PubChemQC PM6 Dataset
Dataset Summary
The PubChemQC PM6 dataset consists of optimized molecular geometries and electronic properties calculated by the PM6 method for 94.0% of the 91.6 million molecules cataloged in PubChem Compounds retrieved on August 29, 2016. In addition to neutral states, the cationic, anionic, and spin flipped electronic states of respectively 56.2%, 49.7%, and 41.3% of the molecules have also been studied. As such, the grand total of the PM6 calculations amounted to 221 million.
Dataset Structure
Data Instances
An example of a data instance is as follows:
{
"cid": 1,
"state": "S0",
"pubchem-inchi": "InChI=1S/C9H17NO4/c1-7(11)14-8(5-9(12)13)6-10(2,3)4/h8H,5-6H2,1-4H3",
"pubchem-charge": 0,
"pubchem-version": "20160829",
"name": "000000001.PM6.S0",
"coordinates": [4.543146, -2.8411939999999998, -1.641861, ..., 4.345637],
"atomic-numbers": [6, 6, 8, ..., 1],
"atom-count": 31,
"heavy-atom-count": 14,
"core-electrons": [0, 0, 0,..., 0],
"version": "2.0",
"obabel-inchi": "InChI=1S/C9H17NO4/c1-7(11)14-8(5-9(12)13)6-10(2,3)4/h8H,5-6H2,1-4H3/t8-/m0/s1",
"pm6-obabel-canonical-smiles": "[O]C(=O)C[C@@H](C[N](C)(C)C)OC(=O)C",
"charge": 0,
"energy-beta-gap": 8.458931156643,
"energy-beta-homo": -8.8325434733795,
"energy-beta-lumo": -0.37361231673649903,
"energy-alpha-gap": 8.458931156643,
"energy-alpha-homo": -8.8325434733795,
"energy-alpha-lumo": -0.37361231673649903,
"total-energy": -7.558832783207512,
"enthalpy": -0.021744,
"homos": [40],
"orbital-energies": [
[-34.149199782348006,
-32.51760513475,
-30.809274381311,
...,
6.947610830966
]
],
"mo-count": 73,
"basis-count": 73,
"temperature": 298.15,
"multiplicity": 1,
"number-of-atoms": 31,
"mulliken-partial-charges": [-0.5888869999999999,
0.6862539999999999,
-0.580137,
...,
0.18249
],
"dipole-moment": 13.22226250268841,
"frequencies": [26.1465, 37.9831, 50.1099, ..., 2779.2147],
"intensities": [0.771, 11.6909, 2.5082, ..., 111.8945],
"pubchem-multiplicity": 1,
"pubchem-obabel-canonical-smiles": "[O-]C(=O)CC(C[N+](C)(C)C)OC(=O)C",
"pubchem-isomeric-smiles": "CC(=O)OC(CC(=O)[O-])C[N+](C)(C)C",
"pubchem-molecular-weight": 203.23558,
"pubchem-molecular-formula": "C9H17NO4"
}
Data Fields
Field | Description |
---|---|
cid | Pubchem Compound ID |
state | Electronic state |
pubchem-inchi | InChI extracted from PubChem Compound entry |
pubchem-charge | Molecular charge extracted from PubChem Compound entry |
pubchem-version | PubChem Compound Database version |
name | Name of the input file used for the PM6 calculation |
coordinates | Cartesian coordinates of the molecular geometry optimized with PM6 method in Angstroem |
atomic-numbers | An array of atomic numbers |
atom-count | Number of atoms in the molecule |
heavy-atom-count | Number of heavy atoms in the molecule |
core-electrons | The number of core electrons in each atom's pseudopotentials |
version | Version number |
obabel-inchi | InChI of the structure generated by Open Babel |
pm6-obabel-canonical-smiles | Canonical SMILES for the structure generated by Open Babel |
charge | Molecular charge |
energy-beta-gap | HOMO-LUMO energy gap for beta spin orbitals |
energy-beta-homo | Energy of the highest-occupied molecular orbital (HOMO) of beta spin symmetry |
energy-beta-lumo | Energy of the lowest-unoccupied molecular orbital (LUMO) of beta spin symmetry |
energy-alpha-gap | HOMO-LUMO energy gap for alpha spin orbitals |
energy-alpha-homo | Energy of the highest-occupied molecular orbital (HOMO) of alpha spin symmetry |
energy-alpha-lumo | Energy of the lowest-unoccupied molecular orbital (LUMO) of alpha spin symmetry |
total-energy | Total electronic energy of the molecule calculated using PM6 method |
enthalpy | Enthalpy |
homos | 1D index array of the highest occupied molecular orbital (HOMOs) with one (two) element(s) for the (un)restricted wavefunctions |
orbital-energies | 1D array of orbital energies in hartree with one (two) member(s) for the (un)restricted wavefunction |
mo-count | Number of molecular orbitals |
basis-count | Number of basis functions |
temperature | Temperature (in K) |
multiplicity | Spin multiplicity |
number-of-atoms | Number of atoms in the molecule |
mulliken-partial-charges | Mulliken partial atomic charges |
dipole-moment | Dipole moment |
frequencies | Infrared (IR) frequencies (in cm$^{-1}$) |
intensities | Infrared intensities |
pubchem-multiplicity | Spin multiplicity of the molecule extracted from PubChem Compound |
pubchem-obabel-canonical-smiles | Canonical SMILES of the molecule extracted from PubChem Compound generated by Open Babel |
pubchem-isomeric-smiles | Isomeric SMILES of the molecule extracted from PubChem Compound calculated by the OpenEye's OEChem Toolkit |
pubchem-molecular-weight | Molecular weight extracted from the PubChem Compound entry |
pubchem-molecular-formula | Molecular formula extracted from the PubChem Compound entry |
Data Splits and Configurations
The dataset has only one train
split. The PubChemQC PM6 dataset
has seven configurations/subsets:
pm6opt
(default)pm6opt_chon300nosalt
pm6opt_chon500nosalt
pm6opt_chnops500nosalt
pm6opt_chnopsfcl300nosalt
pm6opt_chnopsfcl500nosalt
pm6opt_chnopsfclnakmgca500
How to Use the Dataset
Prerequisites
We recommend isolating your work in a virtualenv or conda environment.
You can create a new conda environment, pubchemqc
,
conda create -n pubchemqc python=3.12
and activate it using the following command
conda activate pubchemqc
Once the conda environment is activated, you can install the dependencies in it as shown below
pip install huggingface_hub ijson
Accessing the Data
Once the required packages are installed, you can run the following code to access the data
# import the modules
from datasets import load_dataset
# load the dataset with streaming
hub_ds = load_dataset(path="molssiai-hub/pubchemqc-pm6",
name="pm6opt",
split="train",
streaming=True,
cache_dir="./tmp",
trust_remote_code=True)
# fetch a batch of 32 samples from the dataset
ds = list(hub_ds.take(32))
The argument name
by default is set to pm6opt
which refers to
the entire dataset. Other configurations (subsets), listed in
Sec. Data Splits and Configurations,
can also be selected.
The split
must be set to train
as it is the only split in our dataset.
We recommend using streaming=True
to avoid downloading the entire dataset
on disk. The cache_dir
allows us to store the Hugging Face datasets' and
models' artifacts in a non-default directory (by default, it is set to
~/.cache/huggingface
). As we are using a custom
load script, the trust_remote_code
argument should also be set to True
.
Dataset Creation
Curation Rationale
The present version of PubChemQC PM6 dataset has been extracted
from its original Postgresql database, transformed into a dictionary and
stored in the .json
format.
Source Data
The link to the original PubChemQC PM6 dataset repository can be found here
Initial Data Collection and Normalization
Other than the changes detailed in Sec. Curation Rationale, no data modification has been performed on the PubChemQC PM6 dataset.
Personal and Sensitive Information
The PubChemQC PM6 dataset does not involve any personal or sensitive information.
Considerations for Using the Data
Social Impact of Dataset
The PubChemQC PM6 dataset paves the way for applications in drug discovery and materials science, among others.
Additional Information
Dataset Curators
- Maho Nakata, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
- Tomomi Shimazaki, Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe, Hyogo 657-8501, JAPAN
- Masatomo Hashimoto, Software Technology and Artificial Intelligence Research Laboratory, Chiba Institute of Technology, 2-17-1 Tsudanuma, Narashino, Chiba 275-0016, Japan
- Toshiyuki Maeda, Software Technology and Artificial Intelligence Research Laboratory, Chiba Institute of Technology, 2-17-1 Tsudanuma, Narashino, Chiba 275-0016, Japan
Licensing Information
Creative Commons Attribution 4.0 International License
Citation Information
@article{Nakata:2020:5891,
author = {Maho Nakata and Tomomi Shimazaki and Masatomo Hashimoto and Toshiyuki Maeda},
doi = {10.1021/acs.jcim.0c00740},
issn = {1549960X},
issue = {12},
journal = {Journal of Chemical Information and Modeling},W
month = {12},
pages = {5891-5899},
pmid = {33104339},
publisher = {American Chemical Society},
title = {PubChemQC PM6: Data Sets of 221 Million Molecules with Optimized Molecular Geometries and Electronic Properties},
volume = {60},
url = {https://pubs.acs.org/doi/abs/10.1021/acs.jcim.0c00740},
year = {2020},
}
Contributions
- Mohammad Mostafanejad, The Molecular Sciences Software Institute (MolSSI)
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