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What is MD trajectory analysis?
MD trajectory analysis turns a simulation trajectory into measurements that can actually be interpreted: structural drift, residue flexibility, compactness, contact persistence, secondary-structure content, collective motions, and solvent-facing behavior. The raw frames coming out of GROMACS, AMBER, CHARMM, NAMD, or OpenMM do not answer those questions on their own.
This ProteinIQ tool wraps a workflow pinned to MDAnalysis 2.9.0. It is not a single upstream command-line program. It is a curated analysis surface built from MDAnalysis modules and a small amount of wrapper logic that standardizes inputs, runs multiple observables in one job, and returns structured outputs for charting and download.
The practical value is in combining observables that answer different failure modes:
- RMSD: Detects whether the selected atoms stay close to a chosen reference structure.
- RMSF: Shows which residues are mobile after aggregating atom-level fluctuations by residue.
- Radius of gyration: Tracks compaction or expansion over time.
- Distance tracking: Follows a specific geometric separation, often between domains, termini, ligands, or catalytic motifs.
- Hydrogen bonds and salt bridges: Measures persistence of stabilizing interactions.
- PCA and clustering: Describes dominant motions and recurring conformational states.
- DSSP, Ramachandran, chi angles, helix analysis: Connects motion to secondary structure and torsional states.
- SASA, RDF, density, water dynamics: Relates structural changes to solvent exposure and local environment.
Applications
- Fold stability checks: Compare early and late frames after simulations initialized from AlphaFold 2, Boltz-2, or ESMFold.
- Mutation analysis: Test whether a variant shifts flexibility, compaction, hydrogen-bond persistence, or helix geometry relative to the wild type.
- Binding-site monitoring: Track contact counts, hydrogen bonds, or a distance restraint around a ligand or interface during refinement.
- Ensemble characterization: Use PCA and clustering to summarize whether the trajectory samples one basin or several distinct states.
- Solvent-facing transitions: Use SASA, RDF, density, and water dynamics to examine collapse, exposure, or hydration changes.
How to use MD trajectory analysis online
Upload a topology file and a matching trajectory file, choose one or more analyses, and run the job to receive tabular and chart-ready outputs for each selected observable. The result page returns structural, interaction, conformational, environmental, and secondary-structure summaries with downloadable data for follow-up analysis.
Inputs
| Input | Description | Accepted formats | Max size |
|---|---|---|---|
Topology/Structure file | Defines atom identities, residue assignments, connectivity, and metadata needed to interpret trajectory coordinates. | .pdb, .gro, .psf, .prmtop, .top, .tpr | 50 MB |
Trajectory file | Stores coordinates for each sampled frame. The topology and trajectory must describe the same system and atom ordering. | .xtc, .trr, .dcd, .nc, .tng | 500 MB |
Common pairings include:
.gro+.xtcfor GROMACS.tpr+.xtcwhen topology metadata from GROMACS should be preserved.prmtop+.ncfor AMBER.psf+.dcdfor CHARMM or NAMD
How does MD trajectory analysis work?
The wrapper loads the uploaded files into an MDAnalysis Universe, applies the selected atom selection, resolves the reference mode, optionally aligns sampled frames to that reference, and then dispatches the requested observables.
Three details matter because they change interpretation:
- Reference mode:
first,last, andaverageare not cosmetic options.averagecomputes an average reference over the sampled frames instead of aliasing to the first frame. - Frame sampling:
stepsubsamples the trajectory globally for the audited analysis paths, which reduces runtime and directly changes temporal resolution. - Alignment: When enabled, sampled frames are superimposed onto the chosen reference before RMSD, RMSF, PCA, clustering, and cross-correlation calculations. This removes rigid-body translation and rotation and makes those outputs more about internal motion than bulk drift.
Some analyses rely on additional assumptions from the underlying MDAnalysis modules or the wrapper:
- Hydrogen bonds: The wrapper uses a donor-acceptor cutoff of
3.0 Åand angle cutoff of150°, matching the audited MDAnalysis default. Explicit hydrogens are still required for meaningful hydrogen-bond counts. - RMSF: MDAnalysis computes atom-level fluctuations. The wrapper then aggregates them by residue so the output is residue-oriented even when the selection contains more than one atom per residue.
- DSSP: Secondary-structure assignment uses
MDAnalysis.analysis.dsspwhen available. If that path fails, the wrapper falls back to a simpler internal estimate rather than aborting the whole job. - Water dynamics: This mode is available in the current wrapper, but it depends on water naming conventions and upstream MDAnalysis functionality that is being deprecated on the path to MDAnalysis 3.0.
Understanding the settings
Core settings
| Setting | Description | Default |
|---|---|---|
Analyses to run | Selects which observables are calculated. Multiple analyses can run in one job. | RMSD, RMSF, Radius of gyration |
Atom selection | MDAnalysis selection string applied to the primary analysis group. Examples include protein, protein and name CA, backbone, and resid 1-100. | protein and name CA |
Reference frame | Reference for RMSD-aligned analyses. Average structure computes the mean coordinate set over the sampled frames. | first |
Advanced settings
| Setting | Description | Default |
|---|---|---|
Frame step | Samples every nth frame. A value of 10 processes frames 0, 10, 20, ... instead of every saved frame. | 1 |
Align trajectory | Aligns sampled frames to the chosen reference before RMSD, RMSF, PCA, clustering, and cross-correlation analysis. | true |
Second atom selection | Secondary MDAnalysis selection used for distance tracking and RDF. | resname SOL and name OW |
PCA components | Number of principal components returned in PCA projections. | 3 |
Clusters | Number of k-means clusters used for conformational clustering. | 5 |
Density axis | Axis used for one-dimensional density profiles. | z |
Selection examples
| Selection string | Meaning |
|---|---|
protein | All atoms in standard amino-acid residues |
protein and name CA | One alpha carbon per residue, often used for coarse-grained structural tracking |
backbone | Backbone atoms N, CA, C, O |
resid 45-70 | Residues 45 through 70 |
protein and not name H* | Heavy atoms only |
resname ATP | All atoms in ATP residues, useful for ligand-focused measurements |
Understanding the results
The result page groups outputs into tabs. Not every selected analysis appears in every tab, so the most useful way to read the output is by question rather than by file format.
Structural outputs
| Analysis | Output fields | What it answers |
|---|---|---|
RMSD | frame, time_ps, rmsd_angstrom | Is the selected structure drifting away from the reference? |
RMSF | residue_id, residue_name, chain, rmsf_angstrom | Which residues fluctuate the most over the sampled frames? |
Radius of gyration | frame, time_ps, rg_angstrom | Is the selected structure compacting or expanding? |
End-to-end distance | frame, time_ps, distance_angstrom | Are termini or endpoints moving apart or together? |
Asphericity | frame, time_ps, asphericity | Is the shape becoming more elongated or more spherical? |
Moment of inertia | frame, time_ps, I1, I2, I3 | How is mass distribution changing along principal axes? |
Interaction outputs
| Analysis | Output fields | What it answers |
|---|---|---|
Hydrogen bonds | frame, time_ps, hbond_count; pair table with donor, acceptor, occupancy | Are stabilizing hydrogen-bond networks persistent? |
Salt bridges | frame, time_ps, salt_bridge_count; pair table with residue ids and occupancy | Are charged interactions forming or breaking over time? |
Contacts | frame, time_ps, n_contacts; pair table with occupancy | Is an interface tightening, loosening, or rearranging? |
Distance tracking | frame, time_ps, distance_angstrom | Is a specific geometric feature moving toward or away from another one? |
H-bond lifetime | lifetime distribution and summary statistics | Are hydrogen bonds brief, recurrent events or long-lived contacts? |
Conformational outputs
| Analysis | Output fields | What it answers |
|---|---|---|
PCA | frame, time_ps, pc1, pc2, pc3 plus explained variance arrays | What are the dominant collective motions? |
Clustering | per-frame cluster assignments and cluster statistics | How many recurring conformational states are populated? |
MSD | time-dependent displacement summary and diffusion coefficient | Is there translational diffusion or large-scale wandering? |
Dynamic cross-correlation | significant residue pairs and correlation coefficients | Which residue motions are coupled or anticorrelated? |
Persistence length | estimated persistence length and correlation decay | How stiff is a chain-like segment across the sampled trajectory? |
Secondary structure and environment outputs
| Analysis | Output fields | What it answers |
|---|---|---|
DSSP | per-frame helix, sheet, and coil percentages | Is secondary structure stable, gained, or lost? |
Ramachandran | residue-level mean and standard deviation for phi and psi | Which residues move into strained or alternative backbone states? |
Chi angles | residue-level mean and standard deviation for side-chain dihedrals | Are rotamers stable or switching between states? |
Helix analysis | helix ranges, rise, twist, and variability | Are helices remaining canonical or distorting? |
SASA | per-frame total SASA and per-residue SASA summary | Is the structure exposing or burying surface area? |
RDF | radial bins and g(r) values | How is local solvent or particle organization distributed around a selection? |
Density | position bins and density values along one axis | Is mass or solvent redistributed along a membrane or box axis? |
Water dynamics | residence-time summary statistics | How long do hydration waters remain near the selected region? |
Interpreting results
RMSD and RMSF
RMSD is easiest to misread when alignment and atom selection are not considered together.
- Low, stable RMSD after alignment usually indicates internal structural stability of the selected atoms.
- Low RMSD without alignment disabled can hide large rigid-body motion if the entire selection rotates or translates together.
- High RMSF in loops or termini is often expected.
- High RMSF inside a buried core helix or beta strand usually deserves inspection, especially when it appears alongside SASA growth or DSSP loss.
Distance, contacts, and hydrogen bonds
Distance tracking is strongest when paired with contacts or hydrogen bonds.
- Distance increases while contact count drops often indicates real separation rather than internal breathing.
- Stable distance with fluctuating contacts can mean the interface remains nearby but repacks locally.
- Hydrogen bonds near zero with an explicit warning usually means the uploaded structure lacks hydrogens, not necessarily that the system has no hydrogen bonding in reality.
PCA and clustering
PCA answers whether motion is dominated by a few directions. Clustering answers whether those motions produce recurring states.
- High PC1 variance with one dominant cluster suggests one major breathing or hinge motion inside one broad state.
- Several populated clusters with separated PC projections suggests discrete conformations rather than one continuous fluctuation cloud.
- Poorly separated clusters often mean the trajectory is either short, noisy, or not naturally state-separated under the chosen atom selection.
DSSP, SASA, and compactness
These metrics become more informative when read together.
- Rg decreases while SASA decreases usually indicates compaction.
- DSSP helix or sheet content falls while RMSF rises suggests local unfolding or disordering.
- SASA rises without major Rg change often reflects side-chain or surface rearrangement rather than global unfolding.
When to use MD trajectory analysis vs alternatives
MD trajectory analysis on ProteinIQ is a post-simulation interpretation tool. It is most useful after a trajectory already exists.
| Tool | Best use case | Not the right choice when |
|---|---|---|
MD Trajectory Analysis | Summarizing structure, interaction, and solvent observables from an existing MD run | No trajectory exists yet |
| OpenMM | Running or setting up molecular dynamics simulations | The simulation is already complete and only analysis is needed |
| gmx_MMPBSA | Estimating binding free energy from MD snapshots | The goal is structural interpretation rather than free-energy estimation |
| Ramachandran Plot | Inspecting backbone geometry from a single structure | Time-resolved trajectory behavior is needed |
| RMSD Calculator | Comparing one structure against another | A full time series across many frames is needed |
The main decision point is whether the question is dynamic or static:
- For one structure or one pairwise comparison, a simpler structure-analysis tool is usually enough.
- For questions about persistence, transitions, convergence, flexibility, or hydration over time, trajectory analysis is the correct layer.
Caveats that matter in practice
- Sampling frequency still limits interpretation: A frame saved every 10 ns cannot recover fast side-chain switching, no matter how many downstream analyses are run.
- Selection choice changes the science:
protein and name CAis useful for global fold tracking, but it can miss side-chain rearrangements and interaction chemistry. - Hydrogen-dependent analyses depend on protonation and topology quality: Missing hydrogens or inconsistent naming can suppress hydrogen-bond signals.
- Subsampling trades speed for detail: Larger
stepvalues reduce runtime and noise, but short-lived events may disappear. - Water dynamics is not future-proof upstream: The current wrapper still exposes it, but the underlying MDAnalysis path is being deprecated on the route to version 3.0.