CZ5225 Methods in Computational BiologyCZ5225 Methods in Computational Biology

Lecture 9: Biological pathways and Lecture 9: Biological pathways and pathway simulationpathway simulation

Prof. Chen Yu ZongProf. Chen Yu Zong

Tel: 6874-6877Tel: 6874-6877Email: Email: csccyz@nus.edu.sgcsccyz@nus.edu.sghttp://xin.cz3.nus.edu.sghttp://xin.cz3.nus.edu.sg

Room 07-24, level 7, SOC1, NUSRoom 07-24, level 7, SOC1, NUSAugust 2004August 2004

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Biological pathways • Describe series of molecular events in living systems. • Important in understanding living systems, disease processes,

effect of drugs or mutations on living systems.

Annu. Rev. Biophys. Biomol. Struct. 27, 199-224 (1998)

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Biological pathwaysBiological pathways

                     

        

 

Map of pathways:

Pathway database: KEGG http://www.genome.ad.jp/kegg/kegg2.html

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Multiple biological pathways:Multiple biological pathways: Viral infection as an exampleViral infection as an example

How SARS coronavirus enters a cell and reproduce

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Multiple biological pathways: Multiple biological pathways: Viral infection as an exampleViral infection as an example

Viral induced immune response: cytosine productionTherapeutically relevant multiple pathways database http://xin.cz3.nus.edu.sg/group/trmp/trmp.asp

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Multiple biological pathways: Multiple biological pathways: Viral infection as an exampleViral infection as an example

Viral induced immune response: cytosine productionTherapeutically relevant multiple pathways database http://xin.cz3.nus.edu.sg/group/trmp/trmp.asp

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Biological pathway databases

Biological pathway databases:

• KEGG: Kyoto Encyclopedia of Genes and Genomes. • SPAD: Signaling Pathway Database. • CSNDB: Cell Signaling Networks Database. • PFBP: Protein Function and Biochemical Pathways.

Multiple pathway databases:

• Therapeutically relevant multiple pathways database http://xin.cz3.nus.edu.sg/group/trmp/trmp.asp

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Simulation of a biological pathway

Computer method appears to be the only practical approach (mainly involving no more than a few dozen proteins)

Nature Biotech. 18, 768-774 (2000)

dx1/dt = k1- X2 - k1+ L x1 + w1

dx2/dt = k1+ L X1 - (k1- + k2 )x2

dx3/dt = k2 X2 + k3- X5

L = Fas ligand, x1=ligand-free Fas surface receptor, x2=ligand-bound Fas surface receptor, x3=clustered ligand-bound Fas surface receptor, x4=FADD protein, x5=complex of FADD-Fas receptor

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Simulation of a biological pathway

Quantitative description of a pathway

Nature Biotech. 18, 768-774 (2000)

Protein concentration and variation

dx1/dt = k1- X2 - k1+ L x1 + w1

dx2/dt = k1+ L X1 - (k1- + k2 )x2

dx3/dt = k2 X2 + k3- X5

L = Fas ligand, x1=ligand-free Fas surface receptor, x2=ligand-bound Fas surface receptor, x3=clustered ligand-bound Fas surface receptor, x4=FADD protein, x5=complex of FADD-Fas receptor

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Simulation of a biological pathway

Construction of reaction/binding equations

Nature Biotech. 18,768-774 (2000)

L = Fas ligand

R=ligand-free Fas surface receptor~RL=ligand-bound Fas surface receptor

RL=clustered ligand-bound Fas surface receptor

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Simulation of a biological pathway

Construction of reaction/binding kinetic equations

Nature Biotech. 18,768-774 (2000)

L = Fas ligand

R=ligand-free Fas surface receptor~RL=ligand-bound Fas surface receptor

RL=clustered ligand-bound Fas surface receptor

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Simulation of a biological pathway

Nature Biotech. 18,768-774 (2000)

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CZ5225 Methods in Computational Biology Assignment 3Assignment 3