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Making-it-rain

Cloud-based molecular simulations for everyone

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Hello there!

This is a repository where you can find a Jupyter notebook scripts for running Molecular Dynamics (MD) simulations using OpenMM engine and AMBER and CHARMM force fields files on Google Colab. This repository is a supplementary material of the paper "Making it rain: Cloud-based molecular simulations for everyone" and we encourage you to read it before using this pipeline.

The main goal of this work is to demonstrate how to harness the power of cloud-computing to run microsecond-long MD simulations in a cheap and yet feasible fashion.

  1. AMBER Open In Colab - Using AMBER to generate topology and to build the simulation box
  2. CHARMM Open In Colab - Using inputs from CHARMM-GUI solution builder
  3. AlphaFold2+MD Open In Colab - Using AlphaFold2_mmseqs2 to generate protein model + MD simulation using AMBER to generate topology and to build simulation box

UPDATE (October 2021)

  1. Protein-Ligand simulations Open In Colab - Using AMBER to generate topology and to build the simulation box and for the ligand using GAFF2 or OpenFF force fields
  2. Using AMBER Inputs Open In Colab - Using inputs from AMBER suite of biomolecular simulation program
  3. Using GROMACS Inputs Open In Colab - Using inputs from GROMACS biomolecular simulation package (AMBER, CHARMM and OPLS force fields are compatible)

UPDATE (March 2022)

  1. RESP Partial Charges Open In Colab - Using a SMILES as input and outputs a mol2 file with RESP derived partial charges. Options for setting method (HF, B3LYP, ...), basis set (3-21G, 6-31G*) and singlepoint or geometry optimization are available
  2. Small Molecules MD Open In Colab - Using a SMILES as a input, calculates RESP derived partial charges and uses these charges on topology generation (GAFF2 force field)
  3. GLYCAM Open In Colab - Using inputs from GLYCAM server

UPDATE (August 2022)

  1. DRUDE Open In Colab - Using inputs from CHARMM-GUI Drude Prepper

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Bugs

Acknowledgments

  • We would like to thank the Psi4 team for developing an excellent and open source suite of ab initio quantum chemistry.
  • We would like to thank the OpenMM team for developing an excellent and open source engine.
  • We would like to thank the AlphaFold team for developing an excellent model and open sourcing the software.
  • We would like to thank the ChemosimLab (@ChemosimLab) team for their incredible ProLIF (Protein-Ligand Interaction Fingerprints) tool.
  • Credits to Sergey Ovchinnikov (@sokrypton), Milot Mirdita (@milot_mirdita) and Martin Steinegger (@thesteinegger) for their fantastic ColabFold
  • Making it rain by Pablo R. Arantes (@pablitoarantes), Marcelo D. Polêto (@mdpoleto), Conrado Pedebos (@ConradoPedebos) and Rodrigo Ligabue-Braun (@ligabue_braun).
  • Also, credit to David Koes for his awesome py3Dmol plugin.
  • Finally, we would like to thank Professor Giulia Palermo for her support and thoughtful comments in the development of the present work.

Do you want to cite this work?

Arantes P.R., Depólo Polêto M., Pedebos C., Ligabue-Braun R. Making it rain: cloud-based molecular simulations for everyone. Journal of Chemical Information and Modeling 2021. DOI: 10.1021/acs.jcim.1c00998.

DOI

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