Plain Molecular Dynamics [MDRun]

Category Paths

Follow one of these paths in the Orion user interface, to find the floe.

  • Product-based/Molecular Dynamics/GROMACS

  • Product-based/Molecular Dynamics/OpenMM

  • Role-based/Computational Chemist

  • Role-based/Medicinal Chemist

  • Task-based/Molecular Dynamics

  • Solution-based/Hit to Lead/Target Preparation/Generic MD simulation


  • Purpose

    • This Floe runs unrestricted plain MD simulations on input datasets with fully set up, parameterized, and ready-to-run flasks. It makes possible long MD simulations in Orion, running MD simulations in chunks by using a Floe cycle topology.

    • Method Recommendations/Requirements:

      • If for some reason the Floe along the cycling should stop, the user can try to restart the Floe by using the recovery output

  • One input is required:

    • An Orion Dataset having records with a completely set up and ready-to-run MD flask, including solvent and counterions, and with the force field parameter applied. This can be produced by running one of the MD Floes like the Short Trajectory MD or the Bound Protein Ligand MD Floes, but it is not a prior restricted to protein-ligand flasks.

  • Expertise Level:

    • Regular

  • Compute Resource:

    • High

  • Keywords:

    • MD, Analysis

  • Related Floes:

    • Ligand Bound and Unbound Equilibration for NES [MDPrep] [MD]

    • Bound Protein-Ligand MD [MDPrep] [MDRun]

    • Analyze Protein-Ligand MD [MDAnalysis]

When the Floe completes, the produced chunked trajectories are uploaded to s3 as files and can be downloaded for analysis. In Addition the output dataset will have on its records the references to the produced trajectories which can then be extracted by using the MDDataRecord API.

If the starting dataset was generated by using the Bound Protein-Ligand Floe or the Ligand Bound and Unbound Equilibration Floe than the cycle Floe output can be analyzed by the Analyze Protein-Ligand MD Floe, although very large trajectories can cause problems for the clustering step in the analysis.

Promoted Parameters

Title in user interface (promoted name)

CPU GPU Spot Policy Selection

CPUs (cpu_count_md): The number of CPUs to run this cube with

  • Type: integer

  • Default: 16

GPUs (gpu_count_md): The number of GPUs to run this cube with

  • Type: integer

  • Default: 1

Spot policy (spot_policy_md): Control cube placement on spot market instances

  • Type: string

  • Default: Allowed

  • Choices: [‘Allowed’, ‘Preferred’, ‘NotPreferred’, ‘Prohibited’, ‘Required’]

Plain MD Setup Parameters

Time (time): Total simulation time in nanoseconds

  • Type: decimal

  • Default: 10

MD Engine (md_engine): Select the available MD Engine

  • Type: string

  • Default: OpenMM

  • Choices: [‘OpenMM’, ‘Gromacs’]

Hydrogen Mass Repartitioning (HMR): Give hydrogens more mass to speed up the MD

  • Type: boolean

  • Default: True

  • Choices: [True, False]

Trajectory Interval (trajectory_interval): Trajectory saving interval in nanoseconds

  • Type: decimal

  • Default: 0.01

Reporter interval (reporter_interval): Reporter saving interval in nanoseconds

  • Type: decimal

  • Default: 0.01

Cube max run time (cube_max_run_time): Max Cube Running Time in hrs

  • Type: decimal

  • Default: 1