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Distance#

The Distance analysis measures how far apart two groups are along a path or trajectory. It is excellent for tracking contacts, binding-site opening and closing, domain motion, or the approach of two selected features.

Path Analyzer - Distance

Adding the plot#

  1. Open Path Analyzer.
  2. Choose Distance in Observable.
  3. Choose a Path.
  4. Define Group A and Group B.
  5. Choose a Distance type.
  6. Click Add Time Series or Add Histogram.

Inputs#

  • Two atom-containing selections are required.
  • The available distance types are:
  • Centroids
  • Minimum
  • Minimum along X
  • Minimum along Y
  • Minimum along Z
  • In Centroids mode, each group is reduced to its centroid, i.e. the simple average of all atom positions.
  • In the Minimum modes, Path Analyzer keeps the full atom sets and searches for the minimum pairwise separation instead of replacing the group by a single representative point.

Views#

  • Time series: follow the distance along the path.
  • Histogram: inspect the distribution of sampled distances.

Key equations#

For the centroid mode, the tracked signal is

\[ d_{\mathrm{centroid}}(t)=\|\mathbf{c}_A(t)-\mathbf{c}_B(t)\|,\qquad \mathbf{c}_A(t)=\frac{1}{|A|}\sum_{i\in A}\mathbf{r}_i(t) \]

For minimum-distance modes, Path Analyzer uses

\[ d_{\min}(t)=\min_{i\in A,\ j\in B}\|\mathbf{r}_i(t)-\mathbf{r}_j(t)\| \]

and the axis-specific variants replace the norm by \(|x_i-x_j|\), \(|y_i-y_j|\), or \(|z_i-z_j|\).

How to read it#

  • Centroids is a smooth, high-level descriptor for motion between two groups.
  • Minimum is a better choice when you care about closest contact rather than overall displacement.
  • Axis-specific minima help separate motion along one preferred direction.
  • Centroids uses a geometric average, not a center of mass.
  • This is different from Angle and Dihedral, where multi-atom groups are converted using centers of mass.

Tip

  • Use small selections when you want chemically specific contact tracking.
  • Use residues, domains, or chains when you want an interpretable coarse-grained signal.
  • Saved Distance analyses work very well as inputs to Custom scatter, 2D density map, or Energy landscape.