740 research outputs found
Drug-therapy networks and the predictions of novel drug targets
Recently, a number of drug-therapy, disease, drug, and drug-target networks
have been introduced. Here we suggest novel methods for network-based
prediction of novel drug targets and for improvement of drug efficiency by
analysing the effects of drugs on the robustness of cellular networks.Comment: This is an extended version of the Journal of Biology paper
containing 2 Figures, 1 Table and 44 reference
Water and molecular chaperones act as weak links of protein folding networks: energy landscape and punctuated equilibrium changes point towards a game theory of proteins
Water molecules and molecular chaperones efficiently help the protein folding
process. Here we describe their action in the context of the energy and
topological networks of proteins. In energy terms water and chaperones were
suggested to decrease the activation energy between various local energy minima
smoothing the energy landscape, rescuing misfolded proteins from conformational
traps and stabilizing their native structure. In kinetic terms water and
chaperones may make the punctuated equilibrium of conformational changes less
punctuated and help protein relaxation. Finally, water and chaperones may help
the convergence of multiple energy landscapes during protein-macromolecule
interactions. We also discuss the possibility of the introduction of protein
games to narrow the multitude of the energy landscapes when a protein binds to
another macromolecule. Both water and chaperones provide a diffuse set of
rapidly fluctuating weak links (low affinity and low probability interactions),
which allow the generalization of all these statements to a multitude of
networks.Comment: 9 pages, 1 figur
Weighted Correlation Network Analysis (WGCNA) Applied to the Tomato Fruit Metabolome
BACKGROUND: Advances in "omics" technologies have revolutionized the collection of biological data. A matching revolution in our understanding of biological systems, however, will only be realized when similar advances are made in informatic analysis of the resulting "big data." Here, we compare the capabilities of three conventional and novel statistical approaches to summarize and decipher the tomato metabolome. METHODOLOGY: Principal component analysis (PCA), batch learning self-organizing maps (BL-SOM) and weighted gene co-expression network analysis (WGCNA) were applied to a multivariate NMR dataset collected from developmentally staged tomato fruits belonging to several genotypes. While PCA and BL-SOM are appropriate and commonly used methods, WGCNA holds several advantages in the analysis of highly multivariate, complex data. CONCLUSIONS: PCA separated the two major genetic backgrounds (AC and NC), but provided little further information. Both BL-SOM and WGCNA clustered metabolites by expression, but WGCNA additionally defined "modules" of co-expressed metabolites explicitly and provided additional network statistics that described the systems properties of the tomato metabolic network. Our first application of WGCNA to tomato metabolomics data identified three major modules of metabolites that were associated with ripening-related traits and genetic background
Network analysis of protein dynamics
The network paradigm is increasingly used to describe the topology and
dynamics of complex systems. Here we review the results of the topological
analysis of protein structures as molecular networks describing their
small-world character, and the role of hubs and central network elements in
governing enzyme activity, allosteric regulation, protein motor function,
signal transduction and protein stability. We summarize available data how
central network elements are enriched in active centers and ligand binding
sites directing the dynamics of the entire protein. We assess the feasibility
of conformational and energy networks to simplify the vast complexity of rugged
energy landscapes and to predict protein folding and dynamics. Finally, we
suggest that modular analysis, novel centrality measures, hierarchical
representation of networks and the analysis of network dynamics will soon lead
to an expansion of this field.Comment: 10 pages, 2 figures, 1 tabl
Stress-induced rearrangements of cellular networks: consequences for protection and drug design
The complexity of the cells can be described and understood by a number of
networks such as protein-protein interaction, cytoskeletal, organelle,
signalling, gene transcription and metabolic networks. All these networks are
highly dynamic producing continuous rearrangements in their links, hubs,
network-skeleton and modules. Here we describe the adaptation of cellular
networks after various forms of stress causing perturbations, congestions and
network damage. Chronic stress decreases link-density, decouples or even
quarantines modules, and induces an increased competition between network hubs
and bridges. Extremely long or strong stress may induce a topological phase
transition in the respective cellular networks, which switches the cell to a
completely different mode of cellular function. We summarize our initial
knowledge on network restoration after stress including the role of molecular
chaperones in this process. Finally, we discuss the implications of
stress-induced network rearrangements in diseases and ageing, and propose
therapeutic approaches both to increase the robustness and help the repair of
cellular networks.Comment: 9 pages, 1 table, 2 figures, invited paper of FEBS Letters Cellular
Stress special issu
ModuLand plug-in for Cytoscape: determination of hierarchical layers of overlapping network modules and community centrality
Summary: The ModuLand plug-in provides Cytoscape users an algorithm for
determining extensively overlapping network modules. Moreover, it identifies
several hierarchical layers of modules, where meta-nodes of the higher
hierarchical layer represent modules of the lower layer. The tool assigns
module cores, which predict the function of the whole module, and determines
key nodes bridging two or multiple modules. The plug-in has a detailed
JAVA-based graphical interface with various colouring options. The ModuLand
tool can run on Windows, Linux, or Mac OS. We demonstrate its use on protein
structure and metabolic networks. Availability: The plug-in and its user guide
can be downloaded freely from: http://www.linkgroup.hu/modules.php. Contact:
[email protected] Supplementary information: Supplementary
information is available at Bioinformatics online.Comment: 39 pages, 1 figure and a Supplement with 9 figures and 10 table
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