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Blue Flower

Details: Written by Super User; Category: Uncategorised; Published: 29 March 2020; Hits: 755

We have compiled the first and largest database of disordered patterns from the PDB (version from 28 June 2010).

New database ComSin including structures in bound and unbound states has been created.

A new method (IsUnstruct) based on the Ising model for prediction of disordered residues from protein sequence alone has been developed. According to this model, each residue can be in one of two states: ordered or disordered.

The kinetic scheme describing the amyloid formation process has been constructed taking into account the last experimental data. Computer simulation has shown that the model adequately describes the corresponding stages of amyloid formation.

Several additional scales obtained from the statistics of protein structures have been calculated for prediction of amyloidogenic regions using the amino acid sequence. One of them has been used both for the prediction of amyloidogenic regions and for the residues protected from hydrogen-deuterium exchange. Our analysis demonstrates that the involvement of the amino acid residues which are situated in amyloidogenic regions into the folding nucleus formation is more intensive than that of the residues which are in non-amyloidogenic regions.

Mechanical properties of two immunoglobulin-binding domains of proteins L and G which have similar spatial structures but different amino acid sequences have been investigated by using the method of molecular dynamics. The investigation of mechanical properties of proteins has shown that intermediate states appear on the unfolding pathways of proteins L and G. It turned out that protein G is more stable mechanically than protein L.

We are the first who have constructed a unique database of protein pairs from thermophililic and mesophilic organisms. Comparison of proteins from thermophilic and mesophilic organisms has shown that the first has more close packing of the exterior part of protein (external residues accessible for water molecules) than the second one. Packing of the interior part of proteins (residues not accessible for water molecules) is the same in both cases.

Estimation of the folding rates of globular proteins with known three dimensional structures has been obtained using the method of Monte Carlo. The obtained refolding time values correlate reasonably well with the experimental data. The search for the optimal relationship between the average conformational entropy and the average energy of interactions between contacts for fast folding has been done. We have demonstrated that, among proteins of the same size, alpha/beta proteins are the most compact and have the slowest folding rates. We have shown here that dimensionless structural parameters describing the protein shape have low correlation with protein folding rates. At the same time structural determinants taking into account both the protein shape and its size show good agreement with experimentally observed rates of protein folding.

Reliable differences in the details of internal construction of the same protein globules determined by X-ray analysis, on the one hand, and NMR on the other have been reveale

Details: Written by Super User; Category: Uncategorised; Published: 11 December 2019; Hits: 1180

Galzitskaya Oxana Valerianovna

Graduated from the Moscow Physical-Technical Institute (1990, Honorary Diploma).

Ph.D. in Biophysics (Institute of Theoretical and Experimental Biophysics, Pushchino, 1996).

D.Sc. in Biophysics (Institute of Theoretical and Experimental Biophysics, Pushchino, 2006).

Leading scientist, Head of the Bioinformatics groups at the Institute of Protein Research Russian Academy of Sciences (since 2008).

Author of about 80 scientific papers.

Awarded for Outstanding Russian Young Scientists, 1997 and for Doctor of Science of Russian Science Support Foundation.

Member of the Editorial Boards of ___Current Protein and Peptide Science___, ___Open Biochemistry___, ___Open Bioinformatics___, and ___Open Journal of Biochemistry___. Area of expertise: investigation of protein folding and misfolding, prediction of protein disorder and structure prediction, prediction of amyloidogenic regions and folding rates, mechanical unfolding of proteins.

Glyakina Anna Vladimirovna

Diploma degree in physics (2006) from Tula State University, Russia.

Now she is graduate student in the Laboratory of Molecular Dynamics, Institute of Mathematical Problems of Biology, Russian Academy of Sciences.

Area of expertise: protein physics, molecular biology, bioinformatics, mechanical unfolding of proteins.

Dovidchenko Nikita Vladimirovich

BS and MS degrees in Biology at The Murmansk State University, Russia.

Now he is graduate student in the group of bioinformatics, Institute of Protein Research, Russian Academy of Sciences (Puschchino, Moscow Region).

Lobanov Mikhail Yurievich

Researcher

SELIVANOVA Olga Mihaylovna. Ph.D. in molecular biology, electron microscopist This email address is being protected from spambots. You need JavaScript enabled to view it.
без зв. ГРИШИН Сергей Юрьевич - м.н.с., This email address is being protected from spambots. You need JavaScript enabled to view it.
к.ф.-м.н. ЛИХАЧЁВ Илья Вячеславович – ведущий инженер, This email address is being protected from spambots. You need JavaScript enabled to view it.
без зв. СЛИЗЕНЬ Михаил Валерьевич – магистрант (лаборант) This email address is being protected from spambots. You need JavaScript enabled to view it.
к.ф.-м.н. СУРИН Алексей Константинович - с.н.с., This email address is being protected from spambots. You need JavaScript enabled to view it..ru
без зв. СУВОРИНА Мария Юрьевна - м.н.с., This email address is being protected from spambots. You need JavaScript enabled to view it.
без зв. ГОРБАЧЕВА Ольга Сергеевна – инженер, This email address is being protected from spambots. You need JavaScript enabled to view it.
без зв. ЛЕТОВА Анастасия Александровна аспирант (ст. лаборант), This email address is being protected from spambots. You need JavaScript enabled to view it.
без зв. КУРПЕ Станислав Римасо, студент, This email address is being protected from spambots. You need JavaScript enabled to view it.

Details: Written by Super User; Category: Uncategorised; Published: 11 December 2019; Hits: 1171

Selected Publications

A.M. Gutin and O.V.Galzitskaia, Helix-coil transition in the simplest model of large native RNA. I. Consideration of only native helices. Biofizika (Russian), 38(1), 84-92 (1993)
PubMed
A.M. Gutin and O.V.Galzitskaia, Helix-coil transition in the simplest models of large native RNA. II. Consideration of nonspecific interactions. Biofizika (Russian), 38(1), 93-98 (1993)
PubMed
O.V. Galzitskaya, B.A. Reva and A.V. Finkelstein, Attainment of an energy minimum by a protein chain does not require a complete sorting of conformations: a computerized experiment and phenomenological theory. Molecular Biology (Russian), 28(6), 1412-1427 (1994)
PubMed
O.V. Galzitskaya and A.V. Finkelstein, Self-organization of protein chain accelerates upon stabilization of its native conformation. Numerical experiment. Molecular Biology (Russian), 29(2), 181-186 (1995)
O.V. Galzitskaya and A.V. Finkelstein, Folding of chains with random and edited sequences: similarities and differences. Protein Eng., 8(9), 883-892 (1995)
PubMed
A.V. Finkelstein and O.V. Galzitskaia, Turning speed and stability of a native structure in "random" and "edited" chains. Molecular Biology (Russian), 30(1), 145-155 (1996)
PubMed
O.V. Galzitskaya and A.V. Finkelstein, Computer simulation of secondary structure folding of random and "edited" RNA chains. J.Chem. Phys., 105(1), 319-325 (1996)
O.V. Galzitskaya and A.V. Finkelstein, A theoretical study of the dependence of rate of winding of RNA-like heteropolymers on the length of the chain. Molecular Biology (Russian), 31(3), 478-487 (1997)
PubMed
O.V. Galzitskaya, Effect of the energy of distant contacts on the time of finding the native structure for RNA-like heteropolymers. Molecular Biology (Russian), 31(3), 488-491 (1997)
PubMed
I.N. Serdiuk, O.V. Galzitskaia and A.A. Timchenko, Roughness of the globular protein surface. Biofizika (Russian), 42(6), 1197-207 (1997)
PubMed
O.V. Galzitskaia, Geometrical factor and physical reasons for its influence on the kinetic and thermodynamic properties of RNA-like heteropolymers. Fold Des., 2(3), 193-201 (1997)
PubMed
A.A. Timchenko, O.V. Galzitskaya and I.N. Serdyuk, Roughness of the globular protein surface: analysis of high resolution X-ray data. Proteins, 28(2), 194-201 (1997)
PubMed
A.A. Timchenko, O.V. Galzitskaya and I.N. Serdyuk, Roughness of the globular protein surface. JINR Rapid Communications, 4(90), 59-63 (1998)
O.V. Galzitskaya and A.V. Finkelstein, Folding rate dependence on the chain length of RNA-like heteropolymers. Fold Des., 3(2), 69-78 (1998)
PubMed
V.N. Uversky, S. Winter, O.V. Galzitskaya, L. Kittler and G. Lober, Hyperphosphorylation induces structural modification of tau-protein. FEBS Lett., 439(1-2), 21-25 (1998)
PubMed
O.V. Galzitskaya and A.V. Finkelstein, A theoretical search for folding/unfolding nuclei in three-dimensional protein structures. Proc Natl Acad Sci USA., 96(20), 11299-11304 (1999)
PubMed
V.N. Uversky, O.V. Galzitskaya, S. Winter, L. Kittler and G. Lober, Effect of hyperphosphorylation on structure of TAU protein. Tsitologiia (Russian), 41(6), 540-9 (1999)
PubMed
A.V. Skugarev, O.V. Galzitskaia and AV. Finkelstein, Search for folding nuclei in the spatial structure of proteins. Molecular Biology (Russian), 33(6), 1016-1026 (1999)
PubMed
O. Galzitskaya and A. Caflisch, Solution conformation of phakellistatin 8 investigated by molecular dynamics simulations. J Mol Graph Model., 17(1), 19-27 (1999)
PubMed
O.V. Galzitskaya, A.V. Skoogarev, D.N. Ivankov and A.V. Finkelstein, Folding nuclei in 3D protein structures. Proceedings of the Pacific Symposium on Biocomputing, 131-142 (2000)
PubMed
O.V. Galzitskaya, A.K. Surin and H. Nakamura, Optimal region of average side-chain entropy for fast protein folding. Protein Sci., 9(3), 580-586 (2000)
PubMed
O.V. Galzitskaya, J. Higo, M. Kuroda and H. Nakamura, β-hairpin folds by molecular dynamics simulations. Chemical Physics Letters, 326, 421-429 (2000)
J. Higo, O.V. Galzitskaya, S. Ono and H. Nakamura, Energy landscape of a β-hairpin peptide in explicit water studied by multicanonical molecular dynamics. Chemical Physics Letters, 337, 169-175 (2001)
O.V. Galzitskaya, D.N. Ivankov and A.V. Finkelstein, Folding nuclei in proteins. FEBS Lett., 489(2-3), 113-118 (2001)
O.V. Galzitskaya, D.N. Ivankov and A.V. Finkelstein, The state of art in steps of protein folding. Summer School "The prediction and mechanism of protein folding: from topology to intermediate states". (Chomilier,J., Labesse, G, and Sadoc, J.-F., eds.) Institute d'etudes scientifiques de Cargese, 8-19 (2001)
O.V. Galzitskaya, D.N. Ivankov and A.V. Finkelstein, Kinetics of folding nuclei formation in proteins. Molecular Biology (Russia), 35(4), 708-717 (2001)
PubMed
O.V. Galzitskaya, J. Higo and A.V. Finkelstein, α-helix and β-hairpin folding from experiment, analytical theory and molecular dynamics simulations. Current Protein and Peptide Science, 3(2), 191-200 (2002)
PubMed
O.V. Galzitskaya, Sensitivity of folding pathway to the details of amino-acid sequence. Molecular Biology (Russian), 36(3), 386-390 (2002)
PubMed
O.V. Galzitskaia, Folding of β-hairpins. Molecular Biology (Russian), 36(5), 755-760 (2002)
PubMed
K. Ikeda, O.V. Galzitskaya, H. Nakamura and J. Higo, β-hairpin, α-helices, and the intermediates among the secondary structures in the energy landscape of a peptide from a distal β-hairpin of SH3 domain. J.Comp. Chem., 24(3), 310-318 (2003)
PubMed
O.V. Galzitskaya, S.O. Garbuzynskiy, D.N. Ivankov and A.V. Finkelstein, Chain length is the main determinant of the folding rate for proteins with three-state folding kinetics. Protein, 51 (2), 162-166 (2003)
PubMed
O.V. Galzitskaya and B.S. Melnik, Prediction of protein domain boundaries from sequence alone. Protein Science, 12(4), 696-701 (2003)
PubMed
S.O. Garbuzynskiy, A.V. Finkelstein and O.V. Galzitskaya, Outlining folding nuclei in globular proteins. J. Mol. Biol., 336(2), 509-525 (2004)
PubMed
A.V. Finkelstein and O.V. Galzitskaya, Physics of protein folding. Physics of Life Reviews, 1, 23-56 (2004)
S.O. Garbuzynskiy, M.Yu. Lobanov and O.V. Galzitskaya, To be folded or to be unfolded? Protein Science, 13(11), 2871-2877 (2004)
PubMed
Sh.Suzuki, O.V. Galzitskaya, D. Mitomo and J. Higo, General dynamic properties of Aβ12-36 amyloid peptide involved in Alzheimer's disease from unfolding simulation. Eur. J. Biochem., 136(5), 583-594 (2004)
PubMed
V.V. Marchenkov, I.V. Sokolovskii, N.V. Kotova, O.V. Galzitskaya, E.S. Bochkareva, A.S. Girshovich and G.V. Semisotnov, The interaction of the GroEL chaperone with early kinetic intermediates of renaturing proteins inhibits the formation of their native structure. Biofizika (Russian), 49(6), 987-994 (2004)
PubMed
B.S. Melnik, S.O. Garbuzynskiy, M.Yu. Lobanov and O.V. Galzitskaya, The difference between protein structures that are obtained by X-ray analysis and magnetic resonance spectroscopy. Molecular Biology (Russian), 39(1), 129-38 (2005)
PubMed
A.V. Finkelstein, D.N. Ivankov and O.V. Galzitskaya, Prediction folding rates and folding nuclei in globular proteins on the basis of theory of their folding. Progress in biological chemistry (Russia), 45, 3-36 (2005)
O.V. Galzitskaya, S.O. Garbuzynskiy and A.V. Finkelstein, Theoretical study of protein folding: outlining folding nuclei and estimation of protein folding rates. Journal of Physics: Condensed Matter., 17, S1539-S1551 (2005)
S.O. Garbuzynskiy, B.S. Melnik, M.Yu.Lobanov, A.V. Finkelstein and O.V. Galzitskaya, Comparison of X-ray and NMR structures: is there a systematic difference in residue contacts between X-ray- and NMR-resolved protein structures? Protein, 60(1), 139-147 (2005)
PubMed
S.O. Garbuzynskiy, A.V. Finkelstein and O.V. Galzitskaya, On prediction of folding nuclei in globular proteins. Molecular Biology (Russian), 39(6), 1032-1041 (2005)
PubMed
O.V. Galzitskaya, N.V. Dovidchenko, M.Yu. Lobanov and S.O. Garbuzynskiy, Prediction of protein domain boundaries from statistics of appearance of amino acid residues. Molecular Biology (Russian), 40(1), 111-121 (2006)
PubMed
O.V. Galzitskaya, S.O. Garbuzynskiy and M.Yu. Lobanov, Prediction of natively unfolded regions in protein chains. Molecular Biology (Russian), 40(2) 341-348 (2006)
PubMed
O.V. Galzitskaya and S.O. Garbuzynskiy, Entropy capacity determines protein folding. Protein, 63(1), 144-154 (2006)
PubMed
O.V. Galzitskaya, S.O. Garbuzynskiy and M.Yu. Lobanov, Is it possible to predict amyloidogenic regions from sequence alone? Journal of Bioinformatics and Computational Biology (JBCB), 4(2), 373-88 (2006)
PubMed
O.V. Galzitskaya and S.O. Garbuzynskiy, Optimal relationship between average conformational entropy and average energy of residue interaction for fast protein folding. Biofizika (Russia), 51(4), 622-632 (2006)
PubMed
N.S. Bogatyreva, A.V. Finkelstein and O.V. Galzitskaya, Trend of amino acid compositions of different taxa. Journal of Bioinformatics and Computational Biology (JBCB), 4(2), 597-608 (2006)
PubMed
O.V. Galzitskaya, S.O. Garbuzynskiy and M.Yu. Lobanov, A search of amyloidogenic regions in protein chain. Molecular Biology (Russian), 40(5) 910-918 (2006)
PubMed
O.V. Galzitskaya, Identification of beta-aggregate sites in protein chain. Molecular Biology (Russian), 40(6) 931-936 (2006)
PubMed
O.V. Galzitskaya, S.O. Garbuzynskiy and M.Yu. Lobanov, FoldUnfold: web server for the prediction of disordered regions in protein chain. Bioinformatic, 22(23), 2948-2949 (2006)
PubMed
O.V. Galzitskaya, S.O. Garbuzynskiy and M.Yu. Lobanov, Prediction of Amyloidogenic and Disordered Regions in Protein Chain. PLoS Computational Biology, 2(12), e177 (2006)
PubMed
M.M. Savitski, F. Kjeldsen, M.L. Nielsen, S.O. Garbuzynskiy, O.V. Galzitskaya, A.K. Surin and R.A. Zubarev, Backbone Carbonyl Group Basicities Are Related to Gas-Phase Fragmentation of Peptides and Protein Folding. Angew Chem Int Ed Engl., 46(9), 1481-1484 (2007)
PubMed
N.V. Dovidchenko, M.Yu. Lobanov and O.V. Galzitskaya, Prediction of number and position of domain boundaries in multi-domain proteins by use of amino acid sequence alone. Current Protein and Peptide Science, 8(2), 189-195 (2007)
O.V. Galzitskaya, S.O. Garbuzynskiy and M.Yu. Lobanov, Expected packing density allows predicting both amyloidogenic and disordered regions in protein chain. Journal of Physics: Condensed Matter., 19(28), 285225 (2007)
A.V. Glyakina, M.Yu. Lobanov and O.V. Galzitskaya, Search for structural factors responsible for the stability of proteins from thermophilic organisms. Molecular Biology (Russian), 41(4), 681-687 (2007)
PubMed
I.N. Serdyuk and O.V. Galzitskaya, Unstructured regions in elongation factors EF1A from three overkingdom of the living world. Molecular Biology (Russian), 41(6), 1042-1055 (2007)
PubMed
A.V. Glyakina, S.O. Garbuzynskiy, M.Yu. Lobanov and O.V. Galzitskaya, Different packing of external residues can explain differences in the thermostability of proteins from thermophilic and mesophilic organisms. Bioinformatic, 23(17), 2231-2238 (2007)
PubMed
A.V. Finkelstein, D.N. Ivankov, S.O. Garbuzynskiy and O.V. Galzitskaya, Understanding the folding rates and folding nuclei of globular proteins. Current Protein and Peptide Science, 8(6) 521-536 (2007)
PubMed
O.V. Galzitskaya, D.C. Reifsnyder, N.S. Bogatyreva, D.N. Ivankov and S.O. Garbuzynskiy, More Compact Protein Globules Exhibit Slower Folding Rates. Protein, 70(2), 329-332 (2008)
PubMed
A.V. Finkelstein, D.N. Ivankov, S.O. Garbuzynskiy and O.V. Galzitskaya, Protein structure and its folding rate. In: Applied Optimization: Mathematical Modelling of Biosystems (Editors: R.P. Mondaini, P.M. Pardalos). Springer Verlag (Heidelberg), XII, v.102, pp. 273-301 (2008)
O.V. Galzitskaya, N.S. Bogatyreva and D.N. Ivankov, Compactness determines protein folding type. J Bioinform Comput Biol., 6(4), 667-680 (2008)
PubMed
O.V. Galzitskaya, Search for folding initiation sites from amino acid sequence. J Bioinform Comput Biol., 6(4), 681-691 (2008)
PubMed
N.V. Dovidchenko and O.V. Galzitskaya, Prediction of status residue to be protected or not protected from hydrogen exchange using amino acid sequence only. The Open Biochemistry Journal, 2, 77-80 (2008)
M.Yu. Lobanov, N.S. Bogatyreva and O.V. Galzitskaya, Radius of gyration as an indicator of protein structure compactness. Molecular Biology (Russian), 42(4), 623-628 (2008)
PubMed
N.V. Dovidchenko, N.S. Bogatyreva and O.V. Galzitskaya, Prediction of loop regions in protein sequence. J Bioinform Comput Biol., 6(5), 1035-1047 (2008)
PubMed
E.I. Deruysheva, O.V. Galzitskaya and I.N. Serduyk, Prediction of short loops in the proteins with internal disorder. Molecular Biology (Russian), 42 (6), 1067--1078 (2008)
PubMed
A.V. Finkelstein, D.N. Ivankov, S.O. Garbuzynskiy and O.V. Galzitskaya, Protein structure and its folding rate. In: Applied Optimization: Mathematical Modelling of Biosystems (Editors: R.P. Mondaini, P.M. Pardalos). Springer Verlag (Heidelberg), XII, v.102, pp. 273-301 (2008)
A.V. Glyakina, O.V. Galzitskaya and N.K. Balabaev, Molecular dynamics of protein unfolding under the external forces. Bulletin of Tver University, 8(68), 109-119 (2008)
O.V. Galzitskaya, E.I. Deryusheva and I.N. Serdyuk, Phylogenetic Analysis of the Loops in Elongation Factors EF1A: Stronger Support for the Grouping of Animal and Fungi. Journal of Computer Science and System Biology., 1, 073-080 (2008)
N.S. Bogatyreva, D. N. Ivankov, M. Yu. Lobanov, O.V. Galzitskaya, Connection of shape of globular proteins with their folding and unfolding rates. Mathematical biology and bioinformatics (Russia), 3(2), 69-78 (2008)
M.Yu. Lobanov, N.S. Bogatyreva, O.V. Galzitskaya, Radius of gyration as an indicator of protein structure compactness. Molecular Biology, 42(4), 623-628 (2008)
T.S. Kalebina, T.A. Plotnikova, A.A. Gorkovskii, I.O. Selyakh, O.V. Galzitskaya, E.E. Bezsonov, G. Gellissen and I.S. Kulaev, Amyloid-like properties of Saccharomyces cerevisiae cell wall glucantransferase Bgl2p: prediction and experimental evidences. Prion, 2(2), 91-96 (2008)
PubMed
O.V. Galzitskaya, Do amyloidogenic regions intersect with folding nuclei of native structure? Proceedings from Computational biophysics to system biology (CBSB08), pp.219-221. 19-21 May, 2008b, Julich, Germany (2008)
O.V. Galzitskaya, S.O. Garbuzynskiy, Folding and aggregation features of proteins. Nova Science Publishers, Inc., In: Protein Misfolding, Editors: Cian B. O'Doherty and Adam C. Byrne, pp.99-112 (2008)
O.V. Galzitskaya, Are the same or different amino acid residues responsible for correct and incorrect protein folding? Biochemistry (Russian), 74(2), 229-237 (2009)
PubMed
J. Fong, B. Shoemaker, S.O. Garbuzynskiy, M.Yu. Lobanov, O.V. Galzitskaya and A. Panchenko, Intrinsic disorder in proteins and their complexes: a large-scale view. PLoS Comput Biol., 5(3), e1000316 (2009)
PubMed
O.V. Galzitskaya and S.O. Garbuzynskiy, Comparison of Φ-values and folding time predictions by using Monte-Carlo and Dynamic Programming approaches. Chapter in the book, "Computational Biology: New Research"., pp. 277-314 (2009)
A.V. Glyakina, N.K. Balabaev and O.V. Galzitskaya, Comparison of transition states obtained upon modeling of unfolding of immunoglobulin-binding domains of proteins L and G caused by external action with transition states obtained in the absence of force probed by experiments. Biochemistry (Russian), 74(3), 316-328 (2009)
PubMed
A. V. Glyakina, N. K. Balabaev, and O. V. Galzitskaya, Mechanical unfolding of proteins L and G with constant force: similarities and differences. J Chem. Phys., 131, 045102 (2009)
PubMed
D. N. Ivankov, N. S. Bogatyreva, M. Yu. Lobanov, O. V. Galzitskaya, Coupling between Properties of the Protein Shape and the Rate of Protein Folding. PLoS ONE, 4(8): e6476 (2009)
PubMed
A. V. Glyakina, N. K. Balabaev, and O. V. Galzitskaya, Multiple Unfolding Intermediates Obtained by Molecular Dynamic Simulations under Stretching for Immunoglobulin-Binding Domain of Protein G. Open Biochemistry, 3, 66-77 (2009)
PubMed
N.V. Dovidchenko, M.Yu., Lobanov, S.O. Garbuzynskiy, and O.V. Galzitskaya, Prediction of amino acid residues protected from hydrogen-deuterium exchange in a protein chain. Biochemistry (Russian), 74(8), 1091-1102 (2009)
PubMed
O.V. Galzitskaya, Influence of flexible loops on the rate of protein folding. Current Topics in Peptide & Protein Research, V.9, pages 71-82 (2009)
A. V. Glyakina, N. K. Balabaev, and O. V. Galzitskaya, Two-, Three-, and Four-State Events Occur in the Mechanical Unfolding of Small Protein L Using Molecular Dynamics Simulations. Protein and Peptide Letter, 17, 92-103 (2010)
PubMed
M.Yu. Lobanov, B. A. Shoemaker, S. O. Garbuzynskiy, J. H. Fong, A. R. Panchenko, O. V. Galzitskaya, ComSin: Database of protein structures in bound (Complex) and unbound (Single) states in relation to their intrinsic disorder. Nucleic Acids Research, D283-D287 (2010)
PubMed
M.Yu. Lobanov, S.O. Garbuzynskiy, O.V. Galzitskaya, Statistical analysis of unstructured amino acid residues in protein structures. Biochemistry (Russian), 75(2), 192-200 (2010)
PubMed
T.B. Mamonova, A.V. Glyakina, M.G. Kurnikova, O.V. Galzitskaya, Flexibility and mobility in Mesophilic and thermophilic homologous proteins from Molecular Dynamics and FoldUnfold Method. J Bioinform Comput Biol., 8(3), 377-394 (2010)
PubMed
A.V. Glyakina, O.V. Galzitskaya, A comparative analysis of folding pathways of thermophilic and mesophilic proteins by Monte Carlo simulations. J Bioinform Comput Biol., 8(3), 395-411 (2010)
PubMed
O.V. Galzitskaya, Estimation of protein folding rate from Monte Carlo simulations and entropy capacity. Current Protein and Peptide Science, 11 (7), in pre (2010)
PubMed
O.V. Galzitskaya, Is protein folding rate dependent on the number of folding stages? Modeling of protein folding with ferredoxin-like fold. Biochemistry (Russian), 75(6), 807-818 (2010)
PubMed
A.V. Maltsev and O.V. Galzitskaya, Formation and participation of nano-amyloids in pathogenesis of alzheimer's disease and other amyloidogenic diseases. Biochemistry (Russian), Supplement Series B: Biomedical Chemistry, 4(3), 228вЂ“236 (2010)
S. O. Garbuzynskiy, M. Yu. Lobanov and O. V. Galzitskaya, FoldAmyloid: a method of prediction of amyloidogenic regions from protein sequence. Bioinformatic, 26, 326-332 (2010)
PubMed
A.V. Glyakina, O.V. Galzitskaya, Influence of organization of native structure on its folding: modeling of the folding of alpha-helical proteins. Biochemistry (Russian), 75(8), 1098-1110 (2010)
PubMed
O.V. Galzitskaya, Influence of Conformational Entropy on the Protein Folding Rate. Entropy, 12(4), 961-982 (2010)
O. V. Galzitskaya, Modelling of Protein Folding and Prediction of Rate based on Nucleation Mechanism. Nova Science Publishers, Inc., ISBN: 978-1-61728-990-3 In: protein Folding Editor: Eric C. Walters, in press (2010)
A. V. Glyakina, O. V. Galzitskaya, N. K. Balabaev, Investigation of mechanical properties of immunoglobulin-binding properties of proteins L and G by molecular dynamics simulations. Computer research and modeling, 2, 73-81 (2010)
M. Yu. Lobanov, E. I. Furletova, N. S. Bogatyreva, M. A. Roytberg, O. V. Galzitskaya, Library of Disordered Patterns in 3D Protein Structures. PLoS Computational Biology, 6(10):e1000958. (2010)
PubMed
Galzitskaya O.V., Lobanov M. Yu., Finkelstein A.V., Cunning simplicity of a stoichiometry driven protein folding thesis. J. Biomol. Struct. Dyn., 28 In pre (2010)
PubMed
O.V. Galzitskaya, N.S. Bogatyreva, A.V. Glyakina, Bacterial proteins fold faster than eukaryotic proteins with simple folding kinetics. Biochemistry (Russian), In press (2010)
L.B. Pereyaslavets, M.V. Baranov, E.I. Leonova, O.V. Galzitskaya, Prediction of folding/unfolding nuclei for tRNA molecules. Biochemistry (Russian), In press (2010)

Details: Written by Super User; Category: Uncategorised; Published: 11 December 2019; Hits: 1177

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HSSP
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DSSP (DSSP, program [Kabsch and Sander (1983)Biopolymers, 22, 2577–2637] for localization of secondary structure elements and energy of hydrogen connections in main chain)
SCOP (Structure Classification of Proteins)

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PDB (PDB в обработке М.Лобанова - ручное обновление, исправление ошибок)
IsUnstruct предсказание неструктурированных участков белковой цепи по аминокислотной последовательности
OGU предсказание неструктурированных участков белковой цепи по аминокислотной последовательности
Compact база данных по кинетике сворачивания белковых структур
Nucleic Acids Res. 2009 Jan; 37(Database issue):D342-6
KineticDB база данных по кинетике сворачивания белковых структур
Nucleic Acids Res. 2009 Jan; 37(Database issue):D342-6
Fold Amyloid Base база данных амилоидогенных фрагментов, известных из экспериментальных данных
Fold Amyloid сервер для предсказания амилоидогенных участков по аминокислотной последовательности
ComSin base of protein structures in bound (Complex) and unbound (Single) states in relation to their intrinsic disorder.
Nucleic Acids Res. 2010 Jan;38(Database issue): D283-7. http://www.pathguide.org/fullrecord.php?DBID=321
OG3 предсказание границ доменов по аминокислотной последовательности
BM_OG предсказание границ доменов по аминокислотной последовательности
B_factor предсказание защищенности аминокислотных остатков от водородно-дейтериевого обмена
Thermo- and mesophilic Database of structural pairs of proteins from thermo- and mesophilic organisms
Phi-values Experimentally measured and theoretically predicted phi-values.
Pereyaslavets LB, Sokolovsky IV, Galzitskaya OV. FoldNucleus: web server for the prediction of RNA and protein folding nuclei from their 3D structures. Bioinformatics. 2015 Oct 15;31(20):3374-6. doi: 10.1093/bioinformatics/btv369.
Ideal-base Database of 3D structures of "ideally" folded proteins.
Garbuzynskiy S.O., Lobanov M.Yu., Galzitskaya O.V. (2004). To be folded or to be unfolded? Protein Science, v.13 (11), pp. 2871-2877.
scop_1.61 Database of 3D structures with identity below 80%.
Galzitskaya O.V., Garbuzynskiy S.O., Lobanov M.Yu. (2006). Prediction of natively unfolded regions in protein chains. Molecular Biology, v.40 (2), pp. 298-304.
Natively unfolded Database of natively unfolded proteins.
Galzitskaya O.V., Garbuzynskiy S.O., Lobanov M.Yu. (2006). Prediction of natively unfolded regions in protein chains. Molecular Biology, v.40 (2), pp. 298-304.
Folded 559 Database of 559 globular proteins.
Galzitskaya O.V., Garbuzynskiy S.O., Lobanov M.Yu. (2006). Prediction of natively unfolded regions in protein chains. Molecular Biology, v.40 (2), pp. 298-304.
Folded 80 Database of 80 globular proteins.
Galzitskaya O.V., Garbuzynskiy S.O., Lobanov M.Yu. (2006). Prediction of natively unfolded regions in protein chains. Molecular Biology, v.40 (2), pp. 298-304.
HRAP Database HRAP.
Nucleic Acids Res. 2014 Jan;42(Database issue):D273-8. doi: 10.1093/nar/gkt927. Lobanov MY, Sokolovskiy IV, Galzitskaya OV. HRaP: database of occurrence of HomoRepeats and patterns in proteomes.
HRADIS Database HRADIS.
Lobanov MY, Klus P, Sokolovsky IV, Tartaglia GG, Galzitskaya OV. Non-random distribution of homo-repeats: links with biological functions and human diseases, Sci Rep. 2016 Jun 3;6:26941. doi: 10.1038/srep26941.
foldnucleus Server foldnucleus.
Pereyaslavets LB, Sokolovsky IV, Galzitskaya OV. Bioinformatics. 2015 Oct 15;31(20):3374-6. doi: 10.1093/bioinformatics/btv369. FoldNucleus: web server for the prediction of RNA and protein folding nuclei from their 3D structures.
foldhandedness Server foldhandedness.
Pereyaslavets LB, Glyakina AV, Dovidchenko NV, Sokolovskiy IV, Galzitskaya OV. What handedness and angles between helices has the studied three-helical protein domain? Bioinformatics. 2015 Mar 15;31(6):963-5. doi: 10.1093/bioinformatics/btu737.
Clustered PDB Server Clustered PDB. Michail Yu. Lobanov, Ilya V. Likhachev, Oxana Galzitskaya. Disordered Residues and Patterns in the Protein Data Bank. Molecules. 2020 Apr; 25(7): 1522. doi: 10.3390/molecules
C.A.R.P. Contacts of Aromatic Residues in Proteins Mikhail Yu.Lobanov^a Leonid B.Pereyaslavets^a Ilya V.Likhachev^a^b Bakhyt T.Matkarimov^c Oxana V.Galzitskaya https://doi.org/10.1016/j.csbj.2021.10.036

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The modelling of formation of amyloid fibrils
Prediction of folding/unfolding nuclei for RNA molecules
Modelling of protein folding and prediction of rate based on nucleation mechanism
Statistical analysis of unstructured amino acid residues in protein structures
Prediction of functions for disordered regions in eukaryotic proteomes

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