Introducing Molecular Dynamics with Desmond: Advanced molecular dynamics simulations for the pharmaceutical industry
While many modelers know Dr. Shelley as the product manager for MacroModel,
Dr. Shelley has also been acting as product manager for Desmond, a high
performance molecular dynamics package developed by D. E. Shaw Research
and scheduled for release as part of Schrödinger Suite 2008. Here, Dr.
Shelley discusses the advances conceived and implemented by the D. E.
Shaw Research team, as well as the design and implementation of the
practical, straightforward Desmond interface within Maestro.
Desmond, a new parallel molecular dynamics program created by D. E. Shaw Research,
provides researchers with the tools to simulate biomolecular systems
with unsurpassed speed and accuracy. Schrödinger is releasing Desmond
commercially and has integrated the software into the Maestro
molecular modeling environment. The result is a product that makes
setting up, running, and analyzing molecular dynamics simulations
straightforward, allowing users to focus on the scientific problem of
interest.
Desmond is a state-of-the-art molecular dynamics package, incorporating the following key innovations:
- Exploiting advanced parallel algorithms, Desmond achieves unprecedented scalability on both high-end and typical Linux clusters.
- Desmond
takes advantage of SIMD (single-instruction multiple data) and other
low-level parallelism strategies, providing high performance even at
the single processor level.
- Desmond excels in numerical
accuracy. Simulations can be run in single precision without
compromising numerical rigor. Checkpoint and restore facilities are
bitwise accurate, and bitwise reversible simulations are possible.
Key functionalities include:
- Explicit
solvent simulations with periodic boundary conditions using cubic,
orthorhombic, truncated octahedron, rhombic dodecahedron, and arbitrary
triclinic simulation boxes
- Efficient parallel minimizer application for system setup and equilibration
- Ability to calculate absolute and relative solvation free energies
- Ability to calculate absolute and relative binding free energies
Key technical features include:
- Long range electrostatics rigorously treated via particle mesh based Ewald techniques
- Time-scale splitting and efficient integration using multiple time-step (RESPA) based integrators
- Accurate implementation of constraints to remove highest frequency vibrations and increase the integration time step
- Support for a variety of thermodynamic ensembles including NVE, NVT, NPT with
- Berendsen or Nose-Hoover thermostats
- Berendsen or Martyna-Tobias-Klein barostats
- Support for isotropic, semi-isotropic and anisotropic pressure coupling
- Ability to restrain the position of selected atoms
- Accurate restarts using sophisticated checkpointing facilities
- Plug-in capability to enable visualization and analysis of trajectories using VMD
D. E. Shaw Research has published a number of papers related to Desmond, including an early overview of the Desmond software1.
A number of other papers describe algorithms and implementation
techniques that significantly accelerate parallel MD simulations
compared with current state-of-the-art codes. This includes a set of
papers outlining novel parallel decomposition methods that greatly
reduces the requirement for inter-processor communication2,3,4.
Desmond also excels in numerical accuracy, an example of which is
provided in a short note on the handling of constraints in molecular
dynamics simulations5.
Finally, a number of application studies using Desmond have been
published. These papers include a study of the function of a
transmembrane (sodium/proton antiporter) protein in which simulation
results were subsequently supported by experimental site-directed
mutagenesis studies6,
as well as the use of microsecond-long molecular dynamics simulations
to compare simulation results to those obtained by experimental NMR7.
Desmond
calculations can be set up, run and reviewed from within Maestro,
thereby providing an intuitive and productive environment for
performing molecular dynamics simulations. New panels accessible from
Maestro include the System Builder, the Desmond panel, Free Energy
Perturbation Setup, Trajectory Viewer and Simulation Quality analysis.
The System Builder (Figure 1)
makes it easy to construct systems suitable for simulation using
periodic boundary conditions starting from a solute structure; a
process which involves selectively adding the molecules in the
environment and assigning force field parameters (OPLS_2005). Bulk
solvent (optionally containing salt) and membrane environments are
supported, as are a variety of simulation cell shapes. Charge
neutralization is largely automated; however, control over the
placement of neutralizing ions is supported in a convenient manner. The
panel is designed such that it is often sufficient just to click Start.
The Desmond panel, shown in Figure 2,
is used to actually launch Desmond jobs. This panel supports starting
or continuing both minimizations and simulations. The user can
intuitively examine and adjust many key calculation parameters, and any
coupled parameters are automatically adjusted when changes are made.
The user can also elect to prepend a fully automated relaxation process
to the production simulation with just a single click. As with the
System Builder, the default parameters are selected such that the user
need only enter the desired simulation length and click Start.
Free
energies are key properties of interest in molecular systems. Free
energy calculations are often tedious, difficult and time consuming to
design and setup. The Free Energy Perturbation (FEP) Setup panel (Figure 3)
makes setting up FEP jobs easy so that the user can focus on the real
problem of interest rather than the details of the calculation. This
panel supports the following solvation free energy and binding free
energy calculations:
- ligand side-chain mutation (relative free energy)
- ring atom mutation (relative free energy)
- ligand annihilation (absolute free energy)
Maestro also now supports viewing simulation trajectories via the Trajectory Viewer, depicted in Figure 4.
Using this comprehensive tool the user can intuitively select the frame
being displayed or the speed at which the simulation is viewed.
Maestro's tools permit easy manipulation of the representation and
visibility of the components in the system. Trajectory smoothing,
superposition to an earlier frame, replication of the simulation cell,
and extraction of sets of frames are all supported features. Maestro
can also create images of individual frames, or movies of entire
trajectories, with only a few mouse clicks.
Figure
1. Solvating a globular protein. P38 before solvation (left). The
System Builder panel in default configuration (middle). Simply clicking
Start solvates and adds ions to neutralize the system, yielding the
configuration depicted in the image to the right.
Figure
2. The Desmond panel. Aside from the total simulation time, the default
parameter settings provided in the Desmond panel are appropriate for
most simulations. Minimizations or even multistage relaxations can also
be launched from this panel.
Figure
3. The FEP panel makes it possible to easily set up and launch multiple
FEP calculations. Here multiple molecular fragments have been selected
for addition across a bond (green) in a ligand. The conformation of one
of them is included in the workspace. The user can opt to interactively
adjust the conformation of each selected fragment.
Figure 4. Maestro's trajectory-viewing facility is both feature-rich and convenient.
Figure 5. The Simulation Quality Analysis panel makes it easy to review key quality measures from a simulation.
Desmond
molecular dynamics simulations can be monitored from Maestro's
Workspace. Desmond jobs are launched using Schrödinger's Job Control
facility; providing a standardized mechanism for running both local and
remote jobs, monitoring jobs, interacting with queues, halting jobs,
and incorporating results into Maestro projects automatically. In
addition, a plug-in for viewing Desmond simulations in VMD is provided.
Python
is central to Desmond-related tasks. Nearly all Desmond jobs can be
launched from Python, thus permitting the development of user-specific
workflows. Analysis of Desmond simulations also makes use of Python;
furthermore, straightforward and customizable scripting is possible via
support from NumPy for complex mathematical operations and MatPlotLib
for plotting. There also is an intuitive tool, the Simulation Quality
Analysis panel (Figure 5), for assessing key markers of simulation quality.
Problem-solving
often requires use of a wide range of modelling techniques. A
compelling feature of this new product is the synergies that result
from Desmond's integration into Schrödinger's premier molecular
modelling suite for drug development. For instance, careful chemical
and conformational preparation of molecules often represents a critical
step in setting up a molecular dynamics simulation. The Protein Preparation Wizard, LigPrep (ligand structure) and Epik
(ligand protonation state) can be used to ensure that the structures
provided to Desmond are chemically correct. Starting conformations for
Desmond simulations can originate from a number of sources; including,
homology models produced by Prime or docked ligand poses from Glide.
Desmond's
efficient and accurate simulations make it possible to thermally relax,
refine, and sample conformations of proteins and protein-ligand
complexes on useful time scales. Desmond's simulations may be used to
select systems or conformations for further study. For example, the use
of alternate protein conformations in subsequent docking calculations
with Glide, or as input into SiteMap
to characterize protein active sites. Another new product from
Schrödinger, WaterMap, utilizes a specific type of Desmond simulations
to identify and thermodynamically characterize water molecule positions
within the binding site of a protein.
Desmond's
accuracy, speed, scalability, and ease of use make it possible for
researchers to move beyond the complexities and intricacies of setting
up and running molecular dynamics simulations so that they can
concentrate on the problem of interest. This should greatly expand the
productive use of molecular dynamics simulations in the pharmaceutical
industry.
[1]
Scalable algorithms for molecular dynamics simulations on commodity
clusters, Bowers, K.J., Chow, E., Xu, H., Dror, R.O., Eastwood, M.P.,
Gregerson, B.A., Klepeis, J.L., Kolossvary, I., Moraes, M.A.,
Sacerdoti, F.D., Salmon, J.K., Shan, Y., Shaw, D.E., Proceedings of the ACM/IEEE Conference on Supercomputing (SC06), Tampa, Florida, 2006, which received Best Paper Award for that meeting.
[2] A fast, scalable method for the parallel evaluation of distance-limited pair wise particle interactions, Shaw, D.E., J. Comput. Chem., 2005, 26: 1318.
[3] The midpoint method for parallelization of particle simulations, Bowers, K.J.; Dror, R.O.; Shaw, D.E., J. Chem. Phys., 2006, 124, 184109.
[4] Zonal methods for the parallel execution of range-limited N-body simulations, Bowers, K.J.; Dror, R.O.; Shaw, D.E., J. Comput. Phys., 2007, 221, 303.
[5]
A common, avoidable source of error in molecular dynamics integrators,
Lippert, R.A.; Bowers, K.J.; Dror, R. O.; Eastwood, M.P.; Gregersen,
B.A.; Klepeis, J.L.; Kolossvary, I.; Shaw, D.E., J. Chem. Phys., 2007, 126, 046101.
[6]
Mechanism of Na+/H+ antiporting, Arkin, I.T., Xu, H.; Jensen, M.Ø.;
Arbely, E.; Bennett, E.R.; Bowers, K.J.; Chow, E.; Dror, R.O.;
Eastwood, M.P.; Flitman-Tene, R.; Gregersen, B.A.; Klepeis, J.L.;
Kolossváry, I.; Shan, Y.; Shaw, D.E., Science, 2007, 317, 799.
[7]
Microsecond molecular dynamics simulation shows effect of slow loop
dynamics on backbone amide order parameters of proteins, Maragakis, P.,
Lindorff-Larsen, K.; Eastwood, M.P.; Dror, R.O.; Klepeis, J.L.; Arkin,
I.T.; Jensen, M.O.; Xu, H.; Trbovic, N.; Friesner, R.A.; Palmer III,
A.G.; Shaw, D.E., J. Phys. Chem. B, 2008, [Epub].