Gaussian Accelerated Molecular Dynamics (GaMD) is a biomolecular enhanced sampling method that works by adding a harmonic boost potential to smoothen the system potential energy surface. By constructing a boost potential that follows Gaussian distribution, accurate reweighting of the GaMD simulations is achieved using cumulant expansion to the second order. GaMD has been demonstrated on three biomolecular model systems: alanine dipeptide, chignolin folding and ligand binding to the T4-lysozyme. Without the need to set predefined reaction coordinates, GaMD enables unconstrained enhanced sampling of these biomolecules. Furthermore, the free energy profiles obtained from reweighting of the GaMD simulations allow us to identify distinct low energy states of the biomolecules and characterize the protein folding and ligand binding pathways quantitatively.
- You will need to start by installing Anaconda Python 3.x.
- Next, install OpenMM using the instructions found in the OpenMM User Guide - Section 2.2 Installing OpenMM.
- You'll need the AmberTools for doing the post MD analysis. You can do this by executing the following command:
conda install -c conda-forge ambertools=20 - Finally, you'll need the PyReweighting scripts, which can be cloned from the PyReweighting Git Repository. (NOTE: If you are doing development on the GaMD module itself and want to use the test scripts, the PyReweighting project directory should be added to your path, so that the scripts can find it.)
The dihedral and total boost algorithms are working and have been validated.