17 research outputs found
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
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
Signalogs: Orthology-Based Identification of Novel Signaling Pathway Components in Three Metazoans
BACKGROUND: Uncovering novel components of signal transduction pathways and their interactions within species is a central task in current biological research. Orthology alignment and functional genomics approaches allow the effective identification of signaling proteins by cross-species data integration. Recently, functional annotation of orthologs was transferred across organisms to predict novel roles for proteins. Despite the wide use of these methods, annotation of complete signaling pathways has not yet been transferred systematically between species. PRINCIPAL FINDINGS: Here we introduce the concept of 'signalog' to describe potential novel signaling function of a protein on the basis of the known signaling role(s) of its ortholog(s). To identify signalogs on genomic scale, we systematically transferred signaling pathway annotations among three animal species, the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster, and humans. Using orthology data from InParanoid and signaling pathway information from the SignaLink database, we predict 88 worm, 92 fly, and 73 human novel signaling components. Furthermore, we developed an on-line tool and an interactive orthology network viewer to allow users to predict and visualize components of orthologous pathways. We verified the novelty of the predicted signalogs by literature search and comparison to known pathway annotations. In C. elegans, 6 out of the predicted novel Notch pathway members were validated experimentally. Our approach predicts signaling roles for 19 human orthodisease proteins and 5 known drug targets, and suggests 14 novel drug target candidates. CONCLUSIONS: Orthology-based pathway membership prediction between species enables the identification of novel signaling pathway components that we referred to as signalogs. Signalogs can be used to build a comprehensive signaling network in a given species. Such networks may increase the biomedical utilization of C. elegans and D. melanogaster. In humans, signalogs may identify novel drug targets and new signaling mechanisms for approved drugs
Induced fit, conformational selection and independent dynamic segments: an extended view of binding events
Single molecule and NMR measurements of protein dynamics increasingly uncover
the complexity of binding scenarios. Here we describe an extended
conformational selection model which embraces a repertoire of selection and
adjustment processes. Induced fit can be viewed as a subset of this repertoire,
whose contribution is affected by the bond-types stabilizing the interaction
and the differences between the interacting partners. We argue that protein
segments whose dynamics are distinct from the rest of the protein ('discrete
breathers') can govern conformational transitions and allosteric propagation
that accompany binding processes, and as such may be more sensitive to
mutational events. Additionally, we highlight the dynamic complexity of binding
scenarios as they relate to events such as aggregation and signalling, and the
crowded cellular environment.Comment: 9 pages, 2 Figures, 1 Table, 2 boxes, Trends in Biochemical Sciences
2010 October issue cover stor
Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics
Background: Network communities help the functional organization and
evolution of complex networks. However, the development of a method, which is
both fast and accurate, provides modular overlaps and partitions of a
heterogeneous network, has proven to be rather difficult. Methodology/Principal
Findings: Here we introduce the novel concept of ModuLand, an integrative
method family determining overlapping network modules as hills of an influence
function-based, centrality-type community landscape, and including several
widely used modularization methods as special cases. As various adaptations of
the method family, we developed several algorithms, which provide an efficient
analysis of weighted and directed networks, and (1) determine pervasively
overlapping modules with high resolution; (2) uncover a detailed hierarchical
network structure allowing an efficient, zoom-in analysis of large networks;
(3) allow the determination of key network nodes and (4) help to predict
network dynamics. Conclusions/Significance: The concept opens a wide range of
possibilities to develop new approaches and applications including network
routing, classification, comparison and prediction.Comment: 25 pages with 6 figures and a Glossary + Supporting Information
containing pseudo-codes of all algorithms used, 14 Figures, 5 Tables (with 18
module definitions, 129 different modularization methods, 13 module
comparision methods) and 396 references. All algorithms can be downloaded
from this web-site: http://www.linkgroup.hu/modules.ph