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https://github.com/drorlab/atom3d
ATOM3D: tasks on molecules in three dimensions
https://github.com/drorlab/atom3d
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ATOM3D: tasks on molecules in three dimensions
- Host: GitHub
- URL: https://github.com/drorlab/atom3d
- Owner: drorlab
- License: mit
- Created: 2020-04-03T22:53:11.000Z (about 4 years ago)
- Default Branch: master
- Last Pushed: 2023-03-02T18:21:02.000Z (over 1 year ago)
- Last Synced: 2024-05-14T14:04:56.092Z (about 1 month ago)
- Language: Python
- Homepage: https://www.atom3d.ai
- Size: 40.7 MB
- Stars: 288
- Watchers: 16
- Forks: 34
- Open Issues: 20
-
Metadata Files:
- Readme: README.md
- Contributing: docs/contributing.rst
- License: LICENSE
Lists
- awesome-python-chemistry - atom3d - Enables machine learning on three-dimensional molecular structure. (Machine Learning)
- awesome-python-chemistry - atom3d - Enables machine learning on three-dimensional molecular structure. (Machine Learning)
README
# ATOM3D: Tasks On Molecules in 3 Dimensions
[](http://atom3d.readthedocs.io/?badge=latest)
[](https://codecov.io/gh/drorlab/atom3d)
[](https://badge.fury.io/py/atom3d)
[ATOM3D](https://www.atom3d.ai/) enables machine learning on three-dimensional molecular structure.
## Features
* Access to several datasets involving 3D molecular structure.
* LMDB data format for storing lots of molecules (and associated metadata).
* Utilities for splitting/filtering data based on many criteria.
For more detailed information, [read the documentation](https://atom3d.readthedocs.io/en/latest/).
## Installation
Install with:
```
pip install atom3d
```
To use rdkit functionality, please install within conda:
```
conda create -n atom3d python=3.6 pip rdkit
conda activate atom3d
pip install atom3d
```
## Usage
### Downloading a dataset
From python:
```
import atom3d.datasets as da
da.download_dataset('lba', PATH_TO_DATASET) # Download LBA dataset.
```
Or, download and unzip from the [website](https://www.atom3d.ai/).
### Loading a dataset
From python:
```
import atom3d.datasets as da
dataset = da.load_dataset(PATH_TO_DATASET, {'lmdb','pdb','silent','sdf','xyz','xyz-gdb'})
print(len(dataset)) # Print length
print(dataset[0].keys()) # Print keys
```
### LMDB datasets
LMDB allows for compressed, fast, random access to your structures, all within a
single database. Currently, we support creating LMDB datasets from PDB files, silent files, and xyz files.
#### Creating an LMDB dataset
From command line:
```
python -m atom3d.datasets PATH_TO_PDB_DIR PATH_TO_DATASET --filetype {pdb,silent,xyz,xyz-gdb}
```
For more usage, please see the [documentation](https://atom3d.readthedocs.io/en/latest/).
## Contribute
As a living repository, we welcome contributions of additional datasets, methods, and functionality! See the [Contributing](https://atom3d.readthedocs.io/en/latest/contributing.html) section of the documentation for details.
## Support
For support, please file an issue at https://github.com/drorlab/atom3d/issues.
## License
The project is licensed under the [MIT license](https://github.com/drorlab/atom3d/blob/master/LICENSE).
## Reference
We provide an overview on ATOM3D and details on the preparation of all datasets in our preprint:
> R. J. L. Townshend, M. Vögele, P. Suriana, A. Derry, A. Powers, Y. Laloudakis, S. Balachandar, B. Jing, B. Anderson, S. Eismann, R. Kondor, R. B. Altman, R. O. Dror "ATOM3D: Tasks On Molecules in Three Dimensions", [arXiv:2012.04035](https://arxiv.org/abs/2012.04035)
Please cite this work if some of the ATOM3D code or datasets are helpful in your scientific endeavours. For specific datasets, please also cite the respective original source(s), given in the preprint.