User:TheLarry/Notebook/Larrys Notebook/2009/08/04

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Agent Base Modeling
After talking with Koch yesterday it seems like taking an agent based modeling approach will be more interesting. We'll treat each head as a different object and watch as their interact.

To do this i'll need a sub.vi that figures out the rate constants for each situation which is encountered. I thought about making a giant matrix and just looking up terms but this would be difficult and i want to see it work before i make it more complicated.

So each head can be in a state of |position; state; nucleotide> which means it is defined with where it is right now, bound/unbound to MT, and if it has a nucleotide currently bound to it.

So i'll need to calculate each rate constant for each state that comes across for both heads. There seems to be 12 rate constants. + means that it is moving forward, and - is backwards.

So there it is 12 different rate constants. I think i have to calculate each one for each time the state changes. Most of these will be zero of course.

I forgot the kinesin coming off the MT in general, but that should happen if the other foot disassociates while the other is in the air.

So there are 16 different states possible (2 positions * 2 states * 4 nucleotide = 16 possible). This is why i thought about a matrix. But the elements in the matrix would have to be arrays of the 12 k's? I don't know and am not gonna think about it now.

So let's get started

Categories: Kinetic Monte Carlo for Kinesin Processivity

ATP Binding

 * 1) Strain needs to be relieved.
 * 2) *This is a bit controversial. Block says strain is relieved when phosphate is released in Kinesin Motor Mechanics: Binding, Stepping, Tracking, Gating and Limping
 * 3) *Also said strain is relieved when the other foot unbinds like in Kinesin: World's Tiniest Biped by Charles Asbury.
 * 4) **Asbury uses an earlier Block paper as a source for this but since Block says it later that phosphate release is needed i'll go with him.
 * 5) Head needs to be empty
 * 6) Head needs to be in front
 * 7) Head needs to be bound

ATP released
not sure what else have to get back to this
 * 1) ATP needs to be bound

ATP Hydrolysis

 * 1) Foot must be behind
 * 2) ATP must be attached

ADP-P phosphorylation

 * 1) Foot needs to be in ADP-P state

Pi release
There needs to be another state. like this needs to be behind or something but i can't find anything that states that explicitly
 * 1) Needs to be in ADP-P state

Pi enter

 * 1) Needs to be in ADP state

Unbind from MT

 * 1) Needs to be behind
 * 2) ATP needs to be in front
 * 3) *This creates a forward strain that pulls the foot forward
 * 4) **This might not be so much a pre-requisite as it increases the rate constant
 * 5) Needs to have ADP attached
 * 6) Needs to be bound

Bind to MT

 * 1) needs to be unbound

Diffuse forward

 * 1) needs to be unbound
 * 2) needs to be behind

Diffuse backward

 * 1) needs to be unbound
 * 2) needs to be in front

ADP release

 * 1) ADP needs to be bound to foot
 * 2) Needs to be in front
 * 3) needs to be bound
 * 4) other foot needs to be bound

ADP enter
=Tomorrow= I have completed what Koch suggested, and a base program is now completed. I am gonna put in some fake values to see if it is actually working tomorrow. I'll try to make it fit the flow. it should be fun. and by fun i mean crazy annoying to put in numbers in like 20 3 element arrays. but i am curious to see it work.
 * 1) foot needs to be empty

Just read Theoretical model for motility and processivity of two-headed molecular motors. It is a model based on 3 object diffusion with limiting factors that they have to be close and some rate constants have to be small and shit like that. But this goes into long discussion about rate constants into what i call weird states in my program. Most of the time he just says that they should be small.

Kinesin Motors: No Strain, No Gain: this article is a quick review of some work Yildiz did. It basically is a good review of how strain affects processivity.


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