Experiments with expanded ensemble simulation to explore chemical and mutational space.
This software is licensed under the MIT license, a permissive open source license.
Please be aware that this code is made available in the spirit of open science, but is currently pre-alpha--that is, it is not guaranteed to be completely tested or provide the correct results, and the API can change at any time without warning. If you do use this code, do so at your own risk. We appreciate your input, including raising issues about potential problems with the code, but may not be able to address your issue until other development activities have concluded.
See our installation instructions here.
In a fresh conda environment:
$ conda config --add channels conda-forge openeye
$ conda install perses openeye-toolkits
perses/- Package containing code for performing expanded ensemble simulationsexamples/- Contains examples for various systems and methods of simulationattic/- some old code that may be useful as part of the new setupdevtools/- Continuous integration and packaging utilitiesnotes/- LaTeX notes deriving acceptance criteria and stochastic approximation methods
A complete list of contributors can be found at GitHub Insights.
Major contributors include:
- Julie M. Behr
- Hannah E. Bruce Macdonald
- John D. Chodera
- Patrick B. Grinaway
- Mike M. Henry
- Iván J. Pulido
- Jaime Rodríguez-Guerra
- Dominic A. Rufa
- Ivy Zhang
Please consider citing:
- Software:
Rufa, D. A., Zhang, I., Bruce Macdonald, H. E., Grinaway, P. B., Pulido, I., Henry, M. M., Rodríguez-Guerra, J., Wittmann, M., Albanese, S. K., Glass, W. G., Silveira, A., Schaller, D., Naden, L. N., & Chodera, J. D. (2023). Perses (0.10.3). Zenodo. https://doi.org/10.5281/zenodo.8350218
- Protein mutations:
Zhang, I., Rufa, D. A., Pulido, I., Henry, M. M., Rosen, L. E., Hauser, K., Singh, S., & Chodera, J. D. (2023). Identifying and Overcoming the Sampling Challenges in Relative Binding Free Energy Calculations of a Model Protein:Protein Complex. Journal of chemical theory and computation, 19(15), 4863–4882. https://doi.org/10.1021/acs.jctc.3c00333
- Small molecule transformations:
Rufa, D. A., Bruce Macdonald, H. E., Fass, J., Wieder, M., Grinaway, P. B., Roitberg, A. E., Isayev, O., & Chodera, J. D. (2020). Towards chemical accuracy for alchemical free energy calculations with hybrid physics-based machine learning / molecular mechanics potentials. In bioRxiv (p. 2020.07.29.227959). https://doi.org/10.1101/2020.07.29.227959