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

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