kull-centre / calvados

CALVADOS

Coarse-graining Approach to Liquid-liquid phase separation Via an Automated Data-driven Optimisation Scheme

This repository contains Python code to run coarse-grained molecular dynamics simulations of intrinsically disordered proteins (IDPs) using the CALVADOS model.

Layout

• single_chain/ Python code to run single-chain simulations of IDPs using the CALVADOS model. python submit_local.py runs a simulation of a single ACTR chain on a single CPU.
• direct_coexistence/ Python code to run multi-chain simulations of IDPs using the CALVADOS model in slab geometry. python submit.py submits a direct-coexistence simulation of 100 A1 LCD chains on a single GPU.

In the examples, direct-coexistence and single-chain simulations are performed using openMM and HOOMD-blue installed with mphowardlab/azplugins, respectively.

Usage

To run the code, install Miniconda and make sure all required packages are installed by issuing the following terminal commands

    conda env create -f environment.yml
    source activate calvados

Commands to install HOOMD-blue v2.9.3 with mphowardlab/azplugins v0.11.0

    curl -LO https://github.com/glotzerlab/hoomd-blue/releases/download/v2.9.3/hoomd-v2.9.3.tar.gz
    tar xvfz hoomd-v2.9.3.tar.gz
    git clone https://github.com/mphowardlab/azplugins.git
    cd azplugins
    git checkout tags/v0.11.0
    cd ..
    cd hoomd-v2.9.3
    mkdir build
    cd build
    cmake ../ -DCMAKE_INSTALL_PREFIX=<path to python> \
        -DENABLE_CUDA=ON -DENABLE_MPI=ON -DSINGLE_PRECISION=ON -DENABLE_TBB=OFF \
        -DCMAKE_CXX_COMPILER=<path to g++> -DCMAKE_C_COMPILER=<path to gcc>
    make -j4
    cd ../hoomd
    ln -s ../../azplugins/azplugins azplugins
    cd ../build && make install -j4

Authors

Giulio Tesei (@gitesei)

Thea K. Schulze (@theaschulze)

Ramon Crehuet (@rcrehuet)

Kresten Lindorff-Larsen (@lindorff-larsen)

Articles

G. Tesei, T. K. Schulze, R. Crehuet, and K. Lindorff-Larsen. PNAS 118(44), 2021. DOI: 10.1073/pnas.2111696118

G. Tesei and K. Lindorff-Larsen. Open Research Europe 2023 2(94). DOI: 10.12688/openreseurope.14967.2