Tools and methods for multiscale biomolecular simulations

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Tools and methods for multiscale biomolecular
simulations
Celeste Sagui Department of Physics, NC State
University, Raleigh NC
We represent a partnership of 7 researchers
located at the 3 Universities and the National
Institute of Environmental and Health Sciences
(NIEHS), all located within North Carolinas
Research Triangle
NC State Members Jerry Bernholc, Lubos Mitas,
Christopher Roland and Celeste Sagui (PI)
Physics UNC Member Lee Pedersen Chemistry and
NIEHS Duke Member John Board Computer
Science NIEHS Collaborator Tom Darden
Structural Biology Lab
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ITR Scientific Aims

• explore science as to enable a set of scalable
  computational tools for large-scale, multiscale
  biomolecular simulations
• multiscale methods are to range from Quantum
  Monte Carlo (QMC) to continuum methods
• codes will be based on real-space grids, with
  multigrid acceleration and convergence
• electrostatics will be treated in a highly
  efficient and accurate manner
• codes will be used to solve paradigmatic
  biomolecular problems
• codes will ultimately be distributed under the
  Open Source GPL license

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Some Highlights of Current Progress

• Accurate and efficient electrostatics for
  large-scale biomolecular simulations (Sagui,
  Darden, Roland)
• Coupling of QMC and MD (Mitas)
• Thomas Fermi and DFT (Bernholc)
• PMEMD and AMBER 8.0 (Pedersen, Duke)
• Applications

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Classical Molecular Dynamics Developments
Accurate Electrostatics
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Accurate and Efficient Electrostatics for
Large-Scale Biomolecular Simulations

• Accurate electrostatics is absolutely essential
  for meaningful biomolecular simulations (i.e.,
  they stabilize the delicate 3-d structures, bind
  complexes together, represent the computational
  bottleneck in current simulations, etc)
• Key Challenges
• More accurate description of electrostatics
  with higher-order multipoles is needed (Our
  solution Wannier functions)
• Computationally efficient ways of simulating
  such systems are needed (Our solution advanced
  PME/ Multigrid approaches)

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Limitations of Current Modeling of Electrostatic
Fields

• Higher-order multipoles have not been implemented
  due to their overwhelming costs
• Multipoles up to hexadecapoles have 35 degrees of
  freedom, so that interaction matrix between them
  has 1225 components ? i.e., cost of fixed
  cutoff implementation is 3 orders of magnitude
  more than just charges alone !!
• Ewald implementation grows like O(N2)
• Use of cutoffs alleviate the problem WRONG !!
• much of the cost originates in the direct part
• truncation leads to artifactual behavior unless
  cutoffs of the order of 25 Å are used

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Our Solution

• Implement a McMurchie-Davidson formalism for the
  direct part of the Ewald summation
• Switch most of the calculation to reciprocal
  space
• Implement a Particle-Mesh Ewald (PME)-based
  approach for single-processor machines
• Implement a multigrid-based approach for
  parallel machines

Sagui, Pedersen, and Darden, J. Chem. Phys. 120,
73 (2004)
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PME-based results for 4096 water molecules
Relative RMS force error 5x10-4 for error
5x10-5, hexadecapole cost is 4.4 secs 5x10-6
cost is 5 secs With Rc8 Å cutoff, costs is 6
times more than with PME and has a RMS error of
about 0.05
Single processor Intel Xeon, 3.06 GHz, 512kB
cache, 2GB memory, g77 compiler
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Multigrid-based results for 4096 water molecules
Relative RMS force error 5x10-4
Single processor Intel Xeon, 3.06 GHz, 512kB
cache, 2GB memory, g77 compiler
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MD simulation of DNA decamer d(CCAACGTTGG)2 in a
crystal environment
J. Baucom et al, submitted to J. Chem. Phys. 2004
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RMS deviation of crystal simulations at constant
pressure with respect to crystal structure
charges and induced dipoles
charges only
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Calculating Multipole Moments via Wannier
Functions (WFs)

• to partition the charge density and calculate
  the multipole moments, we use a WANNIER FUNCTION
  (WF) approach
• this has several advantages
• WFs provide for a chemical and physically
  intuitive way of partitioning the charge (ref.
  Marzari and Vanderbilt, PRB 56, 12847 (1997))
• WFs are distributed in space, which allows for a
  more faithful representation of the electrostatic
  potential
• no ad hoc assignment of the charge
• numerically quite stable procedure

Ref C. Sagui, P. Pomorski, T. Darden and C.
Roland, J. Chem. Phys. 120, 4530 (2004)
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Maximally localized Wannier functions for water

• water molecule has 4 WFs
• 2 associated with OH bond (light blue)
• 2 associated with O lone pairs (dark blue)

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Electrostatic potential for single water molecule
as generated by WFs
ab initio
m
mdq
mdqo
mdqoh
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Wannier functions for carbon dioxide

• CO2 has 8 WFs
• 6 associated with the CO bonds (light blue)
• 2 associated with O (dark blue)

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Electrostatic potential for carbon dioxide
molecule as generated by WFs
ab initio
m
mdq
mdqo
mdqoh
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Quantum Monte Carlo Developments
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New continuous quantum Monte Carlo/molecular
dynamics method

• we propose a new method for coupling ab initio
  molecular dynamics ionic with stochastic DMC
  electronic steps to provide accurate DMC energies
  on-the-fly
• exploits the slowness of MD evolution which
  enables to update the QMC sampling process very
  efficiently
• accurate for both thermal averages and
  description of energies along the pathways
• we have carried out the first QMC/MD simulations
  using both forces and energies from QMC

Ref J. Grossmann and L. Mitas, preprint 2004
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Coupling of QMC and MD Basic Idea
average distance by an electron in a typical DMC
time step 10-2 10-1 a.u.
average distance made by an ion in one MD time
step 10-4 10-3 a.u.
Instead of discrete sampling of each point with a
new QMC run calculate QMC energies on-the-fly
during the dynamic simulation ! Continuously
update the DMC walkers so that they correctly
represent the evolving wave function (CDMC
method) Evolution of both configuration spaces
is coupled as the ionic dynamical trajectories
evolve, so does the population of DMC electrons
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Stable CDMC simulation
Successful CDMC Algorithm
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CDMC Number of DMC step needed per MD step

• Use large discrete sampled runs (1000 steps each)
  for comparison

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CDMC Si2H6
As for SiH4, asymmetrically stretch molecule and
let go Average temperature 1500 K
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CDMC Si2H6 Results
ForSi2H6, 3 steps appears to lead to stability as
for SiH4 steps looks like a function of
dynamics rather than size Can pinpoint specific
types of strain that lead to wf lag
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Test of quantum Monte Carlo/molecular dynamics
method on water dissociation
QMC only molecular dynamics, with no
external input from DFT
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Density Functional Theory Developments
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Development of hydrid QM calculations
interfacing DFT with Thomas-Fermi calculations

• Idea in many biological systems, only part of
  the system is chemically active
• Use ab initio methods for this part (real-space,
  multigrid-based code)
• Use more approximate methods for the rest of the
  system (in this case Thomas Fermi approach, with
  frozen density for molecules, and gradient
  corrections)

Ref M. Hodak, W. Lu, and Bernholc, in preparation
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Hybrid calculation tests

• Interaction of two water molecules in hybrid
  calculation
• - Hydrogen bonding test
• - Molecule 1 Ab initio
• - Molecule 2 Thomas-Fermi

Gives estimated speed-up of ?500 times !!
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Parallelization and Coding Advances
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Improvements in performance and parallel
scalability of AMBER MD Software

• A redesign of the AMBER SANDER program, along
  with a rewrite in FORTRAN 90 were undertaken with
  the goal of substantially improving the
  practicality of multi-nanosecond PME simulations
  (i.e., in 100,000 to 300,000 atom range)
• Resulting software has been released to the AMBER
  community in 3 phases the new software is named
  PMEMD for PARTICLE MESH EWALD MOLECULAR DYNAMICS

Release Dates July 2003 PMEND 3.00
October 2003 PMEMD
3.10 March 2004
PMEMD 8.0 (part of AMBER 8.0)
PMEMD is now the primary high performance MD
modeling tool in AMBER !!
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Representative Benchmark
Results for the Factor IX constant pressure
system from Dr. Lalith Perera, a solvated system
with a total of 90906 atoms. The time step
was 1.5 fs, the direct force cutoff was 8.0
angstrom, all simulations used PME. The runs were
done on the IBM 1.3 GHz p690 Regatta at the
Edinburgh Parallel Computing Centre. procs
PMEMD 8 PMEMD 3.1 PMEMD 3.0 Sander 8 Sander
7 Sander 6 psec/day psec/day
psec/day psec/day psec/day psec/day 8
nd 346 353 nd 233
182 16 672 607 594
nd 279 258 32 1125
1035 929 nd 306 297
64 1975 1770 1127 369
318 339 96 2743 2304
nd nd nd nd 112 2945
2631 nd nd nd
nd 128 2516 2864 nd 339
nd nd Performance falloff
observed here. Max performance obtained at
higher processor count was 3600 psec/day, but
required using only 4 of the 8 cpu's on each 8
cpu multi-chip module of the SP4.
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Software References
Maximum throughput obtainable for SP4 is up an
order of magnitude for PMEMD 8, than any other
version of SANDER
Software Publication References R.E. Duke and
L.G. Pedersen, PMEMD 3.0 (2003) R.E. Duke and
L.G. Pedersen, PMEMD 3.1 (2003) D.A. Case et al,
AMBER 8.0 (2004)
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Some Applications

• QM/MM studies of enzymatic sulfate transfer in
  the heparan sulfate precursor
• QM/MM studies of enzymatic sulfate transfer in
  estrogen sulfation
• PMEMD study of the mammalian P450 enzyme and the
  ternary blood coagulation complex tissue factors
• Protein folding study on ionic domains of the
  coagulation protein protothrombin
• Solvation and deprotonation of formic acid
• Crystallographic studies of DNA
• Binding of vancomycin and teicoplanin
  antibiotics to bacterial cell wall termini
• Structure and function of serine proteases
• QM/MM study of role of Mg ions in the mechanism
  of DNA polymerase

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Mixed Quantum and Molecular Mechanics Simulations
of Sulfuryl Transfer Reaction Catalyzed by Human
Estrogen Sulfotransferase P. Lin and L. Pedersen
K47
PAPS
E2
H107
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Mixed Quantum and Molecular Mechanics Simulations
of Sulfuryl Transfer Reaction Catalyzed by Human
Estrogen Sulfotransferase P. Lin and L. Pedersen

• estrogen is one of the most important hormones
  found in the human body
• it is extremely important that the body regulate
  estrogen, being able to both turn it on and off
• the deactivation of estrogen takes place by
  means of transfering a sulfate group to the
  hormone
• the details of this important reaction were
  investigated by means of a mixed quantum and
  classical molecular dynamics simulation, as shown
  in the movie

• movie shows how the sulfate group gets placed on
  the estrogen

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Summary

• Scientific aims are to produce a set of scalable
  and portable computational tools for multiscale
  biomolecular calculations
• Considerable progress in number of aspects
• Development of accurate and efficient methods
  for treatment of long-range electrostatic forces
• Development of QMC and MD methods
• Development of DFT and TF interface
• PMEMD and AMBER 8.0
• Applications