Abstract: For the implementation of the virtual cell, the fundamental question is how to model and simulate complex biological networks. During the last 15 years, Petri nets have attracted more and more attention to help to solve this key problem. Regarding the published papers, it seems clear that hybrid functional Petri nets are the adequate method to model complex biological networks. Today, a Petri net model of biological networks is built manually by drawing places, transitions and arcs with mouse events. Therefore, based on relevant molecular database and information systems biological data integration is an essential step in constructing biological networks. In this paper, we will motivate the application of Petri nets for modeling and simulation of biological networks. Furthermore, we will present a type of access to relevant metabolic databases such as KEGG, BRENDA, etc. Based on this integration process, the system supports semi-automatic generation of the correlated hybrid Petri net model. A case study of the cardio-disease related gene-regulated biological network is also presented. MoVisPP is available at http://agbi.techfak.uni-bielefeld.de/movispp/.
Abstract: Control of cell proliferation, differentiation, activation and cell removal is crucial for the development and existence of multi-cellular organisms. Apoptosis, or programmed cell death, is a major control mechanism by which cells die and is also important in controlling cell number and proliferation as part of normal development. Molecular networks that regulate these processes are critical targets for drug development, gene therapy, and metabolic engineering. The molecular interactions involved in this and other processes are analyzed and annotated by experts and stored as data in different databases. The key task is to integrate, manage and visualize these data available from different sources and present them in a user-comprehensible manner. Here we present VINEdb, a data warehouse developed to interact with and to explore integrated life science data. Extendable open source data warehouse architecture enables platform-independent usability of the web application and the underlying infrastructure. A high degree of transparency and up-to-dateness is ensured by a monitor component to control and update the data from the sources. Furthermore, the system is supported by a visualization component to allow interactive graphical exploration of the integrated data. We will use apoptotic pathway and caspase-3 as a case study to show capability and usability of our approach. VINEdb is available at http://tunicata.techfak.uni-bielefeld.de/VINEdb/.
Abstract: A series of thiosugar derivatives (thiolevomannosans) derived from mannose were synthesized and their inhibitory activity was tested against alpha-mannosidase (jack bean). These inhibitors were found to be more potent than the well-known inhibitors like kifunensine and deoxymannojirimycin based on docking and biochemical studies. The sulfone derivative 10 was shown to be the best inhibitor of alpha-mannosidase with the K(i) value of 350 nM.
Abstract: The identification of T cell epitopes from immune relevant antigens of Mycobacterium tuberculosis is a critical step in the development of a vaccine covering diverse populations. Two multigene families, PE-PGRS and PPE make up about 10% of the M. tuberculosis genome. However, the functions of the proteins coded by these large numbers of genes are unknown. All possible nonameric peptide sequences from PE and PPE proteins were analysed in silico for their ability to bind to 33 alleles of class I HLA. These results reveal that of all PE and PPE proteins, a significant number of these peptides are predicted to be high-affinity HLA binders, irrespective of the length of the protein. The pathogen peptides that could behave as self or partially self-peptides in the host were eliminated using a comparative study with human proteome, thus reducing the number of peptides for analysis. The structural basis for recognition of the nonamers by the respective HLA molecules thus predicted was analyzed by molecular modeling. The structural analysis showed good correlation with the binding prediction. The analysis also led to an understanding of the binding profile of the peptides with respect to different alleles of class I HLA. The predicted epitopes can be tested experimentally for their inclusion in a potential vaccine against tuberculosis that is HLA haplotype-specific.
Abstract: Horsegram (Dolichos biflorus), a protein-rich leguminous pulse, is a crop native to Southeast Asia and tropical Africa. The seeds contain multiple forms of Bowman-Birk type inhibitors. The major inhibitor HGI-III, from the native seed with 76 amino acid residues exists as a dimer. The amino acid sequence of three isoforms of Bowman-Birk inhibitor from germinated horsegram, designated as HGGI-I, HGGI-II, and HGGI-III, have been obtained by sequential Edman analyses of the pyridylethylated inhibitors and peptides derived therefrom by enzymatic and chemical cleavage. The HGGIs are monomers, comprising of 66, 65, and 60 amino acid residues, respectively. HGGI-III from the germinated seed differs from the native seed inhibitor in the physiological deletion of a dodecapeptide at the amino terminus and a tetrapeptide, -SHDD, at the carboxyl terminus. The study of the state of association of HGI-III, by size-exclusion chromatography and SDS-PAGE in the presence of 1 mM ZnCl2, has revealed the role of charged interactions in the monomer <--> dimer equilibria. Chemical modification studies of Lys and Arg have confirmed the role of charge interactions in the above equilibria. These results support the premise that a unique interaction, which stabilizes the dimer, is the cause of self-association in the inhibitors. This interaction in HGI-III involves the epsilon-amino group of the Lys24 (P1 residue) at the first reactive site of one monomer and the carboxyl of an Asp86 at the carboxyl terminus of the second monomer. Identification of the role of these individual amino acids in the structure and stability of the dimer was accomplished by chemical modifications, multiple sequence alignment of legume Bowman-Birk inhibitors, and homology modeling. The state of association may also influence the physiological and functional role of these inhibitors.
Abstract: Classification of protein sequences and structures into families is a fundamental task in biology, and it is often used as a basis for designing experiments for gaining further knowledge. Some relationships between proteins are detected by the similarities in their sequences, and many more by the similarities in their structures. Despite this, there are a number of examples of functionally similar molecules without any recognisable sequence or structure similarities, and there are also a number of protein molecules that share common structural scaffolds but exhibit different functions. Newer methods of comparing molecules are required in order to detect similarities and dissimilarities in protein molecules. In this article, it is proposed that the precise 3-dimensional disposition of key residues in a protein molecule is what matters for its function, or what conveys the "meaning" for a biological system, but not what means it uses to achieve this. The concept of comparing two molecules through their intramolecular interaction networks is explored, since these networks dictate the disposition of amino acids in a protein structure. First, signature patterns, or fingerprints, of interaction networks in pre-classified protein structural families are computed using an approach to find structural equivalences and consensus hydrogen bonds. Five examples from different structural classes are illustrated. These patterns are then used to search the entire Protein Data Bank, an approach through which new, unexpected similarities have been found. The potential for finding relationships through this approach is highlighted. The use of hydrogen-bond fingerprints as a new metric for measuring similarities in protein structures is also described.
Abstract: MOTIVATION: Analysis of cellular signaling interactions is expected to pose an enormous informatics challenge, perhaps even larger than analyzing the genome. The complex networks arising from signaling processes are traditionally represented as block diagrams. A key step in the evolution toward a more quantitative understanding of signaling is to explicitly specify the kinetics of all chemical reaction steps in a pathway. Technical advances in proteomics and high-throughput protein interaction assays promise a flood of such quantitative data. While annotations, molecular information and pathway connectivity have been compiled in several databases, and there are several proposals for general cell model description languages, there is currently little experience with databases of chemical kinetics and reaction level models of signaling networks. RESULTS: The Database of Quantitative Cellular Signaling is a repository of models of signaling pathways. It is intended both to serve the growing field of chemical-reaction level simulation of signaling networks, and to anticipate issues in large-scale data management for signaling chemistry. AVAILABILITY: The Database of Quantitative Cellular Signaling is available at http://doqcs.ncbs.res.in. Links to the signaling model simulator, GENESIS/Kinetikit are at http://www.ncbs.res.in/~bhalla/kkit/index.html and are also provided from within the database. The database source code is available under the GNU Public License.
