristic radius of gyration that determines the protein structure compactness. For instance, α proteins have the highest radius of gyration throughout the protein size range considered, suggesting a less tight packing as compared with β-and (α + β)-proteins. The lowest radius of gyration and, accordingly, the tightest packing are characteristic of α/β-proteins. The protein radius of gyration normalized by the radius of gyration of a ball with the same volume is independent of the protein size, in contrast to compactness and the number of contacts per residue.


PLOS Computational Biology | 2010

Library of disordered patterns in 3D protein structures.

Michail Yu. Lobanov; Eugeniya I. Furletova; Natalya S. Bogatyreva; Michail A. Roytberg; Oxana V. Galzitskaya

Intrinsically disordered regions serve as molecular recognition elements, which play an important role in the control of many cellular processes and signaling pathways. It is useful to be able to predict positions of disordered regions in protein chains. The statistical analysis of disordered residues was done considering 34,464 unique protein chains taken from the PDB database. In this database, 4.95% of residues are disordered (i.e. invisible in X-ray structures). The statistics were obtained separately for the N- and C-termini as well as for the central part of the protein chain. It has been shown that frequencies of occurrence of disordered residues of 20 types at the termini of protein chains differ from the ones in the middle part of the protein chain. Our systematic analysis of disordered regions in PDB revealed 109 disordered patterns of different lengths. Each of them has disordered occurrences in at least five protein chains with identity less than 20%. The vast majority of all occurrences of each disordered pattern are disordered. This allows one to use the library of disordered patterns for predicting the status of a residue of a given protein to be ordered or disordered. We analyzed the occurrence of the selected patterns in three eukaryotic and three bacterial proteomes.


Nature | 2016

Local fitness landscape of the green fluorescent protein.

Karen S. Sarkisyan; Dmitry A. Bolotin; Margarita V. Meer; Dinara R. Usmanova; Alexander S. Mishin; George V. Sharonov; Dmitry N. Ivankov; Nina G. Bozhanova; Mikhail S. Baranov; Onuralp Soylemez; Natalya S. Bogatyreva; Peter K. Vlasov; Evgeny S. Egorov; Maria D. Logacheva; Alexey S. Kondrashov; Dmitry M. Chudakov; Ekaterina V. Putintseva; Ilgar Z. Mamedov; Dan S. Tawfik; Konstantin A. Lukyanov; Fyodor A. Kondrashov

Fitness landscapes depict how genotypes manifest at the phenotypic level and form the basis of our understanding of many areas of biology, yet their properties remain elusive. Previous studies have analysed specific genes, often using their function as a proxy for fitness, experimentally assessing the effect on function of single mutations and their combinations in a specific sequence or in different sequences. However, systematic high-throughput studies of the local fitness landscape of an entire protein have not yet been reported. Here we visualize an extensive region of the local fitness landscape of the green fluorescent protein from Aequorea victoria (avGFP) by measuring the native function (fluorescence) of tens of thousands of derivative genotypes of avGFP. We show that the fitness landscape of avGFP is narrow, with 3/4 of the derivatives with a single mutation showing reduced fluorescence and half of the derivatives with four mutations being completely non-fluorescent. The narrowness is enhanced by epistasis, which was detected in up to 30% of genotypes with multiple mutations and mostly occurred through the cumulative effect of slightly deleterious mutations causing a threshold-like decrease in protein stability and a concomitant loss of fluorescence. A model of orthologous sequence divergence spanning hundreds of millions of years predicted the extent of epistasis in our data, indicating congruence between the fitness landscape properties at the local and global scales. The characterization of the local fitness landscape of avGFP has important implications for several fields including molecular evolution, population genetics and protein design.


Nucleic Acids Research | 2009

KineticDB: a database of protein folding kinetics

Natalya S. Bogatyreva; Alexander Osypov; Dmitry N. Ivankov

We propose here KineticDB, a systematically compiled database of protein folding kinetics, which contains about 90 unique proteins. The main goal of the KineticDB is to provide users with a diverse set of protein folding rates determined experimentally. The search for determinants of protein folding is still in progress, aimed at obtaining a new understanding of the folding process. Comparison with experimental protein folding rates has been the main tool for validation of both theoretical models and empirical relationships during the last 10 years. It is, therefore, necessary to provide a researcher with as much data as possible in a simple and easy-to-use way. At present, the KineticDB contains the results of folding kinetics measurements of single-domain proteins and separate protein domains as well as short peptides without disulfide bonds. It includes data on about 90 unique proteins and many mutants that have been systematically accumulated over the last 10 years and is the largest collection of protein folding kinetic data presented as a database. The KineticDB is available at http://kineticdb.protres.ru/db/index.pl.


PLOS ONE | 2009

Coupling between Properties of the Protein Shape and the Rate of Protein Folding

Dmitry N. Ivankov; Natalya S. Bogatyreva; Michail Yu. Lobanov; Oxana V. Galzitskaya

There are several important questions on the coupling between properties of the protein shape and the rate of protein folding. We have studied a series of structural descriptors intended for describing protein shapes (the radius of gyration, the radius of cross-section, and the coefficient of compactness) and their possible connection with folding behavior, either rates of folding or the emergence of folding intermediates, and compared them with classical descriptors, protein chain length and contact order. It has been found that when a descriptor is normalized to eliminate the influence of the protein size (the radius of gyration normalized to the radius of gyration of a ball of equal volume, the coefficient of compactness defined as the ratio of the accessible surface area of a protein to that of an ideal ball of equal volume, and relative contact order) it completely looses its ability to predict folding rates. On the other hand, when a descriptor correlates well with protein size (the radius of cross-section and absolute contact order in our consideration) then it correlates well with the logarithm of folding rates and separates reasonably well two-state folders from multi-state ones. The critical control for the performance of new descriptors demonstrated that the radius of cross-section has a somewhat higher predictive power (the correlation coefficient is −0.74) than size alone (the correlation coefficient is −0.65). So, we have shown that the numerical descriptors of the overall shape-geometry of protein structures are one of the important determinants of the protein-folding rate and mechanism.


Proceedings of the National Academy of Sciences of the United States of America | 2013

Golden triangle for folding rates of globular proteins

Sergiy O. Garbuzynskiy; Dmitry N. Ivankov; Natalya S. Bogatyreva; Alexei V. Finkelstein

The ability of protein chains to spontaneously form their spatial structures is a long-standing puzzle in molecular biology. Experimentally measured rates of spontaneous folding of single-domain globular proteins range from microseconds to hours: the difference (11 orders of magnitude) is akin to the difference between the life span of a mosquito and the age of the universe. Here, we show that physical theory with biological constraints outlines a “golden triangle” limiting the possible range of folding rates for single-domain globular proteins of various size and stability, and that the experimentally measured folding rates fall within this narrow triangle built without any adjustable parameters, filling it almost completely. In addition, the golden triangle predicts the maximal size of protein domains that fold under solely thermodynamic (rather than kinetic) control. It also predicts the maximal allowed size of the “foldable” protein domains, and the size of domains found in known protein structures is in a good agreement with this limit.


Proteins | 2007

More compact protein globules exhibit slower folding rates

Oxana V. Galzitskaya; Danielle C. Reifsnyder; Natalya S. Bogatyreva; Dmitry N. Ivankov; Sergiy O. Garbuzynskiy

We have demonstrated that, among proteins of the same size, α/β proteins have on the average a greater number of contacts per residue due to their more compact (more “spherical”) structure, rather than due to tighter packing. We have examined the relationship between the average number of contacts per residue and folding rates in globular proteins according to general protein structural class (all‐α, all‐β, α/β, α+β). Our analysis demonstrates that α/β proteins have both the greatest number of contacts and the slowest folding rates in comparison to proteins from the other structural classes. Because α/β proteins are also known to be the oldest proteins, it can be suggested that proteins have evolved to pack more quickly and into looser structures. Proteins 2008.


Journal of Bioinformatics and Computational Biology | 2008

COMPACTNESS DETERMINES PROTEIN FOLDING TYPE

Oxana V. Galzitskaya; Natalya S. Bogatyreva; Dmitry N. Ivankov

We have demonstrated here that protein compactness, which we define as the ratio of the accessible surface area of a protein to that of the ideal sphere of the same volume, is one of the factors determining the mechanism of protein folding. Proteins with multi-state kinetics, on average, are more compact (compactness is 1.49+/-0.02 for proteins within the size range of 101-151 amino acid residues) than proteins with two-state kinetics (compactness is 1.59+/-0.03 for proteins within the same size range of 101-151 amino acid residues). We have shown that compactness for homologous proteins can explain both the difference in folding rates and the difference in folding mechanisms.


Nucleic Acids Research | 2013

QARIP: a web server for quantitative proteomic analysis of regulated intramembrane proteolysis

Dmitry N. Ivankov; Natalya S. Bogatyreva; Peter Hönigschmid; Bastian Dislich; Sebastian Hogl; Peer-Hendrik Kuhn; Dmitrij Frishman; Stefan F. Lichtenthaler

Regulated intramembrane proteolysis (RIP) is a critical mechanism for intercellular communication and regulates the function of membrane proteins through sequential proteolysis. RIP typically starts with ectodomain shedding of membrane proteins by extracellular membrane-bound proteases followed by intramembrane proteolysis of the resulting membrane-tethered fragment. However, for the majority of RIP proteases the corresponding substrates and thus, their functions, remain unknown. Proteome-wide identification of RIP protease substrates is possible by mass spectrometry-based quantitative comparison of RIP substrates or their cleavage products between different biological states. However, this requires quantification of peptides from only the ectodomain or cytoplasmic domain. Current analysis software does not allow matching peptides to either domain. Here we present the QARIP (Quantitative Analysis of Regulated Intramembrane Proteolysis) web server which matches identified peptides to the protein transmembrane topology. QARIP allows determination of quantitative ratios separately for the topological domains (cytoplasmic, ectodomain) of a given protein and is thus a powerful tool for quality control, improvement of quantitative ratios and identification of novel substrates in proteomic RIP datasets. To our knowledge, the QARIP web server is the first tool directly addressing the phenomenon of RIP. The web server is available at http://webclu.bio.wzw.tum.de/qarip/. This website is free and open to all users and there is no login requirement.


FEBS Letters | 2013

Restrictions to protein folding determined by the protein size

Alexei V. Finkelstein; Natalya S. Bogatyreva; Sergiy O. Garbuzynskiy

Experimentally measured rates of spontaneous folding of single‐domain globular proteins range from microseconds to hours: the difference (11 orders of magnitude!) is akin to the difference between the life span of a mosquito and the age of the Universe. We show that physical theory with biological constraints outlines the possible range of folding rates for single‐domain globular proteins of various size and stability, and that the experimentally measured folding rates fall within this narrow “golden triangle” built without any adjustable parameters, filling it almost completely. This “golden triangle” also successfully predicts the maximal allowed size of the “foldable” protein domains, as well as the maximal size of protein domains that fold under solely thermodynamic (rather than kinetic) control. In conclusion, we give a phenomenological formula for dependence of the folding rate on the size, shape and stability of the protein fold.

Collaboration


Dive into the Natalya S. Bogatyreva's collaboration.

Top Co-Authors

Avatar

Dmitry N. Ivankov

Russian Academy of Sciences

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Dinara R. Usmanova

Moscow Institute of Physics and Technology

View shared research outputs
Top Co-Authors

Avatar

M. Yu. Lobanov

Russian Academy of Sciences

View shared research outputs
Top Co-Authors

Avatar

Karen S. Sarkisyan

Institute of Science and Technology Austria

View shared research outputs
Top Co-Authors

Avatar

Alexander S. Mishin

Nizhny Novgorod State Medical Academy

View shared research outputs
Top Co-Authors

Avatar

Anna V. Glyakina

Russian Academy of Sciences

View shared research outputs
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge