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

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.

Wrong Right Wrong DisastrousAMYLOID PROTEIN MISFOLDING LEADS TO DISEASE Human Lysozyme  2 microglobulin Transthyretin eye-lens crystallins p53 - cancer

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

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

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). Results: Clustering

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 10 6 days cpu = 3000 PCs for a year. 1.5 Gb storage per 1 ns simulation = 70 terabytes storage per year.

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 His88 His90 Glu92

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

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

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

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 ?

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.

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

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

Acknowledgements George MoraitakisMark Sansom - Oxford Delphine Flatters Oliver Smart - Birmingham Spiros SkoulakisJonathan Essex - Southampton Isofina Pournara Leo Caves - York Andy Purkiss Charlie Naughton - Nottingham Thomas MatthewsPaul Jeffrey (Oxford) David Boyd & Paul Durham (CLRC)

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

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

pK 1/2 values monomer His His His His Glu Tyr Glu92 0.3

His His Tyr Glu Tyr116 Glu92  pK 1/2 values dimer Tyr116 His88 His90 Glu92

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

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

Stability of  -crystallins using molecular dynamics Andy Purkiss  Crystallin X-ray crystal structure to 1.2Å 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.  -crystallin features

High Temperature (500K) Simulation of  crystallin 0ns 1ns WildtypeF56A Mutant

Water Insertion Protocol on  crystallin Cycle 1 Cycle 1000 WildtypeF56A Mutant

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

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

Distribution of the distance of Ile 56 from Helix B and Helix 3 10 (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 3 10 one near the distance of the crystal structure and one distant. Results: Ile 56 positioning