GROMACS

You can find this application in the demos folder of your Jupyter notebook environment.

GROMACS Molecular Dynamics Simulation

This tutorial demonstrates how to run a GROMACS (GROningen MAchine for Chemical Simulations) molecular dynamics simulation using Camber. GROMACS is one of the most widely used molecular dynamics packages, particularly popular for studying biomolecular systems like proteins, lipids, and nucleic acids.

In this example, we’ll simulate a protein in electrolyte solution using a comprehensive workflow that includes:

• Energy minimization to remove bad contacts
• NVT equilibration to establish proper temperature
• Interactive visualization of the simulation trajectory

Import Camber Package

First, we import the Camber package which provides the interface for running GROMACS simulations on the cloud platform:

import camber

Configure and Submit GROMACS Job

Here we configure and submit a GROMACS molecular dynamics job:

• command="sh ./sim.sh": Executes the simulation script that runs the complete GROMACS workflow
• engine_size="XSMALL": Indicates the engine size for the simulation
• with_gpu=True: Enables GPU acceleration for faster molecular dynamics calculations

The simulation uses these input files:

• sim.sh: Shell script orchestrating the complete GROMACS workflow
• 1cta.pdb: Initial protein structure (Protein Data Bank format)
• topol.top: Molecular topology file defining atoms, bonds, and force field parameters
• inputs/: Directory containing molecular dynamics parameter files:
  • minimize.mdp: Energy minimization parameters
  • nvt.mdp: NVT (constant volume/temperature) equilibration parameters
  • npt.mdp: NPT (constant pressure/temperature) production parameters

gmx_job = camber.gromacs.create_job(
    command="sh ./sim.sh",
    engine_size="XSMALL",
    with_gpu=True
)

Check Job Status

Monitor the job status to track the simulation progress through the multi-step GROMACS workflow:

gmx_job.status

Monitor Job Execution

To monitor job execution in real-time, use the read_logs() method to view the GROMACS output, including energy minimization progress, equilibration statistics, and production run details:

gmx_job.read_logs()

Analyze and Visualize Trajectory

Once the GROMACS simulation is complete, we can analyze and visualize the molecular dynamics trajectory. This section:

1. Loads the trajectory: Uses MDAnalysis to read the GROMACS trajectory files:

   • min-s.tpr: Processed structure file containing topology and coordinates
   • nvt_nopbc.xtc: Trajectory file with periodic boundary conditions removed

2. Creates interactive visualization: Uses NGLView to display the protein structure with:

   • cartoon representation for the protein backbone
   • licorice representation for solvent molecules (SOL)
   • Adjustable frame stepping for smooth playback

3. Adds playback controls: Provides a play widget with customizable speed for exploring the protein dynamics over time

The visualization shows how the protein structure evolves during the molecular dynamics simulation, including conformational changes and solvent interactions:

import os
import MDAnalysis as mda
import nglview as nv
import ipywidgets as widgets
from IPython.display import display

# 1) load your PBC-corrected trajectory
base_path = os.getcwd()
u = mda.Universe(
    os.path.join(base_path, "output/min-s.tpr"),
    os.path.join(base_path, "output/nvt_nopbc.xtc")
)
view = nv.show_mdanalysis(u, step=10)

view.clear_representations()
view.add_representation('cartoon', selection='protein')
view.add_representation('licorice', selection='resname SOL', radius=0.1)

# 2) make a Play widget to drive `view.frame`
play = widgets.Play(
    value=0,
    min=0,
    max=view.max_frame,
    step=1,
    interval=10,      # ms between frames; lower = faster
    description="▶️",
    continuous_update=True
)

# 3) link play.value → view.frame
widgets.jslink((play, 'value'), (view, 'frame'))

# 4) display controls + viewer
display(widgets.HBox([play]))
view