Nodes having a major influence to break cooperation define a novel centrality measure: game centrality.

Cooperation played a significant role in the self-organization and evolution of living organisms. Both network topology and the initial position of cooperators heavily affect the cooperation of social dilemma games. We developed a novel simulation program package, called 'NetworGame', which is able to simulate any type of social dilemma games on any model, or real world networks with any assignment of initial cooperation or defection strategies to network nodes. The ability of initially defecting single nodes to break overall cooperation was called as 'game centrality'. The efficiency of this measure was verified on well-known social networks, and was extended to 'protein games', i.e. the simulation of cooperation between proteins, or their amino acids. Hubs and in particular, party hubs of yeast protein-protein interaction networks had a large influence to convert the cooperation of other nodes to defection. Simulations on methionyl-tRNA synthetase protein structure network indicated an increased influence of nodes belonging to intra-protein signaling pathways on breaking cooperation. The efficiency of single, initially defecting nodes to convert the cooperation of other nodes to defection in social dilemma games may be an important measure to predict the importance of nodes in the integration and regulation of complex systems. Game centrality may help to design more efficient interventions to cellular networks (in forms of drugs), to ecosystems and social networks.

Network-based tools for the identification of novel drug targets.

In the past few years, network-based tools have become increasingly important in the identification of novel molecular targets for drug development. Systems-based approaches to predict signal transduction-related drug targets have developed into an especially promising field. Here, we summarize our studies, which indicate that modular bridges and overlaps of protein-protein interaction and signaling networks may be of key importance in future drug design. Intermodular nodes are very efficient in mediating the transmission of perturbations between signaling modules and are important in network cooperation. The analysis of stress-induced rearrangements of the yeast interactome by the ModuLand modularization algorithm indicated that components of modular overlap are key players in cellular adaptation to stress. Signaling crosstalk was much more pronounced in humans than in Caenorhabditis elegans or Drosophila melanogaster in the SignaLink (http://www.SignaLink.org) database, a uniformly curated database of eight major signaling pathways. We also showed that signaling proteins that participate in multiple pathways included multiple established drug targets and drug target candidates. Lastly, we caution that the pervasive overlap of cellular network modules implies that wider use of multitarget drugs to partially inhibit multiple individual proteins will be necessary to modify specific cellular functions, because targeting single proteins for complete disruption usually affects multiple cellular functions with little specificity for a particular process. Tools for analyzing network topology and especially network dynamics have great potential to identify alternative sets of targets for developing multitarget drugs.

Network strategies to understand the aging process and help age-related drug design.

Recent studies have demonstrated that network approaches are highly appropriate tools for understanding the extreme complexity of the aging process. Moreover, the generality of the network concept helps to define and study the aging of technological and social networks and ecosystems, which may generate novel concepts for curing age-related diseases. The current review focuses on the role of protein-protein interaction networks (inter-actomes) in aging. Hubs and inter-modular elements of both interactomes and signaling networks are key regulators of the aging process. Aging induces an increase in the permeability of several cellular compartments, such as the cell nucleus, introducing gross changes in the representation of network structures. The large overlap between aging genes and genes of age-related major diseases makes drugs that aid healthy aging promising candidates for the prevention and treatment of age-related diseases, such as cancer, atherosclerosis, diabetes and neurodegenerative disorders. We also discuss a number of possible research options to further explore the potential of the network concept in this important field, and show that multi-target drugs (representing 'magic-buckshots' instead of the traditional 'magic bullets') may become an especially useful class of age-related drugs in the future.