Automated Adaptive Absolute alchemical Free Energy calculator. A package for running adaptive alchemical absolute binding free energy calculations with SOMD (distributed within sire) using adaptive protocols based on an ensemble of simulations. This requires the SLURM scheduling system. Please see the documentation.
For details of the algorithms and testing, please see the assocated paper:
Clark, F.; Robb, G. R.; Cole, D. J.; Michel, J. Automated Adaptive Absolute Binding Free Energy Calculations. J. Chem. Theory Comput. 2024, 20 (18), 7806–7828. https://doi.org/10.1021/acs.jctc.4c00806.
If you use a3fe in your research, please cite:
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Software: Clark, F., & Du, . (Haolin) R. (2025). a3fe: Automated Adaptive Absolute alchemical Free Energy calculator (0.4.0). Zenodo. https://doi.org/10.5281/zenodo.17298077.
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Paper: Clark, F.; Robb, G. R.; Cole, D. J.; Michel, J. Automated Adaptive Absolute Binding Free Energy Calculations. J. Chem. Theory Comput. 2024, 20 (18), 7806–7828. https://doi.org/10.1021/acs.jctc.4c00806.
Additionally, please cite the underlying software that makes a3fe possible:
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Sire: Christopher J. Woods, Lester O. Hedges, Adrian J. Mulholland, Maturos Malaisree, Paolo Tosco, Hannes H. Loeffler, Miroslav Suruzhon, Matthew Burman, Sofia Bariami, Stefano Bosisio, Gaetano Calabro, Finlay Clark, Antonia S. J. S. Mey, Julien Michel; Sire: An interoperability engine for prototyping algorithms and exchanging information between molecular simulation programs. J. Chem. Phys. 28 May 2024; 160 (20): 202503. https://doi.org/10.1063/5.0200458
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BioSimSpace:
- Hedges, L. O., Bariami, S., Burman, M., Clark, F., Cossins, B. P., Hardie, A., … Wu, Z. (2023). A Suite of Tutorials for the BioSimSpace Framework for Interoperable Biomolecular Simulation [Article v1.0]. Living Journal of Computational Molecular Science, 5(1), 2375. https://doi.org/10.33011/livecoms.5.1.2375
- Hedges et al., (2019). BioSimSpace: An interoperable Python framework for biomolecular simulation. Journal of Open Source Software, 4(43), 1831, https://doi.org/10.21105/joss.01831
a3fe depends on SLURM for scheduling jobs, and on GROMACS for running initial equilibration simulations. Please ensure that your have sourced your GMXRC or loaded your GROMACS module before proceeding with the installation. While we recommend installing with mamba, you can substitute mamba with conda in the following commands.
Now, download and install a3fe. Choose the appropriate environment for your use case:
Regular users:
git clone https://github.com/michellab/a3fe.git
cd a3fe
make env
mamba activate a3feDevelopers with local GROMACS:
make env-dev- Activate your a3fe conda environment
- Create a base directory for the calculation and create an directory called
inputwithin this - Move your input files into the the input directory. For example, if you have parameterised AMBER-format input files, name these bound_param.rst7, bound_param.prm7, free_param.rst7, and free_param.prm7. For more details see the documentation. Alternatively, copy the example input files from a3fe/a3fe/data/example_run_dir to your input directory.
- In the calculation base directory, run the following python code, either through ipython or as a python script (you will likely want to run the script with
nohupor use ipython through tmux to ensure that the calculation is not killed when you lose connection)
import a3fe as a3
calc = a3.Calculation(
ensemble_size=5, # Use 5 (independently equilibrated) replicate runs
slurm_config=a3.SlurmConfig(partition="<desired partition>"), # Set your desired partition!
)
calc.setup()
calc.get_optimal_lam_vals()
calc.run(adaptive=False, runtime = 5) # Run non-adaptively for 5 ns per replicate
calc.wait()
calc.set_equilibration_time(1) # Discard the first ns of simulation time
calc.analyse()
calc.save()- Check the results in the
outputdirectories (separate output directories are created for the Calculation, Legs, and Stages)
Copyright (c) 2025, Finlay Clark and Roy Haolin Du
Project based on the Computational Molecular Science Python Cookiecutter version 1.1.
