Massively Distributed Computing and An NRPGM Project on Protein Structure and Function

1. Massively Distributed ComputingandAn NRPGM ProjectonProtein Structure and Function Computation Biology LabPhysics Dept & Life Science DeptNational Central University

2. From Gene to Protein

3. About Protein • Function • Storage, Transport, Messengers, Regulation… Everything that sustains life • Structure: shell, silk, spider-silk, etc. • Structure • String of amino acid with 3D structure • Homology and Topology • Importance • Science, Health & Medicine • Industry – enzyme, detergent, etc. • An example – 3hvt.pdb

4. Problem Structure & Function • Primary sequence  Native state with 3D structure • Structure function • Expensive and time consuming • Misfolding means malfunction • Mad cow disease (“prion” misfolds)

5. The Folding Problem • Complexity of mechanism & pathway is huge challenge to science and computation technology

6. Molecular Dynamics (MD) • Molecular’s behavior determined by • Ensemble statistics • Newtonian mechanics • Experiment in silico • All-atom w. water • Huge number of particles • Super-heavyduty computation • Software for macromolecular MD available • CHARMm, AMBER, GROMACS

7. Basic Statistics for Protein MD Simulation • Atoms in a small protein plus surrounding water (N) 32000 • Approximate number of interactions in force calculation (N2/2 ) 0.5x109 • Machine instructions per force calculation 1000 • Machine time per calculation (CPU: 3G) 160 sec • Typical time-step size 0.5x10–15 sec • Total number of steps for 1 ms folding 0.5x109 steps • Total machine time (160 sec x 0.5x109) 106 days

8. How to overcome the factor of 1 million • A two-pronged approach • Faster or more CPUs • Nature of bottle-neck in protein folding dictated by Boltzmann distribution, can be overcome by large statistics (parallel computing NOT needed) • Our solution: Massively distributed computing • We seek factor of ~ 10,000 • Note. IBM’s solution: Blue Machine w/ 106 CPUs • Shorten computation time • Many simulation steps needed b/c short time-scale of fast (vibrational) mode of ~ 10fs • But time-scale of folding motion slow, ~ 1 ns • Ideal solution: by-pass or smooth out fast modes

9. Protein Studies byMassively Distributed Computing A Project in National Research Program on Genomic Medicine • Scientific • Protein folding, structure, function, protein-molecule interaction • Algorithm, force-field • Computing • Massive distributive computing • Education • Everyone and Anyone with a personal PC can take part • Industry – collaborative development

10. Distributive Computing • Concept • Computation through internet • Utilize idle PC power (through screen-saver) • Advantage • Cheap way to acquire huge computation power • Perfectly suited to task • Huge number of runs needed to beat statistics • Parallel computation NOT needed • Massive data - good management necessary • Public education – anyone w/ PC can take part

11. Hardware Strategies • Parallel computation (we are not this) • PC cluster • IBM (The blue gene), 106 CPU • Massive distributive computing • Grid computing (formal and in the future) • Server to individual client (now in inexpensive) • Examples: SETI, folding@home, genome@home • Our project: protein@CBL

12. Software Components • Dynamics of macromolecules • Molecular dynamics, all atomistic or mean-field solvent • Computer codes • GROMACS (for distributive comp; freeware) • AMBER and others(for in-house comp; licensed) • Distributed Computing • COSM - a stable, reliable, and secure system for large scale distributed processing (freeware)

13. Structure of COSM (network dist’n) Client System tests (test all Cosm functions) Self-tests Connect to server Send Request Recv Assignment Running Simulation Put Result Get Accept Packet Request Packet Assignment Packet Result Packet Accept

14. Protein database • Temporary • databank • Job analysis • Automatic • temperature • swaps by • parallel tem- • pering Databank Human intervention Jobs Exceptions Send(COSM) clients Receive Structure at Server end

15. Server Receive If crash MD Run Restart Return result Delete files Structure at Client end

16. Multi-temperature Annealing • Project suited for multi-temperature runs – Parallel Tempering • Two configurations with energy and temperature (E1, T1) and (E2, T2) Temperature swapped with probability P = min{1, exp[-(E2-E1)(1/kT1 – 1/kT2)]} • Mode of operation • Send same peptide at different temperature to many clients; let run; collect; swap T’s by multiple parallel tempering; randomly redistribute peptides with new T’s to clients

17. Server client Old temperatures client Swap temps by Multiple “peptide” parallel tempering client Databank client client client New temperatures client Multi-temperature Annealing (II)

18. Potential of Massive Distributive Computing • Simulation of folding a small peptide for 100ns • Each run (105 simulation steps; 100 ps) ~100 min PC time • 1000 runs (100 ns) per “fold” ~105 min • Approx. 70 days on single PC running 24h/day • Ideal client contribute 8h/day • 100 clients 70x3/100 = 2 days per fold • 10,000 clients 50 folds/day(small peptide) • Mid-sized protein needs > 1 ms to fold • 106 days on single PC • 10,000 clients ~300 days • 106 clients (!!) ~3 days

19. Schedule • Launched –August 2002 • Small PC-cluster – October 2002 • In-house runs to learn codes • Infrastructure for Distributive Computation • InstallationGromacs & COSM – January-March 2003 • Test runs • IntraLaboratory test run – March-October 2003 • NCU test run – July-October 2003 • Launched on WWW – November 20 2003 • Scientific studies • Getting familiar w/ MD and folding of peptides • Looking for ways to increase MD time step

20. Current status of PAC • Last beta version Pac v0.9 • Released on July 15 • To lab CBL members & physics dept • About 25 clients • First alpha version Pac v1.0 released October 1 2003 • Current version Pac v1.2 • Releases to public on 20 November 2003 • In search of clients • Portal in “Educities”http://www.educities.edu.tw/~3,700 downloads, ~700 active clients • PC’s in university administrative units • City halls and county government offices • Talks and visits to universities and high schools

21. 1L2Y: (20 res.) NMR Structure Of Trp-Cage Miniprotein Construct Tc5B; synthetic. 1SOL: (20 res.) A Pip2 and F-Actin-Binding Site Of Gelsolin, Residue 150-169. One helix. 1ZDD: (35 res.) Disulfide-Stab-ilized Mini Protein A Domain. Two helices. Some current Simulations

22. A small test case – 1SOL • Target peptide – 1SOL.pdb • 20 amino acids; 3-loop helix and 1 hairpin; 352 atoms; ~4000 bonds interaction • Unit time step= 1 fs • Compare constant temperature and parallel-tempering • Constant T @ 300K • Parallel-tempering with about 20 peptides, results returned to server for swapping after each “run”, or 105 time steps (100 ps)

23. Parallel-tempering (1SOL) Temperature (K) Number of runs (in units of 100 ps) P = min{1, exp[-(E2-E1)(1/kT1 – 1/kT2)]}

24. Initial structure Native conformation Const temp. (20ns) Parallel-temp. (1.6ns) Preliminary result on 1SOL

25. A second test case – 1L2Y • Simulation target – Trp-Cage • 20 amino acids, 2 helical loops • A short, artificial and fold-by-itself peptide • Have been simulated with AMBER • Folding mechanism not well understood

26. Temperature (K) Number of runs (in units of 100 ps) A case in swap History (1L2Y)

27. Preliminary result on 1L2Y (11 peptides) Native state Initial state PAC 6ns

28. Speeding up simulation - Separating the fast from slow modes • Fast modes associated with bonded interactions • Bond-stretching vibrations ~ 10-20 fs • Bond-angle bending vibrations ~ 20-40 fs • Slow modes associated with dihedral angles • Of the order of 0.1 ns • Alpha-helix folds in ~ 1 -10 ns • Beta-sheets folds in ~ 10 -100 ns • Native structure ~ 1 ms -1 s

29. bij i j θ0 i k j Bonded interactions • Bond stretching • Harmonic angle potential

30. Bond-stretching vibrations Bond-stretching vibrations with an approximate oscillation or relaxation time ζ≈10 fs for bond involving a hydrogen atom (C-H)

31. Bond-stretching vibrations (II) Std < 0.03 A; very small compared with tolerance in structure. Most codes including GROMACS and AMBER have option to freeze out degree of freedom.

32. Bond-angle bending vibrations Bond-angle bending vibrations with ζ ≈20 fs for bond angles involving hydrogen atom (H-N-C).

33. Bond-angle bending vibrations (II) Unique value with relatively small std (~ 3-5 degrees). But cannot be frozen; looking for ways to “half-freeze.”

34. Std at ~15 degrees >> 3-5 degrees

35. Also has multiple eigen-angles

36. Current and future efforts • Computing facility • expand the base of PAC clients; target 10,000 • Data management • efficient server-client protocol • efficient management and analysis of data when client number is large • Running simulations • optimum implementation of parallel tempering • reduce size of water box • Dealing with fast modes • freeze bond stretching • isolate bond-angle bending deg. of freedom for special treatment; new (heavy) code-writing • target time-step: > 20 fs; ultimately 100 fs

37. The Team • Funded by NRPGM/NSC • Computational Biology Laboratory Physics Dept & Life Sciences Dept National Central University • PI: Professor HC Lee (Phys & LS/NCU) • Jia-Lin Lo (PhD student) • Jun-Ping Yiu (MSc Res. Assistant) • Chien-Hao Wei (MSc RA) • Engin Lee ( MSc student ) • Dr. Richard Tseng (PDF, since May 2004) • Visiting scientist: physicist/computer specialist (TBA)

38. Website http://protein.ncu.edu.tw client_stats

39. Please visit http://protein.ncu.edu.tw and let your PC take part in this project while you sleep Thank you