hymd 1.0.0

Massively parallel hybrid particle-field MD

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HylleraasMD (HyMD) is a massively parallel Python package for hybrid particle-field molecular dynamics (hPF-MD) simulations of coarse-grained bio- and soft-matter systems.

HyMD can run canonical hPF-MD simulations [1], or filtered density Hamiltonian hPF (HhPF-MD) simulations [2], with or without explicit PME electrostatic interactions [3]. It includes all standard intramolecular interactions, including stretching, bending, torsional, and combined bending-dihedral potentials. Additionally, topological reconstruction of permanent peptide chain backbone dipoles is possible for accurate recreation of protein conformational dynamics [4]. Martini style elastic networks (ElNeDyn) [5] are also supported.

HyMD uses the pmesh library for particle-mesh operations, with the PPFT [6] backend for FFTs through the pfft-python bindings. File IO is done via HDF5 formats to allow MPI parallel reads.

User Guide

Detailed installation and user guide, together with comprehensive example simulations are located in the HylleraasMD documentation.

Run simulations by

python3 -m hymd [CONFIGURATION_FILE] [TOPOLOGY_FILE]

Installation

Install HyMD with pip by

python3 -m pip install hymd

Install dependencies

HyMD installation requires a working MPI compiler. It is highly recommended to have MPI-enabled HDF5 and h5py for running parallel simulations with HyMD. Install both on Ubuntu with

sudo apt-get update -y
sudo apt-get install -y curl pkg-config python3-pip python3-mpi4py libhdf5-mpi-dev
export CC=mpicc
export HDF5_MPI="ON"
python3 -m pip install --no-binary=h5py h5py

Run in docker

Alternatively, an up-to-date docker image is available from docker hub

docker pull mortele/hymd
docker run -it mortele/hymd
/app# apt-get install -y git
/app# git clone https://github.com/Cascella-Group-UiO/HyMD.git hymd
/app# cd hymd/
/app/hymd# pip3 install .
/app/hymd# pytest 

Run tests

Clone the repository and run tests with pytest

git clone https://github.com/Cascella-Group-UiO/HyMD.git hymd
cd hymd
pytest

Running MPI enabled pytest tests is simplified with a convenient script

chmod +x pytest-mpi
pytest-mpi -oo -n 2 -ns

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References

[1] Milano, G.; Kawakatsu, T. Hybrid particle-field molecular dynamics simulations for densepolymer systems. J. Chem. Phys. 2009, 130, 214106.

[2] Bore, S. L.; Cascella, M. Hamiltonian and alias-free hybrid particle–field molecular dynam-ics. J. Chem. Phys. 2020, 153, 094106.

[3] Kolli, H. B.; De Nicola, A.; Bore, S. L.; Schäfer, K.; Diezemann, G.; Gauss, J.; Kawakatsu, T.;Lu, Z.-Y.; Zhu, Y.-L.; Milano, G.; Cascella, M. Hybrid Particle-Field Molecular DynamicsSimulations of Charged Amphiphiles in an Aqueous Environment. J. Chem. Theory Comput. 2018, 14, 4928–4937.

[4] Bore, S. L.; Milano, G.; Cascella, M. Hybrid Particle-Field Model for Conformational Dy-namics of Peptide Chains. J. Chem. Theory Comput. 2018, 14, 1120–1130.

[5] Periole, X.; Cavalli, M.; Marrink, S. J.; Ceruso, M. A. Combining an elastic network with a coarse-grained molecular force field: structure, dynamics, and intermolecular recognition. J. Chem. Theory Comput. 2009, 5.9, 2531-2543.

[6] Pippig, M. PFFT: An extension of FFTW to massively parallel architectures. SIAM J. Sci. Comput. 2013, 35, C213–C236.