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Use-case guide

Molecular dynamics simulation workflows

Choose a molecular-dynamics method by resolution, sampling problem, perturbation, and intended observable.

Open method workflow

Steered molecular dynamics

Applies a time-dependent pulling restraint to probe forced transitions, unbinding paths, or mechanical response.

Coarse-grained molecular dynamics

Groups atoms into interaction sites to access larger systems and longer effective timescales.

Replica exchange molecular dynamics

Runs interacting replicas at different temperatures or Hamiltonians and periodically attempts exchanges.

Protein molecular dynamics simulation

Simulates a solvated protein with a classical force field to study stability, flexibility, and conformational change.

All-atom molecular dynamics

Represents individual atoms explicitly under an atomistic force field and integration scheme.

Enhanced sampling molecular dynamics

Uses biasing or generalized-ensemble methods to cross barriers that conventional trajectories rarely traverse.

What is molecular dynamics simulation?

Molecular dynamics simulation is a computer method for studying how atoms and molecules move and interact over time. It repeatedly calculates forces and updates particle positions to generate a time-ordered trajectory. Conventional protein and all-atom simulations preserve atomistic detail; coarse-grained models trade detail for scale; steered methods drive selected coordinates; replica exchange couples ensembles; and enhanced-sampling methods alter sampling to cross slow barriers.

Start with the scientific observable. Local contacts and hydration favor atomistic models; membrane organization or large assemblies may justify coarse graining; forced separation calls for steered MD; rugged equilibrium landscapes may motivate replica exchange; and a known slow coordinate can support metadynamics or umbrella sampling.

ProteinIQ directly runs conventional GROMACS and OpenMM workflows for supported protein systems. It does not currently execute coarse-grained, steered, replica-exchange, or enhanced-sampling protocols. Those spokes are explicitly post-run review workflows for compatible trajectories, with method-specific forces, exchanges, bias, reweighting, and convergence retained externally.

When to use molecular dynamics simulation

  • Study molecular motion. Examine stability, flexibility, interactions, transitions, and ensemble organization.
  • Test a physical hypothesis. Connect a defined system and protocol to a measurable structural or thermodynamic observable.
  • Preserve method boundaries. Keep conventional simulation, forced pathways, coarse-graining, replica exchange, and biasing distinct.

Choosing a molecular dynamics simulation type

Choose resolution first, then sampling strategy. All-atom and coarse-grained describe representation; steered MD describes a driven perturbation; replica exchange describes interacting ensembles; enhanced sampling is a broader family that includes several biasing and generalized-ensemble strategies.

A project can combine categories, but the name should stay precise. Replica exchange is an enhanced-sampling method, while an all-atom system may also be steered. Report both the representation and the sampling protocol instead of replacing one with the other.

How to run molecular dynamics simulation online

A defensible trajectory begins with a defined system and ends with convergence-aware analysis, not with a single RMSD plot.

  1. Define the observable. State the structural, kinetic, mechanical, or thermodynamic quantity the model should address.
  2. Prepare the system. Resolve assembly, atoms, protonation, ligands, parameters, solvent, ions, and boundaries.
  3. Choose the protocol. Match resolution, ensemble, duration, perturbation, replicas, or bias to the question.
  4. Run and monitor. Retain logs, energies, checkpoints, trajectories, warnings, and every independent start.
  5. Validate the ensemble. Test equilibration, convergence, replicate agreement, uncertainty, and sensitivity to analysis choices.

Molecular dynamics simulation applications

Molecular dynamics supports protein stability and flexibility analysis, interaction review, conformational hypotheses, membrane and assembly modeling, forced pathway generation, and free-energy calculations. The simulation type determines which of those outputs is scientifically available.

Trajectory length alone is not a quality metric. A shorter, replicated, well-parameterized study with declared uncertainty can support a stronger claim than one long trajectory whose system, ensemble, or slow coordinates are poorly controlled.

How to interpret molecular dynamics simulation

Every observable has a definition: alignment selection for RMSD, reference and units for distance, geometric criteria for contacts, statistical weights for biased ensembles, and state reconstruction for replica exchange. Preserve those definitions with the result.

Distinguish sampled behavior from experimental truth. Force fields and coarse-grained models are approximations, trajectories are finite, driven simulations are nonequilibrium, and enhanced-sampling results require method-specific statistical treatment.

Benefits of molecular dynamics simulation

  • Time-resolved models. Connects molecular structure to motion, interactions, and ensemble behavior.
  • Multiple physical scales. Supports atomistic detail, coarse-grained organization, forced response, and advanced sampling.
  • Inspectable evidence. Preserves trajectories, settings, energies, logs, and analysis definitions.

Limitations of molecular dynamics simulation

  • Finite sampling. Slow states and transitions may remain unobserved even in long trajectories.
  • Model dependence. Force fields, mapping, parameters, solvent, and protonation affect results.
  • Protocol-specific claims. Driven and biased trajectories require specialized interpretation and cannot be treated as conventional equilibrium MD.

How the featured workflow works

The hub workflow prepares one protein structure with PDB Fixer and branches into independent GROMACS and OpenMM configurations.

  1. Define question. Specify the observable, system, resolution, ensemble, and required timescale.
  2. Prepare structure. Review assembly, missing atoms, protonation, ligands, cofactors, solvent, and ions.
  3. Configure engines. Set independent GROMACS and OpenMM force-field and ensemble choices.
  4. Run simulations. Retain trajectory, energy, topology, logs, warnings, and checkpoints.
  5. Compare evidence. Assess equilibration, structural observables, uncertainty, and replicate behavior.

Inputs and outputs for the featured workflow

Check formats before running, then inspect and download the result from every workflow step.

Inputs

Molecular system

PDBmmCIFSDFMOL2

Prepared protein or protein–ligand coordinates with compatible parameters and system conditions.

Outputs

Simulation evidence

XTCPDBEDRTPRCSVZIP

Engine-native trajectories, energies, topologies, coordinates, analyses, logs, and archives.

On this page

  • What is molecular dynamics simulation?
  • Choosing a molecular dynamics simulation type
  • How to run molecular dynamics simulation online
  • Molecular dynamics simulation applications
  • How to interpret molecular dynamics simulation
  • Benefits of molecular dynamics simulation
  • Limitations of molecular dynamics simulation
  • How it works
  • Inputs & outputs

Featured molecular dynamics simulation workflow

Keep the two simulation engines and their native outputs separate for method-aware review.

Molecular dynamics simulation method panelWorkflow preview

Inputs

1 required

Methods

3 connected

  1. 01PDB Fixer
  2. 02GROMACS
  3. 03OpenMM

Keep the two simulation engines and their native outputs separate for method-aware review.

Use this template

Tools for molecular dynamics simulation

Use these methods to prepare inputs, run the core analysis, inspect outputs, and validate the evidence described in this workflow.

GROMACS

GROMACS

Run conventional protein molecular dynamics with classical force fields

protein-analysisphysics-based+2
OpenMM

OpenMM

Run GPU-accelerated all-atom protein or protein–ligand simulations

protein-analysisphysics-based+4
MD Trajectory Analysis

MD Trajectory Analysis

Analyze compatible trajectories with structural and dynamical metrics

structure-analysisphysicochemical-properties+2
PDBFixer

PDBFixer

Repair missing atoms and standardize structures before simulation

structure-analysisquality-validation+3
PDB2PQR

PDB2PQR

Prepare protonation, charges, and radii for structural review

format-conversionprotein+4
PROPKA 3

PROPKA 3

Estimate pKa values and inspect protonation-sensitive sites

protein-analysisproperty-prediction+3
RMSD calculator

RMSD calculator

Compare representative structures with RMSD

structure-analysiscomparison+2
Radius of gyration

Radius of gyration

Measure compactness for representative structures

structure-analysisphysicochemical-properties+2
pyRMSD

pyRMSD

Calculate pairwise RMSD matrices for exported structure ensembles

structure-analysiscomparison+3
DSSP

DSSP

Assign secondary structure to representative protein conformations

structure-analysisprotein+1
SASA calculator

SASA calculator

Calculate solvent-accessible surface area for exported structures

structure-analysisprotein+1
MolProbity

MolProbity

Validate representative protein conformations

structure-analysisquality-validation+4

Frequently asked questions

The maintained use cases here are conventional protein MD, all-atom MD, coarse-grained MD, steered MD, replica exchange MD, and enhanced-sampling MD. Representation and sampling strategy overlap, so a study may require more than one label.

Choose from the observable backward. Use atomistic models for local interactions, coarse graining for larger scales, steered MD for driven response, replica exchange for ensemble mixing, and a justified enhanced-sampling method for a defined barrier or free-energy question.

ProteinIQ currently runs conventional protein and all-atom simulations through supported GROMACS and OpenMM configurations. The steered, coarse-grained, replica-exchange, and enhanced-sampling pages provide honest post-run trajectory review workflows, not simulations relabeled as those methods.

Long enough to support the slow observable behind the claim, with independent starts and convergence evidence. There is no universal duration. ProteinIQ’s current GROMACS configuration supports 1–200 ns per run, but adequate scientific sampling may require multiple runs or an advanced external protocol.

Export original and prepared structures, complete topology and parameters, software versions, ensemble settings, seeds, logs, energies, checkpoints, trajectories, analysis definitions, and replicate-level results.

A complete molecular dynamics simulation project is commonly quote-based because system preparation, parameterization, sampling length, replica count, analysis, and interpretation vary substantially. Current published examples span from $50 for a bounded 100 ns GROMACS simulation to a $5,000 minimum for a dedicated commercial molecular-dynamics engagement.

Those prices describe materially different deliverables, so compare the included preparation, validation, replicates, analysis, raw files, interpretation, and support—not only trajectory length. Membrane building, unusual residues or ligands, advanced sampling, and convergence assessment can dominate the real scope.

ProteinIQ self-service starts at $29 per month for academic Plus and $99 per month for commercial Pro, with the configured run estimated in credits before submission. Done-for-you molecular dynamics work is scoped separately when preparation, method design, external advanced sampling, or interpretation is required.

Start with a workflow you can inspect and edit

Add your inputs, review the settings, and keep every structure, score, table, and file connected to the step that produced it.

Open method workflow
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