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GROMACS Tutorials, Rebuilt for Premium Learning

A clean, structured presentation of the uploaded GROMACS tutorial suite by Justin A. Lemkul, with the original tutorial sequence, scientific scope, source links, and attribution preserved.

Compatible with GROMACS 2018+ Selected tutorials updated for 2025 Fundamentals to advanced topics Original tutorial links retained
3Fundamental tutorial pathways
6Advanced and specialized topics
CC-BY 4.0Original tutorial content is attributed to Justin A. Lemkul and the source tutorial page.

Prepare Before Entering the Tutorial Suite

AMRA-Lab places installation and file preparation first so learners enter the original tutorials with a verified setup and organized simulation inputs.

01

Latest GROMACS Installation

Install and verify GROMACS using an appropriate CPU, CUDA GPU, thread-MPI, or external-MPI pathway.

Compiler and CMakeGPU accelerationMPI planningRegression tests
Open installation reference
02

Simulation File Preparation

Inspect, clean, organize, and validate structures, topologies, force-field files, MDP files, index groups, and restraints.

PDB inspectionForce fieldsTopology hierarchyFolder protocol
AMRA-Lab module page coming later

Complete GROMACS Tutorial Collection

Filter the premium cards by level. Each available card opens the original tutorial source in a new tab.

Important Post-Simulation & Enhanced-Sampling Analyses

A focused post-MD, enhanced-sampling, energetic, secondary-structure, and predictive-modeling pathway covering trajectory quality, protein–ligand retention, DSSP, per-residue energetics, steered molecular dynamics, PMF, QSAR, and publication-oriented interpretation.

1. Prepare the Trajectory Correct periodic boundaries, center the system, fit the protein, and validate frames.
2. Confirm Stability Evaluate global structure, residue flexibility, compactness, exposure, and secondary structure.
3. Examine Binding Track ligand retention, hydrogen bonds, contact occupancy, and energetic contributions.
4. Interpret Dynamics Use PCA, free-energy landscapes, clustering, and correlation analyses for deeper conclusions.
5. SMD & PMF Interpret pulling force, displacement, reaction-coordinate behavior, and free-energy profiles.
Essential First Step

Trajectory Processing & PBC Correction

Remove periodic-boundary artifacts, center the complex, fit the protein, and generate analysis-ready trajectories.

trjconvCenteringRot+trans fitFrame validation
Detailed module later
Core Stability

Protein RMSD

Measure global structural deviation, equilibration behavior, persistent drift, and major conformational transitions.

BackbonePlateauReplicate comparison
Detailed module later
Residue Level

Residue RMSF

Identify flexible loops, stabilized binding-site residues, mobile termini, and mutation-sensitive regions.

Per residueBinding siteLoop motionB-factor mapping
Detailed module later
Compactness

Radius of Gyration & SASA

Assess protein compactness, folding consistency, solvent exposure, and ligand-associated changes in accessible surface area.

RgSASAHydrophobic exposureCompactness
Detailed module later
Interaction Stability

Hydrogen-Bond Analysis

Quantify protein–ligand and intraprotein hydrogen bonds, donor–acceptor persistence, distances, and occupancies.

H-bond countOccupancyDistanceLifetime
Detailed module later
Ligand Retention

Ligand RMSD & Binding-Site Retention

Track ligand pose stability after protein fitting and detect rearrangement, partial escape, or complete unbinding.

Protein-fit RMSDCOM distanceEscape warningPose stability
Detailed module later
Binding Contacts

Protein–Ligand Contact Occupancy

Measure persistent hydrophobic, ionic, aromatic, water-mediated, and residue-specific interactions across the trajectory.

Contact mapPLIPProLIFOccupancy heatmap
Detailed module later
Binding Energetics

MM/PBSA & MM/GBSA

Estimate relative binding energetics, decompose residue contributions, and identify stabilizing or unfavorable interaction regions.

ΔGbindPer-residueEnergy componentsUncertainty
Detailed module later
Essential Dynamics

PCA & Essential Dynamics

Reduce high-dimensional motion into dominant collective modes and compare conformational sampling between systems.

EigenvectorsPC1–PC2VariancePorcupine motion
Detailed module later
Energy Basins

Free-Energy Landscape

Map low-energy conformational basins, transition regions, metastable states, and representative structures.

PC-based FELBasinsMinimaState transitions
Detailed module later
Representative States

Clustering & Representative Structures

Group related conformations, calculate cluster occupancy, select medoids, and identify dominant structural states.

Cluster occupancyMedoidsTransitionsRepresentative frames
Detailed module later
Correlated Motion

DCCM & Dynamic Network Analysis

Reveal correlated and anticorrelated residue motions, communication pathways, communities, and potential allosteric routes.

DCCMCommunitiesCentralityAllostery
Detailed module later
Enhanced Sampling

Steered Molecular Dynamics Simulation

Apply a controlled pulling force along a defined reaction coordinate to investigate ligand dissociation, molecular separation, or conformational transitions.

Pull codePull groupSpring constantPulling velocity
Detailed SMD module later
Pulling Response

Force vs Time Graph

Plot the instantaneous pulling force across simulation time to identify rupture events, peak force, resistance regions, and noisy transitions.

Force.xvgPeak forceRupture eventForce smoothing
Detailed graph module later
Free-Energy Profile

Potential of Mean Force Analysis

Construct and interpret a PMF profile from umbrella-sampling windows using WHAM, histogram overlap, convergence checks, and uncertainty estimation.

gmx whamPMFHistogram overlapBootstrap error
Detailed PMF module later
Secondary Structure

DSSP Secondary-Structure Analysis

Monitor time-dependent changes in α-helices, β-sheets, turns, bends, coils, and other secondary-structure assignments throughout the trajectory.

gmx dsspHelixβ-sheetTime-resolved map
Detailed DSSP module later
Residue Energetics

Per-Residue Energy Decomposition

Decompose MM/PBSA or MM/GBSA binding energy into residue-level contributions to identify stabilizing hotspots, unfavorable residues, and mutation targets.

ΔG residueHotspot residuesVan der WaalsElectrostatics
Detailed decomposition module later
Predictive Modeling

QSAR Analysis

Relate molecular descriptors and structural features to biological activity using validated statistical or machine-learning models for compound prioritization.

DescriptorsActivity modelingModel validationApplicability domain
Detailed QSAR module later
Recommended order:

Always complete trajectory processing and core stability analyses before advanced PCA, FEL, clustering, network, or binding-energy interpretation. For enhanced sampling, use SMD to generate and inspect the pulling pathway, then prepare umbrella-sampling windows before calculating a PMF with WHAM. Each future module can include exact GROMACS commands, input files, expected plots, troubleshooting, figure captions, Methods text, and manuscript-ready Results guidance. DSSP should be interpreted alongside RMSD and RMSF, per-residue decomposition should follow a validated MM/PBSA or MM/GBSA workflow, and QSAR should use an independently validated dataset, model, and applicability domain.

About the Original Tutorial Suite

The scientific intent, version notes, authorship, paper citation, and usage conditions from the uploaded source page remain visible.

Scientific Scope

The tutorials introduce GROMACS through a typical solvated protein, membrane systems, protein–ligand complexes, free-energy transformations, umbrella sampling, biphasic systems, and virtual sites. The original page describes GROMACS as free, open-source, and one of the fastest molecular-dynamics packages available.

The uploaded source notes that the tutorials assume GROMACS 2018 or newer, while some updated pathways require version 2025. Using a different version may produce commands, defaults, or outputs that do not behave exactly as shown.

Author & Citation

Original tutorials: Justin A. Lemkul, Ph.D., Associate Professor, Virginia Tech Department of Biochemistry.

J. A. Lemkul (2018), “From Proteins to Perturbed Hamiltonians: A Suite of Tutorials for the GROMACS-2018 Molecular Simulation Package, v1.0.”

Move from tutorial practice to guided research execution

AMRA-Lab can later connect each tutorial card to a structured premium lesson page with exact commands, reusable files, troubleshooting, analysis, and publication guidance.

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