Why use reForge?
Working with large biomolecular complexes?
reForge aims to simplify the setup process for coarse-grained or all-atom Protein/RNA/Lipid complexes, helping to streamline what can often be a complex workflow.
Python-Based
reForge is built in Python, designed to be accessible and easy to integrate into existing workflows.
Streamlined Workflows: Python scripts help automate repetitive tasks. Whether managing a few or many MD simulations, reForge aims to reduce manual setup overhead.
Accelerated C- and CUDA Routines
Performance Optimization: Utilizes C and CUDA acceleration to improve processing speeds for large datasets compared to standard Python implementations.
Performance improvements can be particularly beneficial for medium to large systems (~1000+ residues) and when scaling to multiple systems.
Tools for Custom Model Development
Provides utilities to help develop custom models and integrate them with existing MD engines and analysis tools.
For New Users
Learning Resources: Tutorials and examples are included to help users get started with basic workflows and understand the package’s capabilities.