Hands-On Protein–Ligand Molecular Dynamics, Trajectory Analysis and MM/PBSA with GROMACS

To equip participants with practical skills in protein–ligand molecular dynamics, trajectory analysis, interaction assessment and MM/PBSA interpretation for computational drug discovery and structural biology research.

• Prepare a simulation-ready protein–ligand complex.
• Generate compatible protein and ligand topologies.
• Perform energy minimisation and equilibration.
• Process molecular dynamics trajectories correctly.
• Analyse RMSD, RMSF, radius of gyration and SASA.
• Evaluate hydrogen bonds, residue contacts and ligand movement.
• Perform and interpret MM/PBSA calculations.
• Prepare publication-quality plots, tables and summaries.

Day 1: Protein–Ligand System Preparation

Focus: Prepare and validate the molecular system before simulation.

• Role of MD after molecular docking
• Protein and ligand structure inspection
• Removal of unwanted molecules and structural errors
• Protein and ligand protonation considerations
• Force-field and water-model selection
• Protein and ligand topology preparation
• Simulation-box generation
• Solvation and ion addition
• Common topology and preparation errors

🛠️ Hands-On: Prepare a validated protein–ligand complex and construct a solvated, neutralised simulation system.

🧰 Tools Covered: GROMACS, Google Colab, PyMOL, Py3Dmol and Python

Day 2: Energy Minimisation and Equilibration

Focus: Stabilise the system before production molecular dynamics.

• Energy-minimisation workflow
• Convergence and maximum-force assessment
• NVT temperature equilibration
• NPT pressure and density equilibration
• Thermostat and barostat concepts
• Position restraints
• Energy, temperature, pressure and density analysis
• Preparation for production simulation

🛠️ Hands-On: Perform energy minimisation, NVT and NPT equilibration and evaluate system stability.

🧰 Tools Covered: GROMACS, Google Colab, Python, Pandas and Matplotlib

Day 3: Trajectory and Interaction Analysis

Focus: Evaluate structural stability and protein–ligand binding behaviour.

• Periodic-boundary-condition correction
• Molecular centring and trajectory fitting
• Protein-backbone RMSD
• Protein-aligned ligand RMSD
• Residue-level RMSF
• Radius of gyration
• Solvent-accessible surface area
• Protein–ligand distances
• Hydrogen-bond occupancy
• Residue-contact persistence
• Binding-pocket visualisation
• Common analysis and interpretation errors

🛠️ Hands-On: Analyse a validated production trajectory and generate publication-quality structural and interaction plots.

🧰 Tools Covered: GROMACS, Google Colab, Python, Pandas, Matplotlib, VMD and Py3Dmol

Day 4: MM/PBSA and Research Reporting

Focus: Interpret energetic contributions and integrate simulation results.

• Principles of MM/PBSA
• Receptor and ligand index preparation
• Trajectory-frame selection
• Van der Waals contributions
• Electrostatic contributions
• Polar and non-polar solvation energies
• Energy variability and convergence
• Optional residue-wise decomposition
• Limitations of endpoint energy methods
• Integration of docking, MD and energy results
• Preparation of figures, tables and conclusions

🛠️ Hands-On: Analyse MM/PBSA output and prepare a concise research-style molecular dynamics report.

🧰 Tools Covered: gmx_MMPBSA, GROMACS, Google Colab, AmberTools, Python, Pandas and Matplotlib

• PhD scholars and postgraduate students
• Researchers in computational drug discovery
• Biotechnology, bioinformatics and pharmacy learners
• Structural biology and molecular-modelling researchers
• Faculty supervising docking or MD projects
• Pharmaceutical and biotechnology professionals
• Researchers preparing theses, dissertations or manuscripts
• Learners progressing from molecular docking to molecular dynamics