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CATEGORIES:Isaac Newton Institute Seminar Series
SUMMARY:Clustering of cell surface receptors: Simulating t
he mesoscale between reaction-diffusion and atomis
tic scales - Jun Allard (University of California\
, Irvine)
DTSTART;TZID=Europe/London:20160623T090000
DTEND;TZID=Europe/London:20160623T094500
UID:TALK66551AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/66551
DESCRIPTION:Co-author: Omer Dushek (Oxford)
Many biological molecules\, including cell sur
face receptors\, form densely-packed clusters tha
t are weakly bound\, mechanically soft\, and have
volumes on the same order as the volumes of the p
roteins they interact with. Preventing the format
ion of clusters dramatically attenuates proper cel
l function in many examples (including T cell act
ivation and allergen activation in Mast cells)\,
but for unknown reason. Therefore\, receptor clust
ers involve biology hidden at the mesoscale betwe
en individual protein structure (~0.1nm) and the
cell-scale signaling pathways of populations of di
ffusing protein (~1000nm). In some parameter regi
mes\, clusters comprise 10-100 molecules tied to
fixed locations on the cell surface by molecular t
ethers. The Dushek Lab is developing an in vitro
setup that mimics this regime\, and find that the
time courses of binding and enzymatic reactions a
re non-trivial and cannot be fit to simple ODE mo
dels. On the other hand\, fitting to explicitly sp
atial simulatio ns with volume exclusion is prohi
bitively slow. Here we present a fast algorithm f
or tethered reactions with volume exclusion. The a
lgorithm exploits\, first\, the spatially-fixed t
ethers\, allowing us to construct a single nearest
-neighbor tree\, and\, second\, a separation of t
imescales between the fast diffusion of molecular
domains and slow binding and catalytic reactions.
This allows use of a hybrid Metropolis-Gillespie
algorithm: on the fast timescale of domain motion
\, efficient equilibrium algorithms that include
volume exclusion provide the effective concentrat
ions for the slow timescale of binding and catalys
is\, which are simulated using a maximally-fast n
ext-event algorithm. Crucially\, we employ dynami
c connected-set-discovery subroutines to simulate
the minimal subset of molecules each time step. T
he algorithm has computational time scaling appro
ximately with the number of molecules and can repr
oduce the non-trivial time courses observed exper
imentally.
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