OpenMM
A high-performance toolkit for molecular dynamics simulation with GPU acceleration.
Overview
OpenMM is a toolkit for molecular dynamics simulation that provides high performance on GPUs. It is designed to be extensible and flexible, allowing users to easily add new features and algorithms.
Features
- GPU-accelerated molecular dynamics
- Support for multiple force fields (AMBER, CHARMM, GROMACS)
- Python API for easy scripting
- Extensive analysis tools
- Cross-platform support
- Free energy calculations
- Enhanced sampling methods
Installation
Requirements
- Python 3.7+
- CUDA toolkit (for GPU support)
- CMake 3.10+
- C++ compiler (GCC 7.0+)
Installation Steps
- Install using conda:
conda install -c conda-forge openmm
- Or install from source:
git clone https://github.com/openmm/openmm.git cd openmm mkdir build cd build cmake .. make -j 4 make install
Basic Usage
Python Example
from openmm import *
from openmm.app import *
from openmm.unit import *
# Create a system
pdb = PDBFile('input.pdb')
forcefield = ForceField('amber14-all.xml', 'amber14/tip3p.xml')
system = forcefield.createSystem(pdb.topology, nonbondedMethod=PME)
# Create a simulation
integrator = LangevinMiddleIntegrator(300*kelvin, 1/picosecond, 0.004*picoseconds)
simulation = Simulation(pdb.topology, system, integrator)
simulation.context.setPositions(pdb.positions)
# Run the simulation
simulation.step(1000)
Advanced Topics
Custom Forces
OpenMM allows you to create custom forces and integrators. Here's an example of creating a custom force:
class CustomForce(CustomExternalForce):
def __init__(self, expression):
super().__init__(expression)
self.addPerParticleParameter("k")
Performance Optimization
- GPU acceleration
- Parallel computing
- Memory optimization
- Custom kernels