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Modeling with limited data
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README.md

MELD

Modeling with limited data

JL MacCallum, A Perez, and KA Dill, Determining protein structures by combining semireliable data with atomistic physical models by Bayesian inference, PNAS, 2015, 112(22), pp. 6985-6990.

Latest Release

Release versions are built here and can be installed from the maccallum_lab anaconda channel.

Installation

The preferred way to install is:

conda config --add channels maccallum_lab omnia
conda install meld-cuda{VER}

where VER is currently one of 75, 80, 90, or 92.

This will install MELD and all of its dependencies.

Testing

Test versions of MELD are built automatically. Current status:

Github master: Build Status Anaconda-Server Badge

Building from Scratch

MELD requires a CUDA compatible GPU.

  • ambermini or ambertools
  • netcdf4
  • mpi4py
  • openmm
  • CUDA Toolkit
  • python >= 3.6
  • numpy
  • scipy
  • sklearn
  • parmed

To install the python portion:

python setup.py install

To install the C++ / CUDA portion:

cd plugin
mkdir build
cd build
ccmake ..
make install
make PythonInstall

Documentation

Documentation will eventually be at project website, but this is currently a placeholder.

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