1. An Analysis of Emergent Behavior Among Molecular Motors Within a Cell By Alexander Bush

2. Review of Literature Molecular Motors are microscopic proteins that have the ability to do work. They hydrolyze ATP in order to accomplish a multitude of different tasks within a cell. For example, RNA polymerase builds RNA, Myosin allows our skeletal muscles to move, and Dynein and Kinesin move substances within a cell.

4. Review of Literature Much is known about Kinesin Kinesin has a known average run length of approximately 100 steps. Each step is 8nm in length.(Bustamante, 2004) It is known that Kinesin travels towards the positive end of a microtubule.

5. Hypothesis If the persistence length of microtubules is increased, the molecular motors will be more efficient in reaching the positive ends of the microtubules.

6. Methods StarLogo TM was chosen because it is designed specifically for modelling large numbers of homogeneous agents. Also, it has been used in previous experiments.(Wong, 2004) 51 pixels by 51 pixels.

7. Example Simulation Window Microtubule PositiveNegative=Kinesin Motor

8. Methods When the motors are not attached to the tubes, they move around via Brownian motion. When the motor comes across a microtubule, it will bind to the microtubule and walk along the tube until it either falls off, or encounters and obstacle.

9. Methods Tubes were randomly generated each time. Each simulation began with the 50 molecular motors placed randomly throughout the map. In the simulation, a Gaussian distribution with a mean of 100 and a variance of 10 was used to simulate the step length.

10. Methods Persistence length of the tubes was modified. Position of each molecular motor was recorded after every frame (approximately 0.01 seconds). The simulation was run for approximately 1 second (100 frames).

11. Persistence Length: 1

12. Persistence Length: 9

13. Example Output

14. Condensed Data Time: 4 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 3 1 1 1 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0

15. Methods A Poisson distribution is a random distribution, and the unique property of a Poisson distribution is that the variance is equal to the mean. R = s 2 /x s 2 = variance x = mean R value represents the amount of correlation or grouping within the pattern of the motors.

16. The Effect of Persistence Length on the Speed of Motor Grouping

17. The Effect of Persistence Length on the Speed of Motor Grouping(Best Fit Line)

18. Rate of Grouping(Slope)

19. Conclusion It was found that there is an optimal persistence length of the microtubules. Tubules that are too curly are not efficient in directing the motors, while tubules that are too stiff do not cover as much surface area.

20. Conclusion If there was more time available, it would be desirable to run more simulations in order to create a more accurate model of the relationship. The effect of the mean and variance of the average run length of the molecular motors could be experimented upon.