10 results on '"Philip V. Toukach"'
Search Results
2. Examining the diversity of structural motifs in fungal glycome
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Philip V. Toukach and Ksenia S. Egorova
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Fungi ,Bacteria ,Protista ,Glycome ,Carbohydrate ,Glycan ,Biotechnology ,TP248.13-248.65 - Abstract
In this paper, we present the results of a systematic statistical analysis of the fungal glycome in comparison with the prokaryotic and protistal glycomes as described in the scientific literature and presented in the Carbohydrate Structure Database (CSDB). The monomeric and dimeric compositions of glycans, their non-carbohydrate modifications, glycosidic linkages, sizes of structures, branching degree and net charge are assessed. The obtained information can help elucidating carbohydrate molecular markers for various fungal classes which, in its turn, can be demanded for the development of diagnostic tools and carbohydrate-based vaccines against pathogenic fungi. It can also be useful for revealing specific glycosyltransferases active in a particular fungal species.
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- 2022
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3. Production and сharacterization of the exopolysaccharide from strain Paenibacillus polymyxa 2020.
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Elena V Liyaskina, Nadezhda A Rakova, Alevtina A Kitykina, Valentina V Rusyaeva, Philip V Toukach, Alexey Fomenkov, Saulius Vainauskas, Richard J Roberts, and Victor V Revin
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Medicine ,Science - Abstract
Paenibacillus spp. exopolysaccharides (EPSs) have become a growing interest recently as a source of biomaterials. In this study, we characterized Paenibacillus polymyxa 2020 strain, which produces a large quantity of EPS (up to 68 g/L),and was isolated from wasp honeycombs. Here we report its complete genome sequence and full methylome analysis detected by Pacific Biosciences SMRT sequencing. Moreover, bioinformatic analysis identified a putative levan synthetic operon. SacC and sacB genes have been cloned and their products identified as glycoside hydrolase and levansucrase respectively. The Fourier transform infrared (FT-IR) and nuclear magnetic resonance (NMR) spectra demonstrated that the EPS is a linear β-(2→6)-linked fructan (levan). The structure and properties of levan polymer produced from sucrose and molasses were analyzed by FT-IR, NMR, scanning electron microscopy (SEM), high performance size exclusion chromatography (HPSEC), thermogravimetric analysis (TGA), cytotoxicity tests and showed low toxicity and high biocompatibility. Thus, P. polymyxa 2020 could be an exceptional cost-effective source for the industrial production of levan-type EPSs and to obtain functional biomaterials based on it for a broad range of applications, including bioengineering.
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- 2021
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4. Three-Dimensional Structures of Carbohydrates and Where to Find Them
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Sofya I. Scherbinina and Philip V. Toukach
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0301 basic medicine ,Computer science ,Test data generation ,Carbohydrates ,Molecular Conformation ,Structural diversity ,Review ,Molecular Dynamics Simulation ,01 natural sciences ,Web tool ,Catalysis ,Inorganic Chemistry ,lcsh:Chemistry ,03 medical and health sciences ,Imaging, Three-Dimensional ,glycoinformatics ,0103 physical sciences ,model build ,Physical and Theoretical Chemistry ,Databases, Protein ,Molecular Biology ,lcsh:QH301-705.5 ,Spectroscopy ,database ,010304 chemical physics ,PDB glycans ,Spatial structure ,molecular modeling ,Organic Chemistry ,web-tool ,Experimental data ,Reproducibility of Results ,Structure validation ,General Medicine ,spatial structure ,Data science ,structure visualization ,Computer Science Applications ,Visualization ,030104 developmental biology ,lcsh:Biology (General) ,lcsh:QD1-999 ,structure validation ,carbohydrate ,Glycoinformatics - Abstract
Analysis and systematization of accumulated data on carbohydrate structural diversity is a subject of great interest for structural glycobiology. Despite being a challenging task, development of computational methods for efficient treatment and management of spatial (3D) structural features of carbohydrates breaks new ground in modern glycoscience. This review is dedicated to approaches of chemo- and glyco-informatics towards 3D structural data generation, deposition and processing in regard to carbohydrates and their derivatives. Databases, molecular modeling and experimental data validation services, and structure visualization facilities developed for last five years are reviewed.
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- 2020
5. Comparison of Methods for Bulk Automated Simulation of Glycosidic Bond Conformations
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Victor S. Stroylov, Philip V. Toukach, and Maria V. Panova
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0301 basic medicine ,nuclear Overhauser effect ,NOE simulation ,Materials science ,Disaccharide ,Thermodynamics ,Nuclear Overhauser effect ,Molecular Dynamics Simulation ,Disaccharides ,01 natural sciences ,Article ,Catalysis ,Force field (chemistry) ,Inorganic Chemistry ,lcsh:Chemistry ,03 medical and health sciences ,chemistry.chemical_compound ,Molecular dynamics ,database filling ,0103 physical sciences ,Carbohydrate Conformation ,Molecule ,Physical and Theoretical Chemistry ,Molecular Biology ,Conformational ensembles ,lcsh:QH301-705.5 ,Spectroscopy ,chemistry.chemical_classification ,010304 chemical physics ,force field ,Organic Chemistry ,Glycosidic bond ,General Medicine ,molecular dynamics ,Computer Science Applications ,030104 developmental biology ,Carbohydrate Sequence ,chemistry ,lcsh:Biology (General) ,lcsh:QD1-999 ,carbohydrate ,Solvents ,Density functional theory ,glycosidic bond conformation ,disaccharide ,Software - Abstract
Six empirical force fields were tested for applicability to calculations for automated carbohydrate database filling. They were probed on eleven disaccharide molecules containing representative structural features from widespread classes of carbohydrates. The accuracy of each method was queried by predictions of nuclear Overhauser effects (NOEs) from conformational ensembles obtained from 50 to 100 ns molecular dynamics (MD) trajectories and their comparison to the published experimental data. Using various ranking schemes, it was concluded that explicit solvent MM3 MD yielded non-inferior NOE accuracy with newer GLYCAM-06, and ultimately PBE0-D3/def2-TZVP (Triple-Zeta Valence Polarized) Density Functional Theory (DFT) simulations. For seven of eleven molecules, at least one empirical force field with explicit solvent outperformed DFT in NOE prediction. The aggregate of characteristics (accuracy, speed, and compatibility) made MM3 dynamics with explicit solvent at 300 K the most favorable method for bulk generation of disaccharide conformation maps for massive database filling.
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- 2020
6. SugarSketcher: Quick and Intuitive Online Glycan Drawing
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Julien Mariethoz, Nicolas Hory, Philip V. Toukach, Renaud Costa, Radka Svobodová Vařeková, Frédérique Lisacek, Pavla Suchánková, and Davide Alocci
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0301 basic medicine ,Carbohydrate ,Source code ,Computer science ,Interface (Java) ,media_common.quotation_subject ,Scalable Vector Graphics ,Pharmaceutical Science ,Web Browser ,JavaScript ,computer.software_genre ,Symbol (chemistry) ,Analytical Chemistry ,World Wide Web ,lcsh:QD241-441 ,03 medical and health sciences ,Structure-Activity Relationship ,Mode (computer interface) ,lcsh:Organic chemistry ,Polysaccharides ,ddc:570 ,Drug Discovery ,Technical Note ,Plug-in ,Physical and Theoretical Chemistry ,ddc:025.063 ,computer.programming_language ,media_common ,2D structure ,030102 biochemistry & molecular biology ,software ,Organic Chemistry ,Computational Biology ,computer.file_format ,030104 developmental biology ,Chemistry (miscellaneous) ,carbohydrate ,Molecular Medicine ,Glycoinformatics ,computer ,Software ,SNFG notation - Abstract
SugarSketcher is an intuitive and fast JavaScript interface module for online drawing of glycan structures in the popular Symbol Nomenclature for Glycans (SNFG) notation and exporting them to various commonly used formats encoding carbohydrate sequences (e.g., GlycoCT) or quality images (e.g., svg). It does not require a backend server or any specific browser plugins and can be integrated in any web glycoinformatics project. SugarSketcher allows drawing glycans both for glycobiologists and non-expert users. The “quick mode„ allows a newcomer to build up a glycan structure having only a limited knowledge in carbohydrate chemistry. The “normal mode„ integrates advanced options which enable glycobiologists to tailor complex carbohydrate structures. The source code is freely available on GitHub and glycoinformaticians are encouraged to participate in the development process while users are invited to test a prototype available on the ExPASY web-site and send feedback.
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- 2018
7. Carbohydrate structure database merged from bacterial, archaeal, plant and fungal parts
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Ksenia S. Egorova and Philip V. Toukach
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0301 basic medicine ,Database ,Bacteria ,Molecular Structure ,Carbohydrates ,Fungi ,Biology ,Plants ,computer.software_genre ,Archaea ,Systems Integration ,03 medical and health sciences ,030104 developmental biology ,Genetics ,Glycoinformatics ,Database Issue ,Carbohydrate composition ,computer ,Nuclear Magnetic Resonance, Biomolecular ,Databases, Chemical ,Software - Abstract
The Carbohydrate Structure Databases (CSDBs, http://csdb.glycoscience.ru) store structural, bibliographic, taxonomic, NMR spectroscopic, and other data on natural carbohydrates and their derivatives published in the scientific literature. The CSDB project was launched in 2005 for bacterial saccharides (as BCSDB). Currently, it includes two parts, the Bacterial CSDB and the Plant&Fungal CSDB. In March 2015, these databases were merged to the single CSDB. The combined CSDB includes information on bacterial and archaeal glycans and derivatives (the coverage is close to complete), as well as on plant and fungal glycans and glycoconjugates (almost all structures published up to 1998). CSDB is regularly updated via manual expert annotation of original publications. Both newly annotated data and data imported from other databases are manually curated. The CSDB data are exportable in a number of modern formats, such as GlycoRDF. CSDB provides additional services for simulation of (1)H, (13)C and 2D NMR spectra of saccharides, NMR-based structure prediction, glycan-based taxon clustering and other.
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- 2015
8. Carbohydrate Structure Database: tools for statistical analysis of bacterial, plant and fungal glycomes
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Philip V. Toukach, Ksenia S. Egorova, and A. N. Kondakova
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Glycosylation ,Carbohydrate synthesis ,Carbohydrates ,Biology ,computer.software_genre ,General Biochemistry, Genetics and Molecular Biology ,Glycomics ,chemistry.chemical_compound ,Carbohydrate Conformation ,Statistical analysis ,Carbohydrate composition ,Gene ,Organism ,Database ,Bacteria ,Fungi ,Plants ,Database Tool ,Biochemistry ,chemistry ,Carbohydrate conformation ,General Agricultural and Biological Sciences ,computer ,Databases, Chemical ,Information Systems - Abstract
Carbohydrates are biological blocks participating in diverse and crucial processes both at cellular and organism levels. They protect individual cells, establish intracellular interactions, take part in the immune reaction and participate in many other processes. Glycosylation is considered as one of the most important modifications of proteins and other biologically active molecules. Still, the data on the enzymatic machinery involved in the carbohydrate synthesis and processing are scattered, and the advance on its study is hindered by the vast bulk of accumulated genetic information not supported by any experimental evidences for functions of proteins that are encoded by these genes. In this article, we present novel instruments for statistical analysis of glycomes in taxa. These tools may be helpful for investigating carbohydrate-related enzymatic activities in various groups of organisms and for comparison of their carbohydrate content. The instruments are developed on the Carbohydrate Structure Database (CSDB) platform and are available freely on the CSDB web-site at http://csdb.glycoscience.ru. Database URL: http://csdb.glycoscience.ru
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- 2015
9. BioHackathon series in 2011 and 2012: penetration of ontology and linked data in life science domains
- Author
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Toshiaki Katayama, Yoshinobu Igarashi, Peter J. A. Cock, Raoul J. P. Bonnal, Yue Wang, Katsuhiko Murakami, Matúš Kalaš, Jan Aerts, Mark Wilkinson, Yoshinobu Kano, Erick Antezana, Yasunori Yamamoto, Yusuke Komiyama, Michel Dumontier, Maori Ito, Shuichi Kawashima, Kiyoko F. Aoki-Kinoshita, Hidemasa Bono, Anna Kokubu, Patricia L. Whetzel, Shujiro Okuda, Shin Kawano, Kazuharu Arakawa, K. Bretonnel Cohen, Toshihisa Takagi, Hiroyo Nishide, Shu Tadaka, Jin-Dong Kim, Pjotr Prins, Andrea Splendiani, Thomas Lütteke, Hiroshi Mori, Naohisa Goto, Soichi Ogishima, Riu Yamashita, Wataru Iwasaki, Francesco Strozzi, Hisashi Narimatsu, Joachim Baran, Yasunobu Okamura, Hidetoshi Itaya, Hiromasa Ono, Alexandru Constantin, Hirokazu Chiba, Philip V. Toukach, Issaku Yamada, Bruno Aranda, Philippe Rocca-Serra, Atsuko Yamaguchi, Shinobu Okamoto, Toyofumi Fujiwara, William S. York, Taehong Kim, Matthew Campbell, Pier Luigi Buttigieg, Yi An Chen, Susanna Sansone, Takatomo Fujisawa, Rutger A. Vos, Mitsuteru Nakao, Masaaki Kotera, Yukie Akune, Sung Ho Shin, Johan Nystrom-Persson, Ikuo Uchiyama, Geraint Duck, Takaaki Mori, Nicki H. Packer, Masahito Umezaki, Robert Hoehndorf, Kazuki Oshita, Rene Ranzinger, Shoko Kawamoto, Chisato Yamasaki, M. Scott Marshall, Takeo Katoda, Yosuke Nishimura, Hilmar Lapp, Jerven Bolleman, Christian M. Zmasek, Hiromichi Sawaki, Camille Laibe, Hongyan Wu, Simon Kocbek, and Mizuki Morita
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Computer science ,Semantic interoperability ,integration ,Review ,glycomics ,0302 clinical medicine ,Semantic computing ,collection ,Semantic analytics ,Semantic Web Stack ,Visualization ,0303 health sciences ,SISTA ,EPS-2 ,Ontology ,biology ,Data models ,Computer Science Applications ,normalization ,web services ,BioHackathon ,Data integration ,Information Systems ,Computer Networks and Communications ,Bioinformatics ,Health Informatics ,bioinformatics web services ,Social Semantic Web ,World Wide Web ,03 medical and health sciences ,Databases ,Upper ontology ,metabolic pathways ,gene ,Laboratorium voor Nematologie ,030304 developmental biology ,Semantic Web ,Web services ,genome analysis environment ,business.industry ,software ,Data science ,Semantic grid ,Knowledge representation ,Semantic technology ,sequences ,Data sharing ,Laboratory of Nematology ,business ,030217 neurology & neurosurgery - Abstract
The application of semantic technologies to the integration of biological data and the interoperability of bioinformatics analysis and visualization tools has been the common theme of a series of annual BioHackathons hosted in Japan for the past five years. Here we provide a review of the activities and outcomes from the BioHackathons held in 2011 in Kyoto and 2012 in Toyama. In order to efficiently implement semantic technologies in the life sciences, participants formed various sub-groups and worked on the following topics: Resource Description Framework (RDF) models for specific domains, text mining of the literature, ontology development, essential metadata for biological databases, platforms to enable efficient Semantic Web technology development and interoperability, and the development of applications for Semantic Web data. In this review, we briefly introduce the themes covered by these sub-groups. The observations made, conclusions drawn, and software development projects that emerged from these activities are discussed. ispartof: Journal of Biomedical Semantics vol:5 issue:5 pages:1-13 ispartof: location:England status: published
- Published
- 2014
10. Statistical analysis of the Bacterial Carbohydrate Structure Data Base (BCSDB): Characteristics and diversity of bacterial carbohydrates in comparison with mammalian glycans
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William E. Hull, Stephan Herget, Philip V. Toukach, René Ranzinger, Yuriy A. Knirel, and Claus-Wilhelm von der Lieth
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Glycan ,Databases, Factual ,Carbohydrates ,Disaccharide ,Disaccharides ,chemistry.chemical_compound ,Polysaccharides ,Structural Biology ,Animals ,Humans ,Monosaccharide ,Carbohydrate composition ,lcsh:QH301-705.5 ,Mammals ,chemistry.chemical_classification ,Bacteria ,biology ,Bacterial Glycan ,Monosaccharides ,Rational design ,biology.organism_classification ,Glycome ,carbohydrates (lipids) ,Carbohydrate Sequence ,chemistry ,Biochemistry ,lcsh:Biology (General) ,biology.protein ,Research Article - Abstract
Background There are considerable differences between bacterial and mammalian glycans. In contrast to most eukaryotic carbohydrates, bacterial glycans are often composed of repeating units with diverse functions ranging from structural reinforcement to adhesion, colonization and camouflage. Since bacterial glycans are typically displayed at the cell surface, they can interact with the environment and, therefore, have significant biomedical importance. Results The sequence characteristics of glycans (monosaccharide composition, modifications, and linkage patterns) for the higher bacterial taxonomic classes have been examined and compared with the data for mammals, with both similarities and unique features becoming evident. Compared to mammalian glycans, the bacterial glycans deposited in the current databases have a more than ten-fold greater diversity at the monosaccharide level, and the disaccharide pattern space is approximately nine times larger. Specific bacterial subclasses exhibit characteristic glycans which can be distinguished on the basis of distinctive structural features or sequence properties. Conclusion For the first time a systematic database analysis of the bacterial glycome has been performed. This study summarizes the current knowledge of bacterial glycan architecture and diversity and reveals putative targets for the rational design and development of therapeutic intervention strategies by comparing bacterial and mammalian glycans.
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