Molecular and Nanometer-Scale Self-Organized System Generated by Protein Motor Functions

2007 ◽  
Vol 539-543 ◽  
pp. 3290-3296 ◽  
Author(s):  
Kazuhiro Oiwa ◽  
R. Kometani ◽  
Dong Yang Li ◽  
Y. Shitaka ◽  
R. Nakamori ◽  
...  

Creatures have evolved extremely intelligent and complex adaptive systems for conducting their movements. They are protein motors with typical sizes of a few tens of nanometers. Protein motors include three major protein families, myosin, kinesin and dynein, which participate in a wide range of cellular processes, using energy from the hydrolysis of adenosinetriphosphate ATP. To harness these protein motors to power nanometer-scale devices, we have investigated effective and non-destructive methods for immobilizing protein motors on surfaces and to arrange the output of these motors, e.g. force and movement, to be in a defined direction. We found NEB-22 to be useful for retaining the abilities of protein motors to support the movement of protein filaments. We fabricated various patterns of tracks of NEB-22 on coverslips and protein motors were introduced and immobilized on glass surface. The trajectories of protein polymers were confined to these tracks. Simple patterns readily biased and guide polymer movement confining it to be unidirectional. In addition, having used dynein c purified from Chlamydomonas flagellar axoneme, we showed that microtubules driven by surface-bound dynein were self-organized into dynamic streams through collisions between the microtubules and their subsequent joining.

Author(s):  
Vineet R. Khare ◽  
Frank Zhigang Wang

The need for a dynamic and scalable expansion of the grid infrastructure and resources and other scalability issues in terms of execution efficiency and fault tolerance present centralized management techniques with numerous difficulties. This chapter presents the case for biologically inspired grid resource management techniques that are decentralized and self organized in nature. To achieve the desired de-centralized resource management, these techniques model the self-organization observed in many natural complex adaptive systems. Using a few representative techniques, the authors review the literature on Bio-inspired Grid Resource Management. Based on this review the authors conclude that many such techniques have been successfully applied to resource discovery, service placement, scheduling and load balancing.


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