def benchmark(reference_system, positions, receptor_atoms, ligand_atoms, platform_name=None, annihilateElectrostatics=True, annihilateSterics=False, nsteps=500):
"""
Benchmark performance relative to unmodified system.
ARGUMENTS
reference_system (simtk.openmm.System) - the reference System object to compare with
positions - the positions to assess energetics for
receptor_atoms (list of int) - the list of receptor atoms
ligand_atoms (list of int) - the list of ligand atoms to alchemically modify
"""
# Create a factory to produce alchemical intermediates.
logger.info("Creating alchemical factory...")
initial_time = time.time()
factory = AbsoluteAlchemicalFactory(reference_system, ligand_atoms=ligand_atoms)
final_time = time.time()
elapsed_time = final_time - initial_time
logger.info("AbsoluteAlchemicalFactory initialization took %.3f s" % elapsed_time)
# Create an alchemically-perturbed state corresponding to nearly fully-interacting.
# NOTE: We use a lambda slightly smaller than 1.0 because the AlchemicalFactory does not use Custom*Force softcore versions if lambda = 1.0 identically.
lambda_value = 1.0 - 1.0e-6
alchemical_state = AlchemicalState(0.00, lambda_value, lambda_value, lambda_value)
alchemical_state.annihilateElectrostatics = annihilateElectrostatics
alchemical_state.annihilateSterics = annihilateSterics
platform = None
if platform_name:
platform = openmm.Platform.getPlatformByName(platform_name)
# Create the perturbed system.
logger.info("Creating alchemically-modified state...")
initial_time = time.time()
alchemical_system = factory.createPerturbedSystem(alchemical_state)
final_time = time.time()
elapsed_time = final_time - initial_time
# Compare energies.
timestep = 1.0 * units.femtosecond
logger.info("Computing reference energies...")
reference_integrator = openmm.VerletIntegrator(timestep)
if platform:
reference_context = openmm.Context(reference_system, reference_integrator, platform)
else:
reference_context = openmm.Context(reference_system, reference_integrator)
reference_context.setPositions(positions)
reference_state = reference_context.getState(getEnergy=True)
reference_potential = reference_state.getPotentialEnergy()
logger.info("Computing alchemical energies...")
alchemical_integrator = openmm.VerletIntegrator(timestep)
if platform:
alchemical_context = openmm.Context(alchemical_system, alchemical_integrator, platform)
else:
alchemical_context = openmm.Context(alchemical_system, alchemical_integrator)
alchemical_context.setPositions(positions)
alchemical_state = alchemical_context.getState(getEnergy=True)
alchemical_potential = alchemical_state.getPotentialEnergy()
delta = alchemical_potential - reference_potential
# Make sure all kernels are compiled.
reference_integrator.step(1)
alchemical_integrator.step(1)
# Time simulations.
logger.info("Simulating reference system...")
initial_time = time.time()
reference_integrator.step(nsteps)
reference_state = reference_context.getState(getEnergy=True)
reference_potential = reference_state.getPotentialEnergy()
final_time = time.time()
reference_time = final_time - initial_time
logger.info("Simulating alchemical system...")
initial_time = time.time()
alchemical_integrator.step(nsteps)
alchemical_state = alchemical_context.getState(getEnergy=True)
alchemical_potential = alchemical_state.getPotentialEnergy()
final_time = time.time()
alchemical_time = final_time - initial_time
logger.info("TIMINGS")
logger.info("reference system : %12.3f s for %8d steps (%12.3f ms/step)" % (reference_time, nsteps, reference_time/nsteps*1000))
logger.info("alchemical system : %12.3f s for %8d steps (%12.3f ms/step)" % (alchemical_time, nsteps, alchemical_time/nsteps*1000))
logger.info("alchemical simulation is %12.3f x slower than unperturbed system" % (alchemical_time / reference_time))
return delta
def overlap_check(reference_system, positions, receptor_atoms, ligand_atoms, platform_name=None, annihilate_electrostatics=True, annihilate_sterics=False, precision=None, nsteps=50, nsamples=200):
"""
Test overlap between reference system and alchemical system by running a short simulation.
Parameters
----------
reference_system : simtk.openmm.System
The reference System object to compare with
positions : simtk.unit.Quantity with units compatible with nanometers
The positions to assess energetics for.
receptor_atoms : list of int
The list of receptor atoms.
ligand_atoms : list of int
The list of ligand atoms to alchemically modify.
platform_name : str, optional, default=None
The name of the platform to use for benchmarking.
annihilate_electrostatics : bool, optional, default=True
If True, electrostatics will be annihilated; if False, decoupled.
annihilate_sterics : bool, optional, default=False
If True, sterics will be annihilated; if False, decoupled.
nsteps : int, optional, default=50
Number of molecular dynamics steps between samples.
nsamples : int, optional, default=100
Number of samples to collect.
"""
# Create a fully-interacting alchemical state.
factory = AbsoluteAlchemicalFactory(reference_system, ligand_atoms=ligand_atoms)
alchemical_state = AlchemicalState()
alchemical_system = factory.createPerturbedSystem(alchemical_state)
temperature = 300.0 * units.kelvin
collision_rate = 5.0 / units.picoseconds
timestep = 2.0 * units.femtoseconds
kT = (kB * temperature)
# Select platform.
platform = None
if platform_name:
platform = openmm.Platform.getPlatformByName(platform_name)
# Create integrators.
reference_integrator = openmm.LangevinIntegrator(temperature, collision_rate, timestep)
alchemical_integrator = openmm.VerletIntegrator(timestep)
# Create contexts.
if platform:
reference_context = openmm.Context(reference_system, reference_integrator, platform)
alchemical_context = openmm.Context(alchemical_system, alchemical_integrator, platform)
else:
reference_context = openmm.Context(reference_system, reference_integrator)
alchemical_context = openmm.Context(alchemical_system, alchemical_integrator)
# Collect simulation data.
reference_context.setPositions(positions)
du_n = np.zeros([nsamples], np.float64) # du_n[n] is the
for sample in range(nsamples):
# Run dynamics.
reference_integrator.step(nsteps)
# Get reference energies.
reference_state = reference_context.getState(getEnergy=True, getPositions=True)
reference_potential = reference_state.getPotentialEnergy()
# Get alchemical energies.
alchemical_context.setPositions(reference_state.getPositions())
alchemical_state = alchemical_context.getState(getEnergy=True)
alchemical_potential = alchemical_state.getPotentialEnergy()
du_n[sample] = (alchemical_potential - reference_potential) / kT
# Clean up.
del reference_context, alchemical_context
# Discard data to equilibration and subsample.
from pymbar import timeseries
[t0, g, Neff] = timeseries.detectEquilibration(du_n)
indices = timeseries.subsampleCorrelatedData(du_n, g=g)
du_n = du_n[indices]
# Compute statistics.
from pymbar import EXP
[DeltaF, dDeltaF] = EXP(du_n)
# Raise an exception if the error is larger than 3kT.
MAX_DEVIATION = 3.0 # kT
if (dDeltaF > MAX_DEVIATION):
report = "DeltaF = %12.3f +- %12.3f kT (%5d samples, g = %6.1f)" % (DeltaF, dDeltaF, Neff, g)
raise Exception(report)
return
def overlap_check(reference_system,
positions,
receptor_atoms,
ligand_atoms,
platform_name=None,
annihilate_electrostatics=True,
annihilate_sterics=False,
precision=None,
nsteps=50,
nsamples=200):
"""
Test overlap between reference system and alchemical system by running a short simulation.
Parameters
----------
reference_system : simtk.openmm.System
The reference System object to compare with
positions : simtk.unit.Quantity with units compatible with nanometers
The positions to assess energetics for.
receptor_atoms : list of int
The list of receptor atoms.
ligand_atoms : list of int
The list of ligand atoms to alchemically modify.
platform_name : str, optional, default=None
The name of the platform to use for benchmarking.
annihilate_electrostatics : bool, optional, default=True
If True, electrostatics will be annihilated; if False, decoupled.
annihilate_sterics : bool, optional, default=False
If True, sterics will be annihilated; if False, decoupled.
nsteps : int, optional, default=50
Number of molecular dynamics steps between samples.
nsamples : int, optional, default=100
Number of samples to collect.
"""
# Create a fully-interacting alchemical state.
factory = AbsoluteAlchemicalFactory(reference_system,
ligand_atoms=ligand_atoms)
alchemical_state = AlchemicalState(0.00, 1.00, 1.00, 1.0)
alchemical_system = factory.createPerturbedSystem(alchemical_state)
temperature = 300.0 * units.kelvin
collision_rate = 5.0 / units.picoseconds
timestep = 2.0 * units.femtoseconds
kT = (kB * temperature)
# Select platform.
platform = None
if platform_name:
platform = openmm.Platform.getPlatformByName(platform_name)
# Create integrators.
reference_integrator = openmm.LangevinIntegrator(temperature,
collision_rate, timestep)
alchemical_integrator = openmm.VerletIntegrator(timestep)
# Create contexts.
if platform:
reference_context = openmm.Context(reference_system,
reference_integrator, platform)
alchemical_context = openmm.Context(alchemical_system,
alchemical_integrator, platform)
else:
reference_context = openmm.Context(reference_system,
reference_integrator)
alchemical_context = openmm.Context(alchemical_system,
alchemical_integrator)
# Collect simulation data.
reference_context.setPositions(positions)
du_n = np.zeros([nsamples], np.float64) # du_n[n] is the
for sample in range(nsamples):
# Run dynamics.
reference_integrator.step(nsteps)
# Get reference energies.
reference_state = reference_context.getState(getEnergy=True,
getPositions=True)
reference_potential = reference_state.getPotentialEnergy()
# Get alchemical energies.
alchemical_context.setPositions(reference_state.getPositions())
alchemical_state = alchemical_context.getState(getEnergy=True)
alchemical_potential = alchemical_state.getPotentialEnergy()
du_n[sample] = (alchemical_potential - reference_potential) / kT
# Clean up.
del reference_context, alchemical_context
# Discard data to equilibration and subsample.
from pymbar import timeseries
[t0, g, Neff] = timeseries.detectEquilibration(du_n)
indices = timeseries.subsampleCorrelatedData(du_n, g=g)
du_n = du_n[indices]
# Compute statistics.
from pymbar import EXP
[DeltaF, dDeltaF] = EXP(du_n)
# Raise an exception if the error is larger than 3kT.
MAX_DEVIATION = 3.0 # kT
if (dDeltaF > MAX_DEVIATION):
report = "DeltaF = %12.3f +- %12.3f kT (%5d samples, g = %6.1f)" % (
DeltaF, dDeltaF, Neff, g)
raise Exception(report)
return
def benchmark(reference_system, positions, receptor_atoms, ligand_atoms, platform_name=None, annihilate_electrostatics=True, annihilate_sterics=False, nsteps=500, timestep=1.0*units.femtoseconds):
"""
Benchmark performance of alchemically modified system relative to original system.
Parameters
----------
reference_system : simtk.openmm.System
The reference System object to compare with
positions : simtk.unit.Quantity with units compatible with nanometers
The positions to assess energetics for.
receptor_atoms : list of int
The list of receptor atoms.
ligand_atoms : list of int
The list of ligand atoms to alchemically modify.
platform_name : str, optional, default=None
The name of the platform to use for benchmarking.
annihilate_electrostatics : bool, optional, default=True
If True, electrostatics will be annihilated; if False, decoupled.
annihilate_sterics : bool, optional, default=False
If True, sterics will be annihilated; if False, decoupled.
nsteps : int, optional, default=500
Number of molecular dynamics steps to use for benchmarking.
timestep : simtk.unit.Quantity with units compatible with femtoseconds, optional, default=1*femtoseconds
Timestep to use for benchmarking.
"""
# Create a factory to produce alchemical intermediates.
logger.info("Creating alchemical factory...")
initial_time = time.time()
factory = AbsoluteAlchemicalFactory(reference_system, ligand_atoms=ligand_atoms, annihilate_electrostatics=annihilate_electrostatics, annihilate_sterics=annihilate_sterics)
final_time = time.time()
elapsed_time = final_time - initial_time
logger.info("AbsoluteAlchemicalFactory initialization took %.3f s" % elapsed_time)
# Create an alchemically-perturbed state corresponding to nearly fully-interacting.
# NOTE: We use a lambda slightly smaller than 1.0 because the AlchemicalFactory does not use Custom*Force softcore versions if lambda = 1.0 identically.
lambda_value = 1.0 - 1.0e-6
alchemical_state = AlchemicalState(lambda_coulomb=lambda_value, lambda_sterics=lambda_value, lambda_torsions=lambda_value)
platform = None
if platform_name:
platform = openmm.Platform.getPlatformByName(platform_name)
# Create the perturbed system.
logger.info("Creating alchemically-modified state...")
initial_time = time.time()
alchemical_system = factory.createPerturbedSystem(alchemical_state)
final_time = time.time()
elapsed_time = final_time - initial_time
# Compare energies.
logger.info("Computing reference energies...")
reference_integrator = openmm.VerletIntegrator(timestep)
if platform:
reference_context = openmm.Context(reference_system, reference_integrator, platform)
else:
reference_context = openmm.Context(reference_system, reference_integrator)
reference_context.setPositions(positions)
reference_state = reference_context.getState(getEnergy=True)
reference_potential = reference_state.getPotentialEnergy()
logger.info("Computing alchemical energies...")
alchemical_integrator = openmm.VerletIntegrator(timestep)
if platform:
alchemical_context = openmm.Context(alchemical_system, alchemical_integrator, platform)
else:
alchemical_context = openmm.Context(alchemical_system, alchemical_integrator)
alchemical_context.setPositions(positions)
alchemical_state = alchemical_context.getState(getEnergy=True)
alchemical_potential = alchemical_state.getPotentialEnergy()
delta = alchemical_potential - reference_potential
# Make sure all kernels are compiled.
reference_integrator.step(1)
alchemical_integrator.step(1)
# Time simulations.
logger.info("Simulating reference system...")
initial_time = time.time()
reference_integrator.step(nsteps)
reference_state = reference_context.getState(getEnergy=True)
reference_potential = reference_state.getPotentialEnergy()
final_time = time.time()
reference_time = final_time - initial_time
logger.info("Simulating alchemical system...")
initial_time = time.time()
alchemical_integrator.step(nsteps)
alchemical_state = alchemical_context.getState(getEnergy=True)
alchemical_potential = alchemical_state.getPotentialEnergy()
final_time = time.time()
alchemical_time = final_time - initial_time
logger.info("TIMINGS")
logger.info("reference system : %12.3f s for %8d steps (%12.3f ms/step)" % (reference_time, nsteps, reference_time/nsteps*1000))
logger.info("alchemical system : %12.3f s for %8d steps (%12.3f ms/step)" % (alchemical_time, nsteps, alchemical_time/nsteps*1000))
logger.info("alchemical simulation is %12.3f x slower than unperturbed system" % (alchemical_time / reference_time))
return delta
def benchmark(reference_system,
positions,
receptor_atoms,
ligand_atoms,
platform_name=None,
annihilate_electrostatics=True,
annihilate_sterics=False,
nsteps=500,
timestep=1.0 * units.femtoseconds):
"""
Benchmark performance of alchemically modified system relative to original system.
Parameters
----------
reference_system : simtk.openmm.System
The reference System object to compare with
positions : simtk.unit.Quantity with units compatible with nanometers
The positions to assess energetics for.
receptor_atoms : list of int
The list of receptor atoms.
ligand_atoms : list of int
The list of ligand atoms to alchemically modify.
platform_name : str, optional, default=None
The name of the platform to use for benchmarking.
annihilate_electrostatics : bool, optional, default=True
If True, electrostatics will be annihilated; if False, decoupled.
annihilate_sterics : bool, optional, default=False
If True, sterics will be annihilated; if False, decoupled.
nsteps : int, optional, default=500
Number of molecular dynamics steps to use for benchmarking.
timestep : simtk.unit.Quantity with units compatible with femtoseconds, optional, default=1*femtoseconds
Timestep to use for benchmarking.
"""
# Create a factory to produce alchemical intermediates.
logger.info("Creating alchemical factory...")
initial_time = time.time()
factory = AbsoluteAlchemicalFactory(
reference_system,
ligand_atoms=ligand_atoms,
annihilate_electrostatics=annihilate_electrostatics,
annihilate_sterics=annihilate_sterics)
final_time = time.time()
elapsed_time = final_time - initial_time
logger.info("AbsoluteAlchemicalFactory initialization took %.3f s" %
elapsed_time)
# Create an alchemically-perturbed state corresponding to nearly fully-interacting.
# NOTE: We use a lambda slightly smaller than 1.0 because the AlchemicalFactory does not use Custom*Force softcore versions if lambda = 1.0 identically.
lambda_value = 1.0 - 1.0e-6
alchemical_state = AlchemicalState(0.00, lambda_value, lambda_value,
lambda_value)
platform = None
if platform_name:
platform = openmm.Platform.getPlatformByName(platform_name)
# Create the perturbed system.
logger.info("Creating alchemically-modified state...")
initial_time = time.time()
alchemical_system = factory.createPerturbedSystem(alchemical_state)
final_time = time.time()
elapsed_time = final_time - initial_time
# Compare energies.
logger.info("Computing reference energies...")
reference_integrator = openmm.VerletIntegrator(timestep)
if platform:
reference_context = openmm.Context(reference_system,
reference_integrator, platform)
else:
reference_context = openmm.Context(reference_system,
reference_integrator)
reference_context.setPositions(positions)
reference_state = reference_context.getState(getEnergy=True)
reference_potential = reference_state.getPotentialEnergy()
logger.info("Computing alchemical energies...")
alchemical_integrator = openmm.VerletIntegrator(timestep)
if platform:
alchemical_context = openmm.Context(alchemical_system,
alchemical_integrator, platform)
else:
alchemical_context = openmm.Context(alchemical_system,
alchemical_integrator)
alchemical_context.setPositions(positions)
alchemical_state = alchemical_context.getState(getEnergy=True)
alchemical_potential = alchemical_state.getPotentialEnergy()
delta = alchemical_potential - reference_potential
# Make sure all kernels are compiled.
reference_integrator.step(1)
alchemical_integrator.step(1)
# Time simulations.
logger.info("Simulating reference system...")
initial_time = time.time()
reference_integrator.step(nsteps)
reference_state = reference_context.getState(getEnergy=True)
reference_potential = reference_state.getPotentialEnergy()
final_time = time.time()
reference_time = final_time - initial_time
logger.info("Simulating alchemical system...")
initial_time = time.time()
alchemical_integrator.step(nsteps)
alchemical_state = alchemical_context.getState(getEnergy=True)
alchemical_potential = alchemical_state.getPotentialEnergy()
final_time = time.time()
alchemical_time = final_time - initial_time
logger.info("TIMINGS")
logger.info(
"reference system : %12.3f s for %8d steps (%12.3f ms/step)" %
(reference_time, nsteps, reference_time / nsteps * 1000))
logger.info(
"alchemical system : %12.3f s for %8d steps (%12.3f ms/step)" %
(alchemical_time, nsteps, alchemical_time / nsteps * 1000))
logger.info(
"alchemical simulation is %12.3f x slower than unperturbed system" %
(alchemical_time / reference_time))
return delta
