When working with proteins that undergo large conformational changes, a key challenge in simulating realistic transition paths is defining where and how atoms are allowed to move. In SAMSON’s Protein Path Finder, this is controlled by a critical setup step: defining the sampling box for the active ARAP atoms.
If you’ve ever run a conformational path search and found the resulting transitions to be unrealistic, too constrained, or simply not reaching the target conformation, your definition of the sampling region might be the limiting factor.
Why the Sampling Box Matters
The sampling box defines the spatial region in which active atoms — the ones responsible for driving protein movement — can explore during the transition. These active atoms are selected prior in the setup phase, often including key alpha-carbon atoms like CA in GLY 12 and CA in ARG 123 in the default example.
By default, the Protein Path Finder app initializes a generous sampling volume encompassing the protein in both start and goal conformations. But giving a thoughtful size and shape to this box can help refine the search space and encourage more physically plausible transitions.
Defining the Box
To define or customize the sampling region:
- In the app interface, expand the Set the sampling box for the active ARAP atoms section.
- A green cube will be shown in the viewport—this represents the current spatial limits.
- Adjust the dimensions to match your expectations or hypotheses. For example, the tutorial uses a cube of 200 Å per edge.
Too small? The atoms might hit artificial boundaries early in the search. Too big? The atoms might wander into less relevant areas, decreasing the efficiency and quality of the search.
Visual Feedback
The App automatically provides intuitive visual feedback on the sampling region. The green box in the viewport updates in real time, allowing you to immediately judge whether key motion directions are allowed.
By setting the box size to match biological knowledge or prior observations (e.g., NMR fluctuation envelopes, crystallographic B-factors, or domain movement ranges), you can bias the search in productive directions.
A Strategy for Better Paths
Mapping biologically relevant conformational landscapes requires more than just algorithms—it needs fitting constraints. Fine-tuning the sampling box lets you:
- Align search space with known domain motions
- Avoid unphysical deformations
- Balance sampling coverage versus performance cost
Together with a good choice of active atoms and search parameters, defining the right sampling box often makes the difference between a good-enough and a compelling path prediction.
SAMSON and all SAMSON Extensions are free for non-commercial use. Get it at https://www.samson-connect.net.