Orengo Chapter 10

1. Orengo Chapter 10 From protein structure to function

2. What is function • The particular catalytic activity, binding properties or conformational changes of a protein. • The complex, or metabolic or signal transduction pathway in which a protein participates

3. Methods of functional evolution • Gene duplication – with two copies of a gene, one can retain its function while the other can assume a new biological role. • Gene fusion – two genes are combined and activated by the same promoter • One Gene – to or more functions • Post translational modifications • Alternate splicing

4. Gene Evolution

5. From Structure to Function • With high throughput crystallization techniques, structure can be determined more easily than function

6. Homologous relationships

7. Analogous relationships

8. Conservation of Enzyme Function in CATH Domain Families Structural similarity (SSAP) score Pairwise sequence identity different functions same functions

9. Structural Similarity vs functional similarity Structural similarity (SSAP) score Pairwise sequence identity different functions same functions

10. Once you have function, how do you analyze the systems biology • Build a interaction network • Model response of gene to changes in promoter concentration • Simulate the system to determine influence of gene product on system

11. What are Biological Systems? • Complex systems of simple elements have functions that emerge from the properties of the networks they form. • Biological systems have functions that rely on a combination of the network and the specific elements involved.

12. Molecular vs. Systems Biology Biology • In molecular biology, gene structure and function is studied at the molecular level. • In systems biology, specific interactions of components in the biological system are studied – cells, tissues, organs, and ecological webs.

13. From Systems Biology to Computational Biology Biological Systems are complex, thus, a combination of experimental and computational approaches are needed. Linkages need to be made between molecular characteristics and systems biology results

14. Databases and Tools • Languages • Systems Biology Markup Language • CellML • Systems Biology Workbench • Databases • Kyoto Encyclopedia of Genes and Genomes • Alliance for Cellular Signaling • Signal Transduction Knowledge Environment

15. p53 • Protein 53 • Guardian of the genome • Detects DNA damages • Halts the cell cycle if damage is detected to give DNA time to repair itself

16. p53 If (damage equals true and repairable = true) halt cell cycle else if(damage equals true and repairable = false) induce apoptosis (suicide)

17. The Cell Cycle • G1 - Growth and preparation of the chromosome replication • S - DNA replication • G2 - Preparation for Mitosis • M - Chromosomes separate

18. Checkpoints for DNA Double Strand Breakage ataxia-telangiectasia mutated

19. Cancer Cell Network

20. p53 activates deactivates p53 p21 CDK No cell cycle!

21. p53

22. Cancer Drugs • Alkylating agents - interfere with cell division and affect the cancer cells in all phases of their life cycle. They confuse the DNA by directly reacting with it. • Antimetabolites - interfere with the cell's ability for normal metabolism. They either give the cells wrong information or block the formation of "building block" chemical reactions one phase of the cell's life cycle. • Vinca alkaloids - (plant alkaloids) are naturally-occurring chemicals that stop cell division in a specific phase. • Taxanes - are derived from natural substances in yew trees. They disrupt a network inside cancer cells that is needed for the cells to divide and grow. all inhibit the cell cycle

23. The next step • Once you have simulated gene regulatory networks, build organ or organism models

24. NOBLE, D (2002) Nature Reviews Molecular Cell Biology3, 460-463. Unravelling complexity Need to work in an integrative way at all levels: organism organ tissue cellular sub-cellular pathways protein gene higher levels control cell function & pathways higher levels control gene expression There are feed-downs as well as upward between all these levels

25. ICa ICl Ang II IK1 Ito ß IK 1 M 2 INa Glucose NO Fatty Acids Ca ATP Amino Acids pH H/Lactate I Na/K I NaCa Na/HCO3 Cl/HCO3 Na/H Cl/OH Heart Model Construction 2000 Channels Receptors Substrates Carriers

26. ICaL IKr Em If Example of protein interaction in a cell model Reconstructing the heart’s pacemaker Sinus rhythm generated by ion channel interaction Acceleration of sinus rhythm by adrenaline Rhythm abolished when interaction prevented All 3 protein levels up-regulated If is example of fail-safe ‘redundancy’

27. Disease insight Modelling arrhythmias Mutations in various ionic channels can predispose to repolarization failure This simulation is of a sodium channel mis-sense mutation responsible for idiopathic ventricular fibrillation

28. Expressed sodium channel kinetics (Chen et al, Nature, 19 March 1998)

29. Computer model prediction • Sodium channel missense mutation • 12 and 18 mV voltage shifts • Using digital cell ventricular model 12 mV shift 18 mV shift

30. Unravelling genetics of arrhythmia This approach has now been used for a substantial number of gene manipulations in heart cells and can account for genetic susceptibility to fatal cardiac arrhythmia Including interactions with drugs causing long QT and arrhythmia in clinical trials Genetic typing to screen out those susceptible to drugs causing QT problems is therefore a foreseeable possibility Noble D (2002) Unravelling the genetics and mechanisms of cardiac arrhythmia. Proc Natl Acad Sci USA99, 5755-6

32. Places to experiment • http://thevirtualheart.org • http://www.math.nyu.edu/~griffith/heart_anim • Systems biology and the heart • Modeling the Heart--from Genes to Cells to the Whole Organ • http://domino.research.ibm.com/comm/research_projects.nsf/pages/cancermodeling.index.html