Transcript Biologically Inspired Molecular Engineering

An Exhibition of Applications:
Molecular Computing
Dr. Chrisantha Fernando
Systems Biology Centre
Birmingham University
Don’t think we can escape from
chemotaxis just yet…
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http://flash.uchicago.edu/~emonet/biology/agentcell/
Stochastic Modeling
 So far we have been doing deterministic modeling.
 Stochastic models consider individual molecules,
undergoing discrete reaction events, i.e. chemical
(autonomous) agents.
 These models diverge from deterministic models when
particle numbers are low, but also they allow “emergent”
reactions…
 To get a feel for stochastic modeling, try BioNetS.
BioNetS
Easy to use
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Here is a paper written using the
tool…
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Lets start with some simple
chemical networks…
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R
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RCheZ
Rm
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CheZ
Example of a Saturated Enzyme (CheZ) acting to methylate R
Applications
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Development and Cellular Differentiation
A Molecular Machine: Bacteriorhodopsin
Molecular Self-Assembly
Liquid State Machines in Cellular
Networks?
Development
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http://www.cogs.susx.ac.uk/users/inmanh/easy/alife06/Lecture%206/lec06.pdf
http://www.bio.unc.edu/courses/2006Spring/Biol052-006/April%2010%20-%20Drosophila%20A-P%20polarity.ppt
Fly Development
T1
anterior
T2
head
thorax
T
dorsal
T3
A1
A2
A3
abdomen
A4
A
A5
A6
posterior
egg
epithelium
(6,000 cells)
A7
“stripy” expression
of segmentation gene
fushi tarazu (ftz)
blastoderm
A8
fate map
larva
(cuticle)
A diffusion gradient is set up by
maternally expressed genes
bcd mRNA
Bcd protein
anterior
posterior
The Reaction Diffusion Principle
cells
source of
morphogen
threshold blue
threshold white
cells
The Fly ‘French Flag’ colors are
made like this…
bcd protein binds differentially to enhancers of target (gap) genes
low affinity
high affinity
target genes are zygotically expressed gap genes
maternally expressed genes
> protein gradients
caudal
bicoid
zygotically expressed genes
bicoid
Krüppel
(gap gene)
> distinct protein expr. domain
bicoid
even-skipped
(pair-rule gene)
> 7 stripes of protein expr.
From Bio to Techno
 Can we make self-assembling, selforganizing machines that utilize the robust
mechanisms displayed by multicellular
development?
The French Flag Problem
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http://www.elec.york.ac.uk/intsys/users/jfm7/gecco2004.pdf
MIT Amorphous Computing Lab
 Printable computers
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http://www-swiss.ai.mit.edu/projects/amorphous/papers/butera-phd.pdf
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Asynchrony
= Stochastic noise in/between cells
Fault tolerance
= Protein misfolding/non-specific binding
Spatial constraints = Allostery and diffusion constraints
Adaptable topology = Individual differences between cells/organs
Code compactness = Slow protein conformation changes
"A programming model employing a self-organizing ecology of mobile process fragments
supports a variety of useful applications on a paintable computer”
Inspired by biological development
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http://chaos.c.u-tokyo.ac.jp/study/papers1.html
Archaebacteria Halobacteria Salinarium absorbs green
light
Bacteriorhodipsin
protons are pumped
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one at a time from the
inside of the cell to the outside
Photons react with a bound retinal group
causing conformational change in BR
1. Retinal changes form when absorbing a photon
www.chembio.uoguelph.ca/educmat/chm455/bacterio.ppt
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http://www.ks.uiuc.edu/Services/Class/BIOPHYS490M/04-bR-retinal.pdf
Agent Based Models of
‘Molecular’ Self-Assembly
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Molecular Dynamics
computer simulation is useful
in designing molecular
self-assembling systems
http://www.iupac.org/publications/pac/2003/pdf/7505x0609.pdf
Now for a special guest…
 Ben Jones (PhD student), will talk about our
recent paper that we will present in Hawaii
this weekend.
 We model the gene transcription network of
E.Coli, and ask if it works like a bucket of
water.