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eARM HPC Workflow Deployment

Overview​

Standing up the eARM molecular modeling workflow on SLU’s HPC cluster.
The eARM pipeline is a computational framework that screens rhodopsin-like photoreceptors for fluorescent mutants.
It chains together multiple molecular modeling and simulation tools, all coordinated by pyARM, and runs them on the HPC system with SLURM job scheduling and cron automation.

Information​

  • Source Code: -https://github.com/oss-slu/earm_pipeline git
  • Client: eARM Scientific Community
  • Current Tech Lead: Vani Walvekar github
  • Developers: Collaborators at SLU HPC team, with support from Filippo and Massimo
  • Start Date: Aug, 2025
  • Technologies Used:
    • Python (pyARM framework)
    • Modeller, pdb2pqr, Dowser, FPocket, VMD, GROMACS
    • Molcas + Tinker (QM/MM calculations)
    • Conda environments
    • SLURM job scheduler
    • Crontab automation
  • Type: Scientific Workflow / HPC Deployment
  • License: MIT (https://opensource.org/license/mit)

Technical Information​

Workflow Summary​

  1. Protein Preparation

    • Use Modeller to complete missing structure pieces.
    • Use pdb2pqr to set charges and protonation states.
    • Add water molecules with Dowser and detect cavities with FPocket.

  2. Mutation Setup

    • Generate mutant proteins with pyARM.

  3. Molecular Dynamics (MD)

    • Simulate protein motion with GROMACS.

  4. QM/MM Calculations

    • Extract snapshots and compute fluorescence properties with Molcas (with Tinker).

  5. Analysis & Ranking

    • pyARM ranks mutants based on predicted fluorescence and stability.

  6. Automation on HPC

    • All steps are scheduled with SLURM and chained with crontab.
    • Enables running many mutants in parallel on the cluster.

Development Priorities​

  • Configure and deploy pyARM-based workflows on SLU’s HPC cluster.
  • Install and manage dependencies (GROMACS, Molcas, Modeller, pdb2pqr, Dowser).
  • Automate job execution with SLURM + cron.
  • Provide reproducible modulefiles and configuration for cluster users.
  • Deliver working demonstrations and documentation for collaborators.

Get Involved​

If you would like to contribute to this project, please visit our GitHub page to create your own issues or pull requests.