User:TheLarry/Notebook/Larrys Notebook/2009/10/30

Paper Writing

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Main things our simulation can do that others can't After reading through some of these other simulation papers, Kanada-Sasaki, Fisher et al, and Peskin-Oster, I came to the realization that simulation papers are brutally boring. Seriously every time i start i want to gauge my eyes out. Anyways i also came up with a list of things that makes our simulation unique from these three other models Study of rare states and detachment mechanism All three of these papers follow a prescribed core cycle that they don't deviate from. While ours can roam free from the core cycle to see how often rare states are entered This also allows us to analyze how a kinesin detaches since this occurs through a rare state It also allows us to see how environmental changes may increase these rare states Core cycle not assumed Like before these three models follow a core cycle that is set in stone. While ours comes out naturally. This is with the exception of Peskin who doesn't have a core cycle just bound/unbound heads No explicit energy landscape. Ours is 100% stochastic These other models have a combination of stochastic and dynamic (i don't have a good word for it yet) components. This means they usually have a core cycle that they can stochastically bounce through but have an energy landscape that governs motion. So the stochastic part is ATP hydrolysis but then the diffusion is energy landscape same with the binding to the microtubule. Usually this energy landscape is diffusion of the head or it describes the neck linker or binding to the microtubule or a combination of all three. I don't have an advantage of our method over theirs outside that Gillespie said that a stochastic process like this is best examined stochastically. But ours is less math intensive and we might be able to make an argument that making environmentally changes like osmotic pressure is easier to do with our model since it is easier to visualize than in a tanh equation for instance. I am sure there are 100% dynamic simulations but i haven't reached them yet. I just read 3 papers so far. This is going really slowly because of how boring they are, but it is important. And I feel that I am getting a better understanding of the simulations out there and where ours fits in. (Steve Koch 15:57, 30 October 2009 (EDT):You're right that this is really important and I'm really glad you're doing it. I like your conclusions above, it will definitely result in key text in our paper.) TheLarry 16:23, 30 October 2009 (EDT): I started thinking about Block's unbound/bound time. I got something like 50% with more time spent in bound state. And i can't follow his argument for 93% of the time spent in an unbound state. Initially he says that they measure an average of 440 ms unbound and 320 ms bound but then says 93% of the time it is unbound. I don't know--it must make sense i just can't figure it out. If you use 440 and 320 my numbers aren't that far off. I can always do some adjutments to try to get to their numbers but i don't think i can get to 93% unbound without some serious work. Interestingly, right now i am getting 450 ms for unbound and 540 ms for bound. so i almost have block's numbers from that paper except i am off by 200 ms for bound. but then his numbers give an expected walk time of .76 seconds while mine are closer to 1 second. So really i don't know what to make of it, but i think i'll be ok keeping it the same right now. 1. Derenyi I, Vicsek T. The kinesin walk: a dynamic model with elastically coupled heads [Internet]. Proc. Natl. Acad. Sci. USA. 1996 ;936775–6779.Available from: http://www.pnas.org/content/93/13/6775.full.pdf This paper models kinesin with an inch worm motion so i think i can skip this guy