def ts_scan(prod, name, chrg, mult, xcontrol_name):
""" scan for transition state """
charged = True # hard coded for mogens
# create conformers
ts_qmmol = QMMol()
ts_qmmol.add_conformer(prod.write_xyz(to_file=False),
fmt='xyz',
label=name,
charged_fragments=charged,
set_initial=True)
xtb_params = {
'method': 'gfn2',
'opt': 'opt',
'cpus': 1,
'input': '../' + str(xcontrol_name)
}
ts_qmmol.calc = xTB(parameters=xtb_params)
ts_conf = ts_qmmol.conformers[0]
#ts_conf.conf_calculate(quantities=['energy', 'structure'], keep_files=True)
#ts_conf.conf_calculate(quantities=['energy'], keep_files=True)
ts_conf.conf_calculate(quantities=['energy', 'ts_guess'], keep_files=True)
def ts_search(gs_dict):
""" Perform ts scan of the bond getting broken"""
reactant = gs_dict['reac']
charged = True # hard coded for mogens
# find atoms to move during scan.
smarts_bond = Chem.MolFromSmarts('[CX4;H0;R]-[CX4;H1;R]')
reactant_rdkit_mol = reactant.get_rdkit_mol()
atom_idx = reactant_rdkit_mol.GetSubstructMatch(smarts_bond)
orca_tsscan = {'method': 'pm3',
'basis': '',
'opt': 'opt',
'geom scan': 'B {} {} = 1.5, 3.5, 12'.format(*atom_idx),
'mem': '8GB',
'cpus': 1}
# run ts guess run
ts_qmmol = QMMol()
name = reactant.label.split('_')[0] + '_ts'
ts_qmmol.add_conformer(reactant.write_xyz(to_file=False), fmt='xyz',
label=name, charged_fragments=charged,
set_initial=True)
ts_qmmol.calc = ORCA(parameters=orca_tsscan)
ts_conf = ts_qmmol.conformers[0]
ts_conf.conf_calculate(quantities=['ts_guess', 'ts_guess_energy'])
# update ts_qmmol, hack since i can't set calc on conf.
# please fix this.
# Run real TS optimization
ts_param = {'method': 'pm3',
'basis': '',
'opt': 'ts,calcall,noeigentest',
'freq': 'freq',
'nproc': 1,
'mem': '8GB'}
ts_qmmol.calc = Gaussian(parameters=ts_param)
ts_conf = ts_qmmol.conformers[0]
ts_conf.conf_calculate(quantities=['energy', 'frequencies', 'intensities', 'normal_coordinates', 'structure'], keep_files=True)
ts_conf = ts_qmmol.conformers[0]
gs_dict['ts'] = ts_conf
gs_dict['ts_energy'] = ts_conf.results['energy']
gs_dict['correct_ts'] = ts_test(ts_conf)
return gs_dict
def create_qmmol():
""" Create qmmol, if qmconf works this is ok """
test_dir = os.path.dirname(os.path.realpath(__file__)) + '/data/formats/'
qmmol = QMMol()
qmmol.add_conformer(input_mol=test_dir + 'propanol.xyz',
fmt='xyz',
label='propanol',
charge=0,
multiplicity=1,
charged_fragments=True,
set_initial=True)
return qmmol
def gs_conformer_search(name, rdkit_conf, chrg, mult, cpus):
""" ground state conformer search """
charged = True # hard coded for mogens
# create conformers
qmmol = QMMol()
qmmol.add_conformer(rdkit_conf, fmt='rdkit', label=name,
charged_fragments=charged, set_initial=True)
# find #-- rot bond.
mol = qmmol.get_rdkit_mol()
triple_smart = '[c]:[c]-[CH0]#[CH0]'
extra_rot_bond = int(len(mol.GetSubstructMatches(Chem.MolFromSmarts(triple_smart))) / 2)
# print compute number of conformers to find
rot_bonds = len(RotatableBonds(qmmol.initial_conformer.get_rdkit_mol())) + extra_rot_bond
num_confs = 5 + 5*rot_bonds
qmmol.create_random_conformers(threads=cpus, num_confs=num_confs)
xtb_params = {'method': 'gfn2',
'opt': 'opt',
'cpus': 1}
qmmol.calc = xTB(parameters=xtb_params)
qmmol.optimize(num_procs=cpus, keep_files=False)
# Get most stable conformer. If most stable conformer
# not identical to initial conf try second lowest.
initial_smi = Chem.MolToSmiles(Chem.RemoveHs(qmmol.initial_conformer.get_rdkit_mol()))
low_energy_conf = qmmol.nlowest(1)[0]
conf_smi = Chem.MolToSmiles(Chem.RemoveHs(low_energy_conf.get_rdkit_mol()))
i = 1
while initial_smi != conf_smi:
low_energy_conf = qmmol.nlowest(i+1)[-1]
conf_smi = Chem.MolToSmiles(Chem.RemoveHs(low_energy_conf.get_rdkit_mol()))
i += 1
if len(qmmol.conformers) < i:
sys.exit('no conformers match the initial input')
return low_energy_conf
def gs_conformer_search(name, rdkit_conf, chrg, mult, cpus):
""" ground state conformer search """
charged = True # hard coded for mogens
# create conformers
qmmol = QMMol()
qmmol.add_conformer(rdkit_conf, fmt='rdkit', label=name,
charged_fragments=charged, set_initial=True)
rot_bonds = len(RotatableBonds(qmmol.initial_conformer.get_rdkit_mol()))
num_confs = 5 + 5*rot_bonds
qmmol.create_random_conformers(threads=cpus, num_confs=num_confs)
xtb_params = {'method': 'gfn2',
'opt': 'opt',
'cpus': 1}
qmmol.calc = xTB(parameters=xtb_params)
qmmol.optimize(num_procs=cpus, keep_files=False)
# Get most stable conformer. If most stable conformer
# not identical to initial conf try second lowest.
initial_smi = Chem.MolToSmiles(Chem.RemoveHs(qmmol.initial_conformer.get_rdkit_mol()))
try:
low_energy_conf = qmmol.nlowest(1)[0]
conf_smi = Chem.MolToSmiles(Chem.RemoveHs(low_energy_conf.get_rdkit_mol()))
except:
conf_smi = 'wrong'
i = 1
while initial_smi != conf_smi:
low_energy_conf = qmmol.nlowest(i+1)[-1]
conf_smi = Chem.MolToSmiles(Chem.RemoveHs(low_energy_conf.get_rdkit_mol()))
i += 1
if len(qmmol.conformers) < i:
sys.exit('no conformers match the initial input')
return low_energy_conf
def pm3opt(gs_dict):
""" Run Gaussian PM3 calculations on low energy xTB structures """
charged = True # hardcoded for this project.
xtb_reactant = gs_dict['xtb_reac']
xtb_product = gs_dict['xtb_prod']
pm3_param = {'method': 'pm6',
'basis': '',
'opt': 'opt',
'nproc': 1,
'mem': '4GB'}
for reac_prod, conf in [('reac', xtb_reactant), ('prod', xtb_product)]:
qmmol = QMMol()
name = conf.label
qmmol.add_conformer(conf.write_xyz(to_file=False), fmt='xyz',
label=name, charged_fragments=charged,
set_initial=True)
qmmol.calc = Gaussian(parameters=pm3_param)
qmconf = qmmol.conformers[0]
qmconf.conf_calculate(quantities=['energy', 'structure'], keep_files=False)
qmconf = qmmol.conformers[0]
if reac_prod == 'reac':
reac_conf = qmconf
reac_energy = qmconf.results['energy']
if reac_prod == 'prod':
prod_conf = qmconf
prod_energy = qmconf.results['energy']
gs_dict['pm3_reac'] = reac_conf
gs_dict['pm3_prod'] = prod_conf
gs_dict['pm3_storage'] = (prod_energy - reac_energy) * 627.503
return gs_dict
n = name + "_ts"
ts_scan(x.prod, n, charge, mult, xcontrol_name)
with open(n + "_xtbscan.log", 'r') as out:
output = out.read()
print(output)
ts_qmmol = QMMol()
xyz_file = ts_scan_xtb.read_ts_guess_structure2(output)
ts_qmmol.add_conformer(input_mol=xyz_file,
fmt='xyz',
label=n,
charge=charge,
multiplicity=mult,
read_freq=False,
charged_fragments=True)
ts_conf = ts_qmmol.conformers[0]
ts_conf.results['energy'] = ts_scan_xtb.read_ts_guess_energy(output)[0]
#print(ts_conf.results['energy'])
reac_qmconf = x.reac
prod_qmconf = x.prod
ts_qmconf = ts_conf
storage = x.storage * 2625.5 #convert from Hartree to kJ/mol
tbr = (ts_conf.results['energy'] - x.prod.results['energy']
) * 2625.5 #convert from Hartree to kJ/mol