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Lecture 2: Overview of Computer Simulation of Lecture 2: Overview of Computer Simulation of Biological Pathways and Network Crosstalk Biological Pathways and Network Crosstalk Y.Z. Chen Y.Z. Chen Department of Pharmacy Department of Pharmacy National University of Singapore National University of Singapore Tel: 65-6616-6877; Email: Tel: 65-6616-6877; Email: [email protected] [email protected] ; Web: ; Web: http://bidd.nus.edu.sg http://bidd.nus.edu.sg Content Content Biological pathways and crosstalk Biological pathways and crosstalk Simulation model development Simulation model development Example: Development of simulation model of Example: Development of simulation model of RhoA crosstalk to EGFR-ERK pathways RhoA crosstalk to EGFR-ERK pathways Future perspectives: more pathways, more Future perspectives: more pathways, more crosstalk, network level drug effects, crosstalk, network level drug effects, signaling specificity, component sensitivity, signaling specificity, component sensitivity, TCM mechanism TCM mechanism

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Lecture 2: Overview of Computer Simulation of Biological Pathways and Network Crosstalk Y.Z. Chen Department of Pharmacy National University of Singapore Tel: 65-6616-6877; Email: [email protected] ; Web: http://bidd.nus.edu.sg. Content Biological pathways and crosstalk - PowerPoint PPT Presentation

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Page 1: Content Biological pathways and crosstalk Simulation model development

Lecture 2: Overview of Computer Simulation of Biological Lecture 2: Overview of Computer Simulation of Biological Pathways and Network Crosstalk Pathways and Network Crosstalk

Y.Z. ChenY.Z. ChenDepartment of PharmacyDepartment of Pharmacy

National University of SingaporeNational University of Singapore Tel: 65-6616-6877; Email: Tel: 65-6616-6877; Email: [email protected]@nus.edu.sg ; Web: ; Web: http://bidd.nus.edu.sghttp://bidd.nus.edu.sg

ContentContent

• Biological pathways and crosstalkBiological pathways and crosstalk

• Simulation model developmentSimulation model development

• Example: Development of simulation model of RhoA crosstalk Example: Development of simulation model of RhoA crosstalk to EGFR-ERK pathwaysto EGFR-ERK pathways

• Future perspectives: more pathways, more crosstalk, network Future perspectives: more pathways, more crosstalk, network level drug effects, signaling specificity, component sensitivity, level drug effects, signaling specificity, component sensitivity, TCM mechanismTCM mechanism

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Generic Signaling PathwayGeneric Signaling PathwaySignal

Receptor (sensor)

Transduction Cascade

Targets

Response Altered Metabolism

MetabolicEnzyme

Gene Regulator Cytoskeletal Protein

Altered Gene

Expression

Altered Cell Shape or Motility

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Integrated circuit of the cell

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EGFR-ERK/MAPK Signaling Pathways

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Crosstalk of Rho and Ras

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The Multiple Functions of Rho

Aznar & Lacal Cancer Lett 165, 1 (2001)Hall Biochem Society Transactions 33, 891 (2005)

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Actin Cytoskeleton Regulation Pathways

KEGG database

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Crosstalk between RhoA and EGFR-ERK/MAPK via MEKK1 and PTEN

• RhoA promotes ERK activation by its interaction with Rho kinase, an effector of RhoA, which helps to delay EGF receptor endocytosis by phosphorylating endophilin A1 and to prevent Akt inhibition of Raf by activating phosphatase PTEN that hydrolyzes Akt second messenger PIP3.

• RhoA binds to MEKK1 and activate its kinase activity which subsequently phosphorylates and activates MEK1

• As activated MEK1 promotes ERK activation, it is of interest to examine to what extent RhoA can prolong ERK/MAPK activity via this MEKK1-mediated crosstalk between RhoA and EGFR-ERK signaling networks

Gallagher et al. J Biol Chem 2004: 279, 1872

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RhoA's crosstalk to EGFR-mediated Ras/MAPK activation via MEKK1

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RhoA's crosstalk to EGFR-mediated Ras/MAPK activation via PTEN

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Pathway Mathematical ModelPathway Mathematical Model• Biochemical kinetics based on mass action law (Guldberg

and Waage 1864)

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Fussenegger et al Nature Biotech 18, 768 (2000)

Schoeberl et al Nature Biotech 20, 370 (2002)Sasagawa et al Nature Cell Biol 7, 365 (2005)Kiyatkin et al J Biol Chem 281, 19925 (2006)

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Pathway Mathematical ModelPathway Mathematical Model• Biochemical kinetics based on mass action law (Guldberg

and Waage 1864)

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Fussenegger et al Nature Biotech 18, 768 (2000)

Schoeberl et al Nature Biotech 20, 370 (2002)Sasagawa et al Nature Cell Biol 7, 365 (2005)Kiyatkin et al J Biol Chem 281, 19925 (2006)

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Pathway Mathematical ModelPathway Mathematical Model• Michaelis-Menton Kinetics (Leonor Michaelis 1875-1947;

Maud Menton 1879-1960)• The rate of the reaction is equal to the negative rate of

decay of the substate as well as the rate of product formation

• Initial concentration of the substrate is much larger than the concentration of the enzyme

• Leading to:

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Pathway Mathematical ModelPathway Mathematical Model

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Materi & Wishart Drug Discov Today 12, 295 (2007)

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Pathway Mathematical ModelPathway Mathematical Model

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Alderidge et al. Nature Cell Biol 8, 1195 (2006)

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Pathway Mathematical ModelPathway Mathematical Model

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Alderidge et al. Nature Cell Biol 8, 1195 (2006)

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Pathway Mathematical ModelPathway Mathematical Model

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Alderidge et al. Nature Cell Biol 8, 1195

(2006)

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Solving the Pathway EquationsSolving the Pathway EquationsRunge-Kutta methodRunge-Kutta method

• Our task is to solve the differential equation: dx/dt = f(t, y), x(t0)= x0

• Clearly, the most obvious scheme to solve the above equation is to replace the differentials by finite differences:

dt = h dx = x(t+h) - x(t)

• One can then apply the Euler method or first-order Runge-Kutta formula:

x(t+h) = x(t) + h f(t, x(t)) + O(h2) • The term first order refers to the fact that the equation is accurate to first

order in the small step size h, thus the (local) truncation error is of order h2. The Euler method is not recommended for practical use, because it is less accurate in comparison to other methods and it is not very stable.

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Solving the Pathway EquationsSolving the Pathway EquationsRunge-Kutta methodRunge-Kutta method

• The accuracy of the approximation can be improved by evaluating the function f at two points, once at the starting point, and once at the midpoint. This lead to the second-order Runge-Kutta or midpoint method:

k1 = h f(t, x(t)) k2 = h f(t+h/2, x(t)+k1/2) x(t + h) = x(t) + k2 + O(h3)

• The most popular Runge-Kutta formula is the fourth-order one: k1 = h f(t, x(t)) k2 = h f(t+h/2, x(t)+k1/2) k3 = h f(t+h/2, x(t)+k2/2) k4 = h f(t+h, x(t)+k3) x(t + h) = x(t) + k1/6 + k2/3 + k3/3 + k4/6 + O(h5)

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Solving the Pathway EquationsSolving the Pathway EquationsCash-Karp embedded Runge-Kutta algorithmCash-Karp embedded Runge-Kutta algorithm

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Mathematical Model of Mathematical Model of EGFR-ERK/MAPK PathwayEGFR-ERK/MAPK Pathway

• Interaction equations and kinetic parameters

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Mathematical Model of Mathematical Model of EGFR-ERK/MAPK PathwayEGFR-ERK/MAPK Pathway

• Interaction equations and kinetic parameters

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Mathematical Model of Mathematical Model of EGFR-ERK/MAPK PathwayEGFR-ERK/MAPK Pathway

• Analysis of kinetic parameters

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Mathematical Model of Mathematical Model of EGFR-ERK/MAPK PathwayEGFR-ERK/MAPK Pathway

• Analysis of kinetic parameters

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Mathematical Model of Mathematical Model of EGFR-ERK/MAPK PathwayEGFR-ERK/MAPK Pathway

• Analysis of kinetic parameters

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Validation of RhoA EGFR-ERK/MAPK Validation of RhoA EGFR-ERK/MAPK Crosstalk ModelCrosstalk Model

• Time-dependent behavior of EGF activation of ERK in PC12 cells• Our model predicted that ERK activation peaks at ~5 minutes

and decays within ~50 minutes, in good agreement with observation

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Validation of RhoA EGFR-ERK/MAPK Validation of RhoA EGFR-ERK/MAPK Crosstalk ModelCrosstalk Model

• EGF variation on duration of ERK activation in PC12 cells• Our model predicted that further increase of EGF levels leads

to sustained ERK activation, in good agreement with observation and previous simulation results

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Validation of RhoA EGFR-ERK/MAPK Validation of RhoA EGFR-ERK/MAPK Crosstalk ModelCrosstalk Model

• Time-dependent behavior of active RasGTP and their effects on ERK activation in PC12 cells • Our model predicted that RasGTP peaks at ~2.5 minutes and

quickly decays to its basal levels within 20 minutes, in good agreement with observation and previous simulation results

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Validation of RhoA EGFR-ERK/MAPK Validation of RhoA EGFR-ERK/MAPK Crosstalk ModelCrosstalk Model

• Time-dependent behavior of active RasGTP and their effects on ERK activation in PC12 cells• Our model predicted that Ras over-expression prolongs ERK

activation by delaying its decay rate without altering the time cause for reaching the peak of activation, in good agreement with observation and previous simulation results2121 PPSS 2121 PPSS

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Validation of RhoA EGFR-ERK/MAPK Validation of RhoA EGFR-ERK/MAPK Crosstalk ModelCrosstalk Model

• Effect of scaffold protein MEKK1 on ERK activities• Our model predicted that Increased MEKK1 concentration

helps to increase the level of active ERK, delay its peak time, and slightly prolong the duration of ERK activation, in good agreement with observation

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Validation of RhoA EGFR-ERK/MAPK Validation of RhoA EGFR-ERK/MAPK Crosstalk ModelCrosstalk Model

• Effects of Ras over-expression on RhoA and ERK activities• Our model predicted that Ras over-expression increases the

amount of active GTP-bound RhoA and prolongs the duration of its activation, leads to sustained ERK activation, in good agreement with observation and previous simulation results

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Effects of RhoA over-expression on ERK Effects of RhoA over-expression on ERK activationactivation

• When Ras expression is at the normal level, RhoA over-expression was found to prolong ERK activation in a dose-dependent manner

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Effects of RhoA over-expression on ERK Effects of RhoA over-expression on ERK activationactivation

• Effect of scaffold

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Effects of RhoA over-expression on ERK Effects of RhoA over-expression on ERK activationactivation

• When Ras is over-expressed, RhoA over-expression significantly reduces the number of active ERK while further prolonging its activation

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Future Work: Other PathwaysKEGG database

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Pathways and DiseasePathways and Disease

• Mapping normal and cancer cell signalling networks: towards single-cell proteomics Nature Rev Cancer 6, 146, 2006

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Future Trend:More crosstalk

e.g. crosstalk of EGFR-ERK pathway to others via RTK - PI3K – AKT pathways

P

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Future Trend:Network level drug effects

e.g. drug combinations in RTK-ERK and RTK - PI3K – AKT pathways

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Annals Oncology 18, 421 (2007)

Drug metabolism pathway simulation published in PloS Comput Biol 3, e55

(2007)

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Future Trend:Knowledgelearned and informationgained beused forstudying TCM

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Project AssignmentProject Assignment• Project 1: Development of pathway simulation models

• You will be given a section of a biological pathway. You are required to try to generate a more detailed and precise pathway section, derive the corresponding pathway equations and parameters, and implement the equations in an ODE solver

• Project 2: Mechanism of biological crosstalks

• You will be given a few papers of crosstalks between different biological entities. You are required to probe the mechanism of each of these crosstalks based on their network relationships (generated by Pathway studio), expression profiles (generated by microarray analysis), and biochemical or regulatory profiles (from literature reports)