HylleraasMD documentation

Release:: 1.0.8
Date:: Mar 22, 2023

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 [Milano and Kawakatsu, 2009], or filtered density Hamiltonian hPF (HhPF-MD) simulations [Bore and Cascella, 2020], with or without explicit PME electrostatic interactions [Kolli et al., 2018]. 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 [Bore et al., 2018, Cascella et al., 2008]. Martini style elastic networks (ElNeDyn) [Periole et al., 2009] are also supported.

HyMD uses the pmesh (github.com/rainwoodman/pmesh) library for particle-mesh operations, with the PPFT [Pippig, 2013] backend for FFTs through the pfft-python bindings (github.com/rainwoodman/pfft-python). File IO is done via HDF5 formats to allow MPI parallel reads.

User Guide

The HylleraasMD User Guide provides comprehensive information on how to run simulations. Selected Examples are available to guide new users.

Installing HyMD

The easiest approach is to install using pip:

python3 -m pip install --upgrade pip
python3 -m pip install --upgrade numpy mpi4py cython
python3 -m pip install hymd

For more information and required dependencies, see Installation.

Run in Google colab

Run HyMD interactively in Google Colaboratory jupyter notebook here.

Source Code

Source code is available from https://github.com/Cascella-Group-UiO/HyMD/ under the GNU Lesser General Public License v3.0. Obtain the source code with git:

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

Development

HyMD is developed and maintained by researchers at the Hylleraas Centre for Quantum Molecular Sciences at the University of Oslo.

References

[BC20]

Sigbjørn Løland Bore and Michele Cascella. Hamiltonian and alias-free hybrid particle–field molecular dynamics. J. Chem. Phys., 153(9):094106, 2020. doi:10.1063/5.0020733.

[BMC18]

Sigbjørn Løland Bore, Giuseppe Milano, and Michele Cascella. Hybrid particle-field model for conformational dynamics of peptide chains. J. Chem. Theory Comput., 14(2):1120–1130, 2018. doi:10.1021/acs.jctc.7b01160.

[BDP07]

Giovanni Bussi, Davide Donadio, and Michele Parrinello. Canonical sampling through velocity rescaling. J. Chem. Phys., 126(1):014101, 2007. doi:10.1063/1.2408420.

[CNCDP08]

Michele Cascella, Marilisa A. Neri, Paolo Carloni, and Matteo Dal Peraro. Topologically based multipolar reconstruction of electrostatic interactions in multiscale simulations of proteins. J. Chem. Theory Comput., 4(8):1378–1385, 2008. doi:10.1021/ct800122x.

[KDNB+18]

Hima Bindu Kolli, Antonio De Nicola, Sigbjørn Løland Bore, Ken Schäfer, Gregor Diezemann, Jürgen Gauss, Toshihiro Kawakatsu, Zhong-Yuan Lu, You-Liang Zhu, Giuseppe Milano, and Michele Cascella. Hybrid particle-field molecular dynamics simulations of charged amphiphiles in an aqueous environment. J. Chem. Theory Comput., 14(9):4928–4937, 2018. doi:10.26434/chemrxiv.6264644.v1.

[LBC20]

Morten Ledum, SigbjÃ¸rn LÃ¸land Bore, and Michele Cascella. Automated determination of hybrid particle-field parameters by machine learning. Mol. Phys., 118(19-20):e1785571, 2020. doi:10.1080/00268976.2020.1785571.

[MK09]

Giuseppe Milano and Toshihiro Kawakatsu. Hybrid particle-field molecular dynamics simulations for dense polymer systems. J. Chem. Phys., 130(21):214106, 2009. doi:10.1063/1.3142103.

[PCMC09]

Xavier Periole, Marco Cavalli, Siewert-Jan Marrink, and Marco A Ceruso. Combining an elastic network with a coarse-grained molecular force field: structure, dynamics, and intermolecular recognition. Journal of chemical theory and computation, 5(9):2531–2543, 2009. doi:10.1021/ct9002114.

[Pip13]

Michael Pippig. Pfft: an extension of fftw to massively parallel architectures. SIAM J. Sci. Comput., 35(3):C213–C236, 2013. doi:10.1137/120885887.

[TBM92]

MBBJM Tuckerman, Bruce J Berne, and Glenn J Martyna. Reversible multiple time scale molecular dynamics. J. Chem. Phys., 97(3):1990–2001, 1992. doi:10.1063/1.463137.