This package aids in the analysis of dissipation-corrected targeted molecular dynamics (dcTMD) simulations. The method enforces rare unbinding events of ligands from proteins via a constraint pulling bias. Subsequently, free energy profiles and friction factors are estimated along the unbinding coordinate. For a methodological overview, see our article.
S. Wolf, and G. Stock,
Targeted molecular dynamics calculations of free energy profiles using a nonequilibrium friction correction.,
J. Chem. Theory Comput. 2018 14 (12), 6175-6182,
doi: 10.1021/acs.jctc.8b00835
This package will be published soon:
M. Jäger, V. Tänzel, D. Nagel, and S. Wolf,
Dissipation Corrected Targeted Molecular Dynamics,
in preparation 2025
We kindly ask you to cite these articles in case you use this software package for published works.
- Intuitive usage via module and CI
- Sklearn-style API for fast integration into your Python workflow
- Supports Python 3.9-3.14
- Multitude of publications with dcTMD
- Estimation of free energy profiles and friction factors along the unbinding coordinate of ligands as described by Wolf and Stock 2018.
- Analysis of separate unbinding pathways as described by Wolf et al. 2023.
dcTMD is available on PyPI and conda-forge.
pip install dcTMDPyPI project page: https://pypi.org/project/dcTMD/
conda install conda-forge::dctmdConda-forge package page: https://anaconda.org/conda-forge/dcTMD
python3 -m pip install git+ssh://git@github.com/moldyn/dcTMD.gitCheck out the documentation for an overview over all modules as well as the tutorials.