def test_opt_orca():
"""
Test Orca input generation and run functions.
"""
h2o = Molecule('test/test_files/h2o.xyz', 'xyz', charge=0, multiplicity=1)
h2o_geometry = dftb(templates.geometry, h2o)
s = Settings()
# generic keyword "basis" must be present in the generic dictionary
s.basis = "sto_dzp"
# "specific" allows the user to apply specific keywords for a
# package that are not in a generic dictionary
# s.specific.adf.basis.core = "large"
r = templates.singlepoint.overlay(s)
h2o_singlepoint = orca(r, h2o_geometry.molecule)
dipole = h2o_singlepoint.dipole
final_result = run(dipole, n_processes=1)
expected_dipole = [0.82409, 0.1933, -0.08316]
diff = sqrt(sum((x - y) ** 2 for x, y in zip(final_result,
expected_dipole)))
print("Expected dipole computed with Orca 3.0.3 is:", expected_dipole)
print("Actual dipole is:", final_result)
assert diff < 1e-2
def test_opt_orca():
"""Test Orca input generation and run functions."""
h2o = Molecule(PATH_MOLECULES / "h2o.xyz", 'xyz', charge=0, multiplicity=1)
h2o_geometry = dftb(templates.geometry, h2o)
s = Settings()
# generic keyword "basis" must be present in the generic dictionary
s.basis = "sto_dzp"
# s.specific.adf.basis.core = "large"
r = templates.singlepoint.overlay(s)
h2o_singlepoint = orca(r, h2o_geometry.molecule)
dipole = h2o_singlepoint.dipole
final_result = run(dipole, n_processes=1)
expected_dipole = [0.82409, 0.1933, -0.08316]
diff = sqrt(sum((x - y)**2 for x, y in zip(final_result, expected_dipole)))
logger.info(
f"Expected dipole computed with Orca 3.0.3 is: {expected_dipole}")
logger.info(f"Actual dipole is: {final_result}")
assertion.lt(diff, 1e-2)
def test_opt_orca():
"""
Test Orca input generation and run functions.
"""
h2o = Molecule('test/test_files/h2o.xyz', 'xyz', charge=0, multiplicity=1)
h2o_geometry = dftb(templates.geometry, h2o)
s = Settings()
# generic keyword "basis" must be present in the generic dictionary
s.basis = "sto_dzp"
# "specific" allows the user to apply specific keywords for a
# package that are not in a generic dictionary
# s.specific.adf.basis.core = "large"
r = templates.singlepoint.overlay(s)
h2o_singlepoint = orca(r, h2o_geometry.molecule)
dipole = h2o_singlepoint.dipole
final_result = run(dipole, n_processes=1)
expected_dipole = [0.82409, 0.1933, -0.08316]
diff = sqrt(sum((x - y)**2 for x, y in zip(final_result, expected_dipole)))
print("Expected dipole computed with Orca 3.0.3 is:", expected_dipole)
print("Actual dipole is:", final_result)
assert diff < 1e-2
def test_hessian_transfer():
"""Test DFTB -> Orca hessian transfer."""
h2o = molkit.from_smiles('O')
h2o.properties.symmetry = 'C1'
h2o_freq = dftb(templates.freq, h2o, job_name="freq").hessian
s = Settings()
s.inithess = h2o_freq
h2o_opt = orca(templates.geometry.overlay(s), h2o, job_name="opt")
energy = h2o_opt.energy
dipole = h2o_opt.dipole
wf = gather(energy, dipole)
logger.info(run(wf))
def test_hessian_transfer():
"""
Test DFTB -> Orca hessian transfer
"""
h2o = molkit.from_smiles('O')
h2o.properties.symmetry = 'C1'
h2o_freq = dftb(templates.freq, h2o, job_name="freq").hessian
s = Settings()
s.inithess = h2o_freq
h2o_opt = orca(templates.geometry.overlay(s), h2o, job_name="opt")
energy = h2o_opt.energy
dipole = h2o_opt.dipole
wf = gather(energy, dipole)
print(run(wf))
def example_ADF3FDE_Dialanine():
# For the purpose of the example, define the pdb file here.
dialanine_pdb = io.StringIO(
'''HEADER OXIDOREDUCTASE 06-JUL-94 1PBE
TITLE CRYSTAL STRUCTURE OF THE P-HYDROXYBENZOATE HYDROXYLASE-SUBSTRATE
TITLE 2 COMPLEX REFINED AT 1.9 ANGSTROMS RESOLUTION. ANALYSIS OF THE ENZYME-
TITLE 3 SUBSTRATE AND ENZYME-PRODUCT COMPLEXES
ATOM 937 N ALA A 124 28.566 107.090 69.900 1.00 19.62 N
ATOM 938 CA ALA A 124 28.940 106.368 71.140 1.00 19.55 C
ATOM 939 C ALA A 124 30.169 105.591 70.700 1.00 21.08 C
ATOM 940 O ALA A 124 29.935 104.701 69.852 1.00 22.09 O
ATOM 941 CB ALA A 124 27.826 105.376 71.472 1.00 28.37 C
ATOM 942 N ALA A 125 31.330 105.921 71.145 1.00 22.72 N
ATOM 943 CA ALA A 125 32.573 105.296 70.663 1.00 22.82 C
ATOM 944 C ALA A 125 33.073 104.318 71.705 1.00 26.31 C
ATOM 945 O ALA A 125 32.743 104.415 72.876 1.00 22.69 O
ATOM 946 CB ALA A 125 33.596 106.405 70.359 1.00 22.03 C
END
''')
supermol = molkit.readpdb(dialanine_pdb)
supermol = molkit.add_Hs(supermol)
# Calculate dipole normally
supermol_job = dftb(templates.singlepoint, supermol,
job_name='supermol_singlepoint')
# Calculate dipole with mfcc approach
frags, caps = molkit.partition_protein(supermol)
mfcc_job = mfcc(dftb, frags, caps)
supermol_dipole, mfcc_dipole = run(gather(supermol_job.dipole, mfcc_job.dipole))
print("Supermolecule dipole: ", supermol_dipole)
print("mfcc dipole: ", mfcc_dipole)
return supermol_dipole, mfcc_dipole
'surface': {
'nsteps': 6,
'start': [2.3, 2.3],
'stepsize': [0.1, 0.1]
}
}
# returns a set of results object containing the output of
# each point in the scan
lt = PES_scan([dftb, adf], settings, cnc, scan)
# Gets the object presenting the molecule
# with the maximum energy calculated from the scan
apprTS = select_max(lt, "energy")
appr_hess = dftb(templates.freq.overlay(settings), apprTS.molecule)
t = Settings()
t.specific.adf.geometry.inithess = appr_hess.archive.path
# Run the TS optimization with ADF, using initial hessian from DFTB freq calculation
ts = run(adf(templates.ts.overlay(settings).overlay(t), appr_hess.molecule),
n_processes=1)
# Retrieve the molecular coordinates
mol = ts.molecule
r1 = mol.atoms[0].coords
r2 = mol.atoms[4].coords
print("TS Bond distance:", bond_distance(r1, r2))
print("TS Energy:", ts.energy)
settings.functional = "b3lyp"
settings.specific.orca.basis.basis = "_6_31G"
settings.specific.orca.basis.pol = "_d"
settings.specific.orca.basis.diff = "_p"
settings.specific.dftb.dftb.scc.ndiis = 4
settings.specific.dftb.dftb.scc.Mixing = 0.1
settings.specific.dftb.dftb.scc.iterations = 300
job_list = []
# Loop over all reactions
for name, r1_smiles, r2_smiles, p_smiles in reactions:
# Prepare reactant1 job
r1_mol = molkit.from_smiles(r1_smiles)
r1_dftb = dftb(templates.geometry.overlay(settings), r1_mol, job_name=name + "_r1_DFTB")
r1 = adf(templates.geometry.overlay(settings), r1_dftb.molecule, job_name=name + "_r1")
r1_freq = adf(templates.freq.overlay(settings), r1.molecule, job_name=name + "_r1_freq")
# Prepare reactant2 job
r2s_mol = molkit.from_smiles(r2_smiles, nconfs=10, forcefield='mmff', rms=0.1)
r2s_dftb = [dftb(templates.geometry.overlay(settings), r2_mol, job_name=name + "_r2_DFTB") for r2_mol in r2s_mol]
r2_dftb = select_min(gather(*r2s_dftb), 'energy')
r2 = adf(templates.geometry.overlay(settings), r2_dftb.molecule, job_name=name + "_r2")
r2_freq = adf(templates.freq.overlay(settings), r2.molecule, job_name=name + "_r2_freq")
# Prepare product job
ps_mol = molkit.from_smiles(p_smiles, nconfs=10, forcefield='mmff', name=name, rms=0.1)
ps_dftb = [dftb(templates.geometry.overlay(settings), p_mol, job_name=name + "_ps_DFTB") for p_mol in ps_mol]
p_dftb = select_min(gather(*ps_dftb), 'energy')
p = adf(templates.geometry.overlay(settings), p_dftb.molecule, job_name=name + "_p")
# User define Settings
settings = Settings()
settings.functional = "pbe"
settings.basis = "TZ2P"
settings.specific.dftb.dftb.scc
job_list = []
# Loop over all reactions
for name, reactant1, reactant2, product in reactions[:1]:
# Prepare reactant1 job
r1mol = molkit.from_smiles(reactant1)
r1job = adf(
templates.geometry.overlay(settings),
dftb(templates.geometry.overlay(settings), r1mol,
job_name=name + "_r1_DFTB").molecule,
job_name=name + "_r1")
# Prepare reactant2 job
r2mol = molkit.from_smiles(reactant2)
r2job = adf(
templates.geometry.overlay(settings),
dftb(templates.geometry.overlay(settings), r2mol,
job_name=name + "_r2_DFTB").molecule,
job_name=name + "_r2")
# Prepare product job
pmol = molkit.from_smiles(product)
pmol.properties.name = name
pjob = adf(
templates.geometry.overlay(settings),
O 0.93874565776916 0.76907359603763 -0.48055185294869
C -0.93375384866586 -0.24065248892727 -1.32868508338709
H -2.06330249766107 -1.10524960979939 0.46177231972758
H -0.61425226052981 0.06238167064304 -2.30462642727095
''')
guessTS = plams.Molecule()
guessTS.readxyz(xyz_file, 1)
# Some dftb specific settings
dftb_set = Settings()
dftb_set.specific.dftb.dftb.scc
# Calculate the DFTB hessian
freq_dftb = dftb(templates.freq.overlay(dftb_set),
guessTS,
job_name="freq_dftb")
# User define Settings
settings = Settings()
settings.functional = "b3lyp"
settings.specific.orca.basis.basis = "_3_21G"
settings.specific.orca.basis.pol = "_d"
settings.specific.orca.basis.diff = "_p"
# Run the TS optimization, using the initial hessian from DFTB
settings.inithess = freq_dftb.hessian
# Define job
ts = orca(templates.ts.overlay(settings), guessTS, job_name="ts")
