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Python package for building coarse-grained models using the Iterative Boltzmann Inversion (IBI) and Inverse Monte Carlo (IMC) methods

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Module name: scg4py (Systematic Coarse-Graining for Python)

Author: Saeed Mortezazadeh

Description: scg4py is a program written in python language to generate coarse-grained (CG) potentials of the system of interest through systematic coarse-graining approach. This module is a collection of tools to implement all coarse-graining steps including mapping the atomistic trajectory to the CG trajectory, generating the CG topology file, calculating distribution functions and refining the CG potentials through Iterative Boltzmann Inversion (IBI) and Inverse Monte Carlo (IMC) methods. In the following paper, we applied this module to study the lamellar and inverse hexagonal formation of lipid phases at different conditions. If you find this module useful, please cite our paper:

  • Implicit Solvent Systematic Coarse-Graining of Dioleoylphosphatidylethanolamine Lipids: from the Inverted Hexagonal to the Bilayer Structure, Saeed Mortezazadeh, Yousef Jamali, Hossein Naderi-Manesh, and Alexander P.Lyubartsev, (https://doi.org/10.1371/journal.pone.0214673)

For using this code you need python 3 and the following prerequisite modules: numpy, scipy, matplotlib, and mdtraj for parsing the ’dcd’ and ’xtc’ trajectory file formats. For ease of use, you can append the path of scg4py code to PYHTONPATH in the .bashrc file.

export PYTHONPATH="/path/to/scg4py/:$PYTHONPATH"

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Python package for building coarse-grained models using the Iterative Boltzmann Inversion (IBI) and Inverse Monte Carlo (IMC) methods

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