Biomolecular Modelling and Simulation

1. Biomolecular Modelling and Simulation Julia M Goodfellow, Birkbeck College, University of London

2. The Chemical Interface:Simulation and Biodesign • Example: Application of commonly used algorithm is that of molecular dynamics i.e. iterative solution of differential equations describing atomic motion. • One bottleneck is cpu • Second bottleneck is coordinated storage and analysis.

3. PROTEIN MISFOLDING LEADS TO DISEASE Wrong eye-lens crystallins p53 - cancer Wrong Right Human Lysozyme 2 microglobulin Transthyretin Disastrous AMYLOID

4. Human Lysozyme • Two domains: a and b. 130 residue enzyme • Mutation causes repulsion between distal loop and b hairpin of b domain. • Amyloid precursor has been suggested to be formed from destabilised b domain. H-bond networks change. • D67H and I56T lead to non-neuropathic amyloidosis

5. Results: Unfolding rates Results agree with plots from native contacts plots whereby the number of native residue contacts decreases slightly faster in the mutant in all trajectories. Indication that mutant moves faster away from native structure RMSD shows that mutant unfolds slightly faster than wild type. Indication that more susceptible

6. Results: Clustering • Clustering is used to identify favourable partially folded conformations • Most conformations have lost most of their secondary structure. • Highly populated conformational states of the mutant and a few low populated of wild type have distorted β domain • The distortion is more evident in the area of the domain interface (Ile 56).

7. GENERALISE PROBLEM 1 ns simulation on 40,000 atom protein 20 days on typical single processor Aiming for simulations of 10 trajectories of 10 ns = 100 ns UK community say 10 groups of 10 people each studying 5 related systems total days cpu = 20 x 100 x 100 x 5 = 1 x 106 days cpu = 3000 PCs for a year. 1.5 Gb storage per 1 ns simulation = 70 terabytes storage per year.

8. PB electrostatics with conformational change Lowering of pH results in break up of tetramer and changes to the monomer structure for transthyretin Would like to be able to combine modelling of changes in conformation with changes in pH 45,000 atoms with solvent Tyr 116 Tyr116 His88 His90 Glu92

9. Prototype GRID Other centres in future cpu* disk archive Centre with strong link to particle physics community 64 cpu 64 cpu 64 cpu 64 cpu

10. GRID2 for Data Analysis Distributed data - often on tape i.e. not on line Birkbeck Birmingham Oxford Metadata York Southampton REST of WORLD Nottingham

11. First Stage • Metadata - • Define what has been done by whom • is raw data available on line? • make this information available to all • Using Grid tools to allow sub-group (initially) to access raw data

12. Second stage • Do we trust each others data? • Developing a ‘kite’ mark for quality or resolution of data • What are we going to use to do this ?

13. Third Stage Developing analysis tool box ( not reinventing the wheel). How are these to be used? Testing of Grid tools - where do we run the analysis? Do we move ‘code to data’ or ‘data to code’? This may involve sharing of our servers for running programmes.

14. Where do we want to be? • Sharing data with other modellers • Integrating simulation data with other data • Presenting data so it can be used/accessed by non-modellers • Having all singing/all dancing database • Using any spare capacity within our group for number crunching

15. Samuel Butler 1835-1902 We shall never get people whose time is money to take much interest in atoms. Funding: BBSRC, EPSRC Wellcome Trust AICR

16. Acknowledgements George Moraitakis Mark Sansom - Oxford Delphine Flatters Oliver Smart - Birmingham Spiros Skoulakis Jonathan Essex - Southampton Isofina Pournara Leo Caves - York Andy Purkiss Charlie Naughton - Nottingham Thomas Matthews Paul Jeffrey (Oxford) David Boyd & Paul Durham (CLRC)

17. Electrostatic stability of wild type and mutant transthyretin oligomers V30M  90° T119M 90°   pH induced changes

18. CPU timings ~17,000 atoms using Gromacs 2.0 - 8 processor Beowulf Cluster - 6 ns 12.5 days 27,000 atoms using AMBER 6 4 processor Beowulf Cluster - 3 ns 23 days

19. pK1/2 values monomer His31 5.1 His56 4.8 His88 3.9 His90 3.6 Glu54 2.1 Tyr116 9.3 Glu92 0.3

20. pK1/2 values dimer His88 -5.3 His90 -7.6 Tyr116 -1.7 Glu92 -5.3 Tyr116 Glu92 Tyr116 Glu92 His88 His90

21. Free energies D-M 16kcal/mol, T-M 43kcal/mol, pH 7-3.5 D-M 13kcal/mol, T-M 35kcal/mol, pH 7-4 wt1 < wt2  mut_noa < mut_a

22. Conclusions Stability, Yes? Relative stability, No Important residues identified? Desolvation, Descreening Need for a method that allows for conformational flexibility.

23. Stability of -crystallins using molecular dynamics Crystallin X-ray crystal structure to 1.2Å Andy Purkiss -crystallin features • A two domain protein, each domain around 80 residues. • Each domain has a pair of ß-sheets each formed from two greek key motifs. • Short linker peptide with bend bringing domains together. • A six residue hydrophobic domain interface.

24. High Temperature (500K) Simulation of crystallin Wildtype F56A Mutant 0ns 1ns

25. Water Insertion Protocol on crystallin Wildtype F56A Mutant Cycle 1 Cycle 1000

26. Cluster Analysis of Water insertion on C-terminal domain of Scrystallin

27. Cluster Analysis of Water insertion on C-terminal domain of crystallin

28. Results: Ile 56 positioning • Distribution of the distance of Ile 56 from Helix B and Helix 310 (sitting each on the two opposite sides of the residue) from all the conformations sampled. • Only in the mutant conformations we find that Ile 56 exhibits two alternative preferable distances from Helix B and from Helix 310 one near the distance of the crystal structure and one distant.