A package for setting up, performing, and analyzing molecular dynamics ensembles using GROMACS
Project description
Ensemble Molecular Dynamics
ensemble_md
is a Python package that provides methods for setting up, running, and analyzing GROMACS simulation ensembles. Currently, the package implements all the necessary algorithms for running synchronous replica exchange (REX) of expanded ensembles (EE), abbreviated as REXEE, as well as its multi-topology (MT) variation, MT-REXEE. Our future work includes implementing asynchronous REXEE and other possible variations of the REXEE method. For installation instructions, theory overview, tutorials, and API references, please visit the documentation and our JCTC paper.
Reference
If you use any components of the Python package ensemble_md
or the REXEE method in your research, please cite the following paper:
Hsu, W. T., & Shirts, M. R. (2024). Replica Exchange of Expanded Ensembles: A Generalized Ensemble Approach with Enhanced Flexibility and Parallelizability. Journal of Chemical Theory and Computation. doi: 10.1021/acs.jctc.4c00484
Copyright
Copyright (c) 2022, Wei-Tse Hsu
Acknowledgements
Project based on the Computational Molecular Science Python Cookiecutter version 1.6.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file ensemble_md-1.0.0.tar.gz
.
File metadata
- Download URL: ensemble_md-1.0.0.tar.gz
- Upload date:
- Size: 584.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.15
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | d03dc7d4a6081488194ed3b16c981a404c996e458795778131736cec9f14b74f |
|
MD5 | 2e670ccc5026261a19c93ff90030c7d6 |
|
BLAKE2b-256 | e06ac65741255ded96a12d9f57f745fce4ff8c2d976b29f1ed1e9f0382707137 |
File details
Details for the file ensemble_md-1.0.0-py3-none-any.whl
.
File metadata
- Download URL: ensemble_md-1.0.0-py3-none-any.whl
- Upload date:
- Size: 273.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.15
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 53923e7950d7bd8a67c4d34ce43a68bae747c04d964084722ae0f93750f84b86 |
|
MD5 | 9e062678d5907bac777f6c37483c699e |
|
BLAKE2b-256 | 08c36e6401e5aaf1675244fdf711e4f6b9e7f8931491a497ae538967135980fa |