File size: 16,706 Bytes
d0a41de a0321f2 d0a41de a0321f2 d0a41de |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 |
---
license:
- cc-by-4.0
license_link: https://creativecommons.org/licenses/by/4.0
tags:
- homo-lumo-gaps
- energy
- dipole-moments
- quantum-chemistry
- pubchem
- small-molecules
- ir-frequencies
- ir-intensities
annotations_creators:
- crowdsourced
pretty_name: pubchemqc-pm6
size_categories:
- 10K<n<300M
source_datasets:
- pubchem
- pubchemqc-pm6
task_categories:
- tabular-regression
- other
task_ids:
- tabular-single-column-regression
viewer: false
configs:
- config_name: pm6opt
data_files:
- split: train
path: "data/pm6opt/train/*.json"
default: true
- config_name: pm6opt_chon300nosalt
data_files:
- split: train
path: "data/pm6opt_chon300nosalt/train/*.json"
- config_name: pm6opt_chon500nosalt
data_files:
- split: train
path: "data/pm6opt_chon500nosalt/train/*.json"
- config_name: pm6opt_chnops500nosalt
data_files:
- split: train
path: "data/pm6opt_chnops500nosalt/train/*.json"
- config_name: pm6opt_chnopsfcl300nosalt
data_files:
- split: train
path: "data/pm6opt_chnopsfcl300nosalt/train/*.json"
- config_name: pm6opt_chnopsfcl500nosalt
data_files:
- split: train
path: "data/pm6opt_chnopsfcl500nosalt/train/*.json"
- config_name: pm6opt_chnopsfclnakmgca500
data_files:
- split: train
path: "data/pm6opt_chnopsfclnakmgca500/train/*.json"
---
# PubChemQC PM6 Dataset
## Table of Contents
- [PubChemQC PM6 Dataset](#pubchemqc-pm6-dataset)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits and Configurations](#data-splits-and-configurations)
- [How to Use the Dataset](#how-to-use-the-dataset)
- [Prerequisites](#prerequisites)
- [Accessing the Data](#accessing-the-data)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** https://nakatamaho.riken.jp/pubchemqc.riken.jp/pm6_datasets.html
- **Repository:** https://nakatamaho.riken.jp/pubchemqc.riken.jp/pm6_datasets.html
- **Paper:** https://pubs.acs.org/doi/abs/10.1021/acs.jcim.0c00740
- **Point of Contact:** [Maho Nakata]([email protected])
- **Point of Contact:** [Mohammad Mostafanejad]([email protected])
- **Point of Contact:** [MolSSI-AI Hub]([email protected])
### 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:
```json
{
"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`,
```bash
conda create -n pubchemqc python=3.12
```
and activate it using the following command
```bash
conda activate pubchemqc
```
Once the conda environment is activated, you can
install the dependencies in it as shown below
```bash
pip install huggingface_hub ijson
```
### Accessing the Data
Once the required packages are installed, you can run the following code
to access the data
```python
# 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](#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](https://huggingface.co/datasets/molssiai-hub/pubchemqc-pm6/blob/main/pubchemqc-pm6.py), 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](https://nakatamaho.riken.jp/pubchemqc.riken.jp/pm6_datasets.html)
#### Initial Data Collection and Normalization
Other than the changes detailed in Sec. [Curation Rationale](#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](https://creativecommons.org/licenses/by/4.0)
### Citation Information
```tex
@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)
|