LSM3241: Bioinformatics and Biocomputing Lecture 9: Biological Pathway Simulation Prof. Chen Yu Zong Tel: Room 07-24, level 7, SOC1, NUS

2 Biomolecular Interaction: Enzyme + Substrate E + S ==> E + P This is a generalization of how a biochemist might represent the function of enzymes.

3 Biomolecular Interaction: Enzyme + Substrate E + S ==> E + P kinase-ATP complex + inactive-enzyme ==> Kinase + ADP + active enzyme K ATPADP P Here is an example of the generalization represented by two different ways.

4 Biomolecular Interaction: Enzyme + Substrate This is another representation. Kinase-ATP complex Active enzyme inactive enzyme ADP

5 Spoke and Matrix Models of Protein-Protein Interactions Vrp1 (bait), Las17, Rad51, Sla1, Tfp1, Ypt7 Spoke Matrix Possible Actual Topology Bader&Hogue Nature Biotech Oct 20(10):991-7 Simple model Intuitive, more accurate, but can misrepresent Theoretical max. no. of interactions, but many FPs

6 Synthetic Genetic Interactions in Yeast Tong, Boone Cell Polarity Cell Wall Maintenance Cell Structure Mitosis Chromosome Structure DNA Synthesis DNA Repair Unknown Others

7 Glycolysis –Phosphorylation –Pyruvate Anaerobic respiration Lactate production 2 ATPs produced Metabolic Pathway: ATP Production

8 Cyclic Metabolic Pathway

9 Methods of Metabolic Engineering

10 Generic Signaling Pathway Signal Receptor (sensor) Transduction Cascade Targets Response Altered Metabolism Metabolic Enzyme Gene Regulator Cytoskeletal Protein Altered Gene Expression Altered Cell Shape or Motility

11 Components of Signaling What can be the Signal? External message to the cell Peptides / Proteins- Growth Factors Amino acid derivatives - epinephrine, histamine Other small biomolecules - ATP Steroids, prostaglandins Gases - Nitric Oxide (NO) Photons Damaged DNA Odorants, tastants Signal = LIGAND Ligand- A molecule that binds to a specific site on another molecule, usually a protein, ie receptor

12 Components of Signaling What are Receptors? Sensors, what the signal/ligand binds to initiate ST Cell surface Intracellular Hydrophillic Ligand Cell-Surface Receptor Plasma membrane Hydrophobic Ligand Carrier Protein Intracellular Receptor Nucleus

13 Generic Signal Transduction

14 RTK Signal Transduction

15 Signal Transduction Downstream effectors Protein Signaling Modules (Domains) SH2 and PTB bind to tyrosine phosphorylated sites SH3 and WW bind to proline-rich sequences PDZ domains bind to hydrophobic residues at the C-termini of target proteins PH domains bind to different phosphoinositides FYVE domains specifically bind to Pdtlns(3)P (phosphatidylinositol 3-phosphate)

16 Mechanisms for Activation of Signaling Proteins by RTKs Activation by membrane translocation Activation by a conformational change Activation by tyrosine phosphorylation

17 Mechanisms for Attenuation & Termination of RTK Activation 1) Ligand antagonists 2) Receptor antagonists 3) Phosphorylation and dephosphorylation 4) Receptor endocytosis 5) Receptor degradation by the ubiquitin-proteosome pathway

18 Activation of MAPK Pathways by Multiple Signals Growth, differentiation, inflammation, apoptosis -> tumorigenesis

19 Overview of MAPK Signaling Pathways

20 The MAPK Pathway Activated by RTK

21 RTK ST- PI3K pathway P

22 Apoptosis Pathways

23 TGF Pathway

24 Constructing a pathway model: things to consider 1. Dynamic nature of biological networks. Biological pathway is more than a topological linkage of molecular networks. Pathway models can be based on network characteristics including those of invariant features.

25 Constructing a pathway model: things to consider 2. Abstraction Resolution: How much do we get into details? What building blocks do we use to describe the network? High resolution Low resolution (A) Substrates and proteins (B) Pathways (C) “special pathways”

26 Constructing a pathway model Step I - Definitions We begin with a very simple imaginary metabolic network represented as a directed graph: Vertex – protein/substrate concentration. Edge - flux (conversion mediated by proteins of one substrate into the other) Internal flux edge External flux edge How do we define a biologically significant system boundary?

Constructing a pathway model Step II: Interaction Kinetics E + S ==> E + P kinase-ATP complex + inactive-enzyme ==> Kinase + ADP + active enzyme K ATPADP P

28 Reversibility of Chemical Reactions: Equilibrium Chemical reactions are reversible Under certain conditions (concentration, temperature) both reactants and products exist together in equilibrium state H 2  2H

29 Reaction Rates Net reaction rate = forward rate – reverse rate In equilibrium: Net reaction rate = 0 When reactants “just” brought together: Far from equilibrium, focus only on forward rate But, same arguments apply to the reverse rate

30 The Differential Rate Law How does the rate of the reaction depend on concentration? E.g. 3A + 2B  C + D rate = k [A] m [B] n (Specific reaction) rate constant Order of reaction with respect to A Order of reaction with respect to B m+n: Overall order of the reaction

31 Rate Constants and Reaction Orders Each reaction is characterized by its own rate constant, depending on the nature of the reactants and the temperature In general, the order with respect to each reagent must be found experimentally (not necessarily equal to stoichiometric coefficient)

32 Elementary Processes and Rate Laws Reaction mechanism: The collection of elementary processes by which an overall reaction occurs The order of an elementary process is predictable UnimolecularA*  BK + [A] First order Bimolecular A + B  C + D K + [A] [B] Second order Trimolecular A + B + C  D + E K + [A] [B] [C] Third order

33 Elementary Processes and Rate Laws Reaction mechanism: The collection of elementary processes by which an overall reaction occurs The order of an elementary process is predictable UnimolecularA*  BK + [A] – K - [B] First order Bimolecular A + B   C + D K + [A] [B] – K - [C] [D] Second order Trimolecular A + B + C   D + E K + [A] [B] [C] – K - [D] [E] Third order

34 Stoichiometry Matrix Flux vectorConcentration vector Constructing a pathway model Step III - Dynamic mass balance

35 A ‘simple’ ODE model of yeast glycolysis

36 A model pathway system and its time-dependent behavior Positive Feedback Loop

37 A model pathway system and its time-dependent behavior

38 A model pathway system and its time-dependent behavior