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MolSSI/mm_workflows

Examples of MM-based workflows

Installation

Google colab notebooks

Install conda with a handy pip package by Jaime Rodríguez-Guerra
You have to run this first, and then wait to run any other cells.
This terminates and reboots the Python session.

!pip install -q condacolab
import condacolab
condacolab.install()

To make sure Conda was installed correctly, run

import condacolab
condacolab.check()

Get the Conda env file we are going to need and install the file

!wget https://raw.githubusercontent.com/MolSSI/mmic_autodock_vina/main/devtools/conda-envs/test_env.yaml
!mamba env update -n base -f test_env.yaml
!pip install git+https://github.com/MolSSI/mmic_autodock_vina.git

Local machine

Make sure conda is installed on your system, then run the following:

conda env create -f https://raw.githubusercontent.com/MolSSI/mmic_autodock_vina/main/devtools/conda-envs/test_env.yaml

Then activate the test environment:

conda activate test

MMIC workflows

  • Docking: QC-based ligand conformation generation for rigid-receptor docking.
  • Dynamics: forcefield assignment, energy minimization, and molecular dynamics

MMElemental

  • Molecule: molecule object creation from common file formats
  • ForceField: forcefield object creation and manipulation

Languages

Jupyter Notebook100.0%

Contributors

Created April 9, 2021
Updated March 15, 2025