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Kim “Avrama” Blackwell George Mason University Modelling Biochemical Reactions - Tutorial Second Latin American School on Computational Neuroscience

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Page 1: Kim “Avrama” Blackwell George Mason University Modelling Biochemical Reactions - Tutorial Second Latin American School on Computational Neuroscience

Kim “Avrama” Blackwell

George Mason University

Modelling Biochemical Reactions - Tutorial

Second Latin American School on Computational

Neuroscience

Page 2: Kim “Avrama” Blackwell George Mason University Modelling Biochemical Reactions - Tutorial Second Latin American School on Computational Neuroscience

Three Types of Objects

• Pools of molecules– Keep track of concentration

• Uni- and Bi-molecular Reactions– Transformation of one or more molecules

into equal number of another molecule

• Enzyme reactions– One enzyme molecule can transform

multiple copies of substrate into equal number of product

Page 3: Kim “Avrama” Blackwell George Mason University Modelling Biochemical Reactions - Tutorial Second Latin American School on Computational Neuroscience

Compartment-Like Objects•Keep track of molecule quantities and concentrations

• Similar to compartment calculating voltage

–Requires geometry/morphology values• length

• radius

• area of outer surface

• area of inner surface (can be zero)

• area of side surface

• volume

Page 4: Kim “Avrama” Blackwell George Mason University Modelling Biochemical Reactions - Tutorial Second Latin American School on Computational Neuroscience

Compartment-Like Objects• Keep track of molecule quantities and

concentrations– rxnpool (Chemesis)

• dC/dt = A - B C

• A = change in quantity independent of present quantity

• B = rate of change

• Receives messages with quantities A and/or B from other objects (enzymes, reactions, also calcium influx)

•RXN0 (A), RXN1 (B), RXN2 (A and B)

Page 5: Kim “Avrama” Blackwell George Mason University Modelling Biochemical Reactions - Tutorial Second Latin American School on Computational Neuroscience

Compartment-Like Objects• Keep track of molecule quantities and

concentrations– conservepool (Chemesis)

• C = Ctot - Ci

• Quantity is remainder after all other forms of molecule accounted for

– pool (Kinetikit)

• dC/dt = A - B C

• Or C = Ctot - Ci(if flag is set to conserve)

• Can also implement stochastic reactions

Page 6: Kim “Avrama” Blackwell George Mason University Modelling Biochemical Reactions - Tutorial Second Latin American School on Computational Neuroscience

Concentration Pools• chemesis

• genesis #1 > showobject rxnpool

• genesis #2 > showobject conservepool

• genesis #3 > showobject pool

Page 7: Kim “Avrama” Blackwell George Mason University Modelling Biochemical Reactions - Tutorial Second Latin American School on Computational Neuroscience

Enzyme and Reaction objects

• Calculate changes due to reactions– mmenz (Chemesis)

• Use if MM assumptions are met

• Fields: Km and Vmax

• Inputs: enzyme, substrate concentration

• Calculates Vmax times [Enzyme] times

[substrate] divided by ([substrate] + Km)

• Send messages RXN0 or RXN0moles to rxnpool

• Empirical feedback modification of enzyme activity can be added

Page 8: Kim “Avrama” Blackwell George Mason University Modelling Biochemical Reactions - Tutorial Second Latin American School on Computational Neuroscience

Enzyme and Reaction objects

• Calculate changes due to reactions– Enzyme (Chemesis)

• Fields: Kcat, Kf, Kb

• Inputs: enzyme, substrate quantity

• Calculates amount of Enzyme-Substrate complex

• Calculates change in product, enzyme, substrate

– Enz (kinetikit)• Fields: Kcat, Kf, Kb

• Inputs: enzyme, substrate quantity

• Can implement stochastic reactions

Page 9: Kim “Avrama” Blackwell George Mason University Modelling Biochemical Reactions - Tutorial Second Latin American School on Computational Neuroscience

Enzyme and Reaction objects

• Calculate changes due to reactions– reaction (Chemesis) or reac (kinetikit)

• Fields: kf, kb

• Inputs (messages): substrates and products

• Calculates:– forward rate constant times substrate molecules– backward rate constant times product molecules

• send messages RXN0 - RXN2 to rxnpool

Page 10: Kim “Avrama” Blackwell George Mason University Modelling Biochemical Reactions - Tutorial Second Latin American School on Computational Neuroscience

Enzyme and Reaction objects

• Genesis #4> showobject mmenz

• Genesis #5> showobject enzyme– Compartment dimensions allows

membrane bound enzyme to have different volume than substrate and products

• Genesis #5> showobject enz

• Genesis #6> showobject reaction

• Genesis #7> showobject reac

Page 11: Kim “Avrama” Blackwell George Mason University Modelling Biochemical Reactions - Tutorial Second Latin American School on Computational Neuroscience

Creating Chemesis Simulation

• Create rxnpool pool1

• Create conservepool pool2

• Setfield pool1 Cinit initvalue ...

• Addmsg pool1 pool2 CONC Conc– mGlu-IP3-enz.g for complete examples

Page 12: Kim “Avrama” Blackwell George Mason University Modelling Biochemical Reactions - Tutorial Second Latin American School on Computational Neuroscience

Creating Chemesis Simulation

• Create reaction rxn1• Setfield rxn1 kf kfvalue kb kbvalue• Addmsg pool1 rxn1 SUBSTRATE Conc• Addmsg pool2 rxn1 SUBSTRATE Conc• Addmsg pool3 rxn1 PRODUCT Conc• Addmsg rxn1 pool1 RXN2 kbprod

kfsubs– To substrate – kbprod is first

• Addmsg rxn1 pool3 RXN2 kfsubs kbprod– To product – kfsubs is first

Page 13: Kim “Avrama” Blackwell George Mason University Modelling Biochemical Reactions - Tutorial Second Latin American School on Computational Neuroscience

Chemesis Example

• Metabotropic receptor to PLC to IP3

– Include param.g– Include mGlu-IP3-enz.g– Listglobals– Create neutral purkcell– Create neutral glutamate (under purkcell)

• Allow setting a concentration of neurotransmitter

– Invoke function (no parentheses or commas)

– Include graphs.g (and invoke function)– Step (to run simulation)

Page 14: Kim “Avrama” Blackwell George Mason University Modelling Biochemical Reactions - Tutorial Second Latin American School on Computational Neuroscience

XPP example

• Xppaut mglu-ip3.ode– Evaluate role of aG decay– Evaluate role of IP3 decay