What is this repo?

This is a repository with some preparatory scripts for getting started running the AMOEBA force field using OpenMM.

This workflow utilizes only OpenMM, even using the modelling utilities inside to parametrize the system. You do not need to install the Tinker-OpenMM interface to use this workflow.

However, this is incapable of handling non-standard residues. You will need to use the standard Tinker workflow in that case.

Getting started

There are scripts in here to prepare the system for simulation, minimize the structure, and the perform standard dynamics (NVE, NVT, and NpT).

Dependencies

This whole workflow is implemented in Python. You will need to have the following tools installed:

• Python
• numpy
• OpenMM
• ParmEd

The easiest way to get all of this up and working is to install Anaconda or Miniconda. You can then use conda to install OpenMM quickly and easily! Use the following command:

conda install -c omnia openmm parmed

Note: if you used Miniconda, you will also need to install numpy via the command:

conda install numpy

Preparing your system

The prep_openmm.py script will take a PDB file (that you should have prepared and solvated previously using something like tleap from the AmberTools suite of programs) that has unit cell information (stored as a CRYST1 record) and parametrize it with a target force field.

To use prep_openmm.py, you can ask for help via the --help flag. A sample command-line that will create a system.xml file from structure.pdb using the AMOEBA 2013 protein force field is shown below:

prep_openmm.py -p structure.pdb -f amoeba2013 -s system.xml

For standard AMOEBA simulations, most of the defaults are appropriate. This is also the stage where you would implement H-mass repartitioning or SHAKE to try and limit high-frequency motions.

Minimizing your system

The minimize.py script is responsible for doing a local geometry optimization (using OpenMM's LBFGS minimizer). It takes both an XML file of a serialized OpenMM System and a PDB file as the source of coordinates. It produces an XML file of a serialized OpenMM State (which contains the minimized coordinates) for use in the next step.

Running dynamics

The main engine here for running dynamics is runmd.py. There are many options, and this can be used to run restrained dynamics, NVT, NpT (with either anisotropic or isotropic pressure scaling using the Monte-Carlo Barostat), or NVE. Note that for NVE, you should set an appropriately small default induced dipole tolerance in the preparatory step.

Like with the other Python scripts here, you can use the -h/--help flags to get a full listing of the available options.

This script will generate a tab-delimited output file with energies and other state variables, a NetCDF trajectory file (that can be analyzed alongside the original PDB file with any trajectory analysis program, like cpptraj and pytraj), and a NetCDF restart file for use in continuing the simulation.