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196 | class Splinter(BaseInteractionDataset):
"""
Splinter consists of 30,416A dimer pairs with over 1.5 million geometries. The geometries are generated
by quantum mechanical optimization with B3LYP-D3/aug-cc-pV(D+d)Z level of theory. The interaction energies
and the various components are computed using SAPT0/qug-cc-pV(D=d)Z method.
Usage:
```python
from openqdc.datasets import Splinter
dataset = Splinter()
```
Reference:
https://doi.org/10.1038/s41597-023-02443-1
"""
__energy_unit__ = "kcal/mol"
__distance_unit__ = "ang"
__forces_unit__ = "kcal/mol/ang"
__name__ = "splinter"
__energy_methods__ = [
InteractionMethod.SAPT0_JUN_CC_PVDDZ,
InteractionMethod.SAPT0_JUN_CC_PVDDZ,
InteractionMethod.SAPT0_JUN_CC_PVDDZ,
InteractionMethod.SAPT0_JUN_CC_PVDDZ,
InteractionMethod.SAPT0_JUN_CC_PVDDZ,
InteractionMethod.SAPT0_JUN_CC_PVDDZ,
InteractionMethod.SAPT0_JUN_CC_PVDDZ,
InteractionMethod.SAPT0_JUN_CC_PVDDZ,
InteractionMethod.SAPT0_JUN_CC_PVDDZ,
InteractionMethod.SAPT0_JUN_CC_PVDDZ,
InteractionMethod.SAPT0_AUG_CC_PVDDZ,
InteractionMethod.SAPT0_AUG_CC_PVDDZ,
InteractionMethod.SAPT0_AUG_CC_PVDDZ,
InteractionMethod.SAPT0_AUG_CC_PVDDZ,
InteractionMethod.SAPT0_AUG_CC_PVDDZ,
InteractionMethod.SAPT0_AUG_CC_PVDDZ,
InteractionMethod.SAPT0_AUG_CC_PVDDZ,
InteractionMethod.SAPT0_AUG_CC_PVDDZ,
InteractionMethod.SAPT0_AUG_CC_PVDDZ,
InteractionMethod.SAPT0_AUG_CC_PVDDZ,
# "sapt0/jun-cc-pV(D+d)Z_unscaled", #TODO: we need to pick the unscaled version only here
# "sapt0/jun-cc-pV(D+d)Z_es_unscaled",
# "sapt0/jun-cc-pV(D+d)Z_ex_unscaled",
# "sapt0/jun-cc-pV(D+d)Z_ind_unscaled",
# "sapt0/jun-cc-pV(D+d)Z_disp_unscaled",
# "sapt0/jun-cc-pV(D+d)Z_scaled",
# "sapt0/jun-cc-pV(D+d)Z_es_scaled",
# "sapt0/jun-cc-pV(D+d)Z_ex_scaled",
# "sapt0/jun-cc-pV(D+d)Z_ind_scaled",
# "sapt0/jun-cc-pV(D+d)Z_disp_scaled",
# "sapt0/aug-cc-pV(D+d)Z_unscaled",
# "sapt0/aug-cc-pV(D+d)Z_es_unscaled",
# "sapt0/aug-cc-pV(D+d)Z_ex_unscaled",
# "sapt0/aug-cc-pV(D+d)Z_ind_unscaled",
# "sapt0/aug-cc-pV(D+d)Z_disp_unscaled",
# "sapt0/aug-cc-pV(D+d)Z_scaled",
# "sapt0/aug-cc-pV(D+d)Z_es_scaled",
# "sapt0/aug-cc-pV(D+d)Z_ex_scaled",
# "sapt0/aug-cc-pV(D+d)Z_ind_scaled",
# "sapt0/aug-cc-pV(D+d)Z_disp_scaled",
]
__energy_type__ = [
InterEnergyType.TOTAL,
InterEnergyType.ES,
InterEnergyType.EX,
InterEnergyType.IND,
InterEnergyType.DISP,
InterEnergyType.TOTAL,
InterEnergyType.ES,
InterEnergyType.EX,
InterEnergyType.IND,
InterEnergyType.DISP,
InterEnergyType.TOTAL,
InterEnergyType.ES,
InterEnergyType.EX,
InterEnergyType.IND,
InterEnergyType.DISP,
InterEnergyType.TOTAL,
InterEnergyType.ES,
InterEnergyType.EX,
InterEnergyType.IND,
InterEnergyType.DISP,
]
energy_target_names = []
__links__ = {
"dimerpairs.0.tar.gz": "https://figshare.com/ndownloader/files/39449167",
"dimerpairs.1.tar.gz": "https://figshare.com/ndownloader/files/40271983",
"dimerpairs.2.tar.gz": "https://figshare.com/ndownloader/files/40271989",
"dimerpairs.3.tar.gz": "https://figshare.com/ndownloader/files/40272001",
"dimerpairs.4.tar.gz": "https://figshare.com/ndownloader/files/40272022",
"dimerpairs.5.tar.gz": "https://figshare.com/ndownloader/files/40552931",
"dimerpairs.6.tar.gz": "https://figshare.com/ndownloader/files/40272040",
"dimerpairs.7.tar.gz": "https://figshare.com/ndownloader/files/40272052",
"dimerpairs.8.tar.gz": "https://figshare.com/ndownloader/files/40272061",
"dimerpairs.9.tar.gz": "https://figshare.com/ndownloader/files/40272064",
"dimerpairs_nonstandard.tar.gz": "https://figshare.com/ndownloader/files/40272067",
"lig_interaction_sites.sdf": "https://figshare.com/ndownloader/files/40272070",
"lig_monomers.sdf": "https://figshare.com/ndownloader/files/40272073",
"prot_interaction_sites.sdf": "https://figshare.com/ndownloader/files/40272076",
"prot_monomers.sdf": "https://figshare.com/ndownloader/files/40272079",
"merge_monomers.py": "https://figshare.com/ndownloader/files/41807682",
}
def read_raw_entries(self) -> List[Dict]:
logger.info(f"Reading Splinter interaction data from {self.root}")
data = []
i = 0
with tqdm(total=1680022) as progress_bar:
for root, dirs, files in os.walk(self.root): # total is currently an approximation
for filename in files:
if not filename.endswith(".xyz"):
continue
i += 1
filepath = os.path.join(root, filename)
filein = open(filepath, "r")
lines = list(map(lambda x: x.strip(), filein.readlines()))
n_atoms = np.array([int(lines[0])], dtype=np.int32)
metadata = lines[1].split(",")
try:
(
protein_monomer_name,
protein_interaction_site_type,
ligand_monomer_name,
ligand_interaction_site_type,
index,
r,
theta_P,
tau_P,
theta_L,
tau_L,
tau_PL,
) = metadata[0].split("_")
index, r, theta_P, tau_P, theta_L, tau_L, tau_PL = list(
map(float, [index, r, theta_P, tau_P, theta_L, tau_L, tau_PL])
)
except ValueError:
(
protein_monomer_name,
protein_interaction_site_type,
ligand_monomer_name,
ligand_interaction_site_type,
index,
_,
) = metadata[0].split("_")
r, theta_P, tau_P, theta_L, tau_L, tau_PL = [np.nan] * 6
energies = np.array([list(map(float, metadata[4:-1]))]).astype(np.float32)
n_atoms_ptr = np.array([int(metadata[-1])], dtype=np.int32)
total_charge, charge0, charge1 = list(map(int, metadata[1:4]))
lines = list(map(lambda x: x.split(), lines[2:]))
pos = np.array(lines)[:, 1:].astype(np.float32)
elems = np.array(lines)[:, 0]
atomic_nums = np.expand_dims(np.array([ATOM_TABLE.GetAtomicNumber(x) for x in elems]), axis=1)
natoms0 = n_atoms_ptr[0]
natoms1 = n_atoms[0] - natoms0
charges = np.expand_dims(np.array([charge0] * natoms0 + [charge1] * natoms1), axis=1)
atomic_inputs = np.concatenate((atomic_nums, charges, pos), axis=-1, dtype=np.float32)
subset = np.array([root.split("/")[-1]])
item = dict(
energies=energies,
subset=subset,
n_atoms=n_atoms,
n_atoms_ptr=n_atoms_ptr,
atomic_inputs=atomic_inputs,
protein_monomer_name=np.array([protein_monomer_name]),
protein_interaction_site_type=np.array([protein_interaction_site_type]),
ligand_monomer_name=np.array([ligand_monomer_name]),
ligand_interaction_site_type=np.array([ligand_interaction_site_type]),
index=np.array([index], dtype=np.float32),
r=np.array([r], dtype=np.float32),
theta_P=np.array([theta_P], dtype=np.float32),
tau_P=np.array([tau_P], dtype=np.float32),
theta_L=np.array([theta_L], dtype=np.float32),
tau_L=np.array([tau_L], dtype=np.float32),
tau_PL=np.array([tau_PL], dtype=np.float32),
name=np.array([protein_monomer_name + "." + ligand_monomer_name]),
)
data.append(item)
progress_bar.update(1)
logger.info(f"Processed {i} files in total")
return data
|