Monte Carlo and Molecular Dynamics simulations for atomistic, coarse-grained, and mesoscale modeling. OpenMM library provides functionality for the atomistic and coarse-grained particle models. Extending CHARMM compatibility to more software codes.
please cite: "Interplay of Protein and DNA Structure Revealed in Simulations of the lac Operon" (PLOS One 2013)
for any code related to protein-DNA modeling and
"Free Energy Monte Carlo Simulations on a Distributed Network" (Lecture Notes in Computer Science Journal for PARA 2010)
for parallel client-server code, users of additional code should cite this web site. Code is provided as-is with no warranty and examples are provided to illustrate the usage of these modeling techniques with some sample systems. Code is the intellectual property of Luke Czapla, developer and biophysicist. Examples are provided in C/C++ and Python.
The goal of these tools is to interpret experimental data and provide insight into complex biological systems using physics and statistical mechanics. Potential uses are for analyzing simulation results and building larger models from simulation data and preparing for runs using OpenMM and running massive calculation in parallel.
The methods are focused on computer simulations with enhanced sampling techniques. Monte Carlo and Molecular Dynamics simulations written from the ground up and using the OpenMM toolkit (LGPL C++ library)