A ligand can sit securely inside a protein pocket, but the route it takes to leave may not be obvious from a static structure. For molecular modelers, that creates a practical challenge: how do you explore possible exit pathways without choosing a route in advance?
SAMSON’s Ligand Path Finder offers one way to investigate this problem. It searches for candidate unbinding pathways using ART-RRT: T-RRT for pathway search, ARAP modeling to generate ligand motion, and constrained minimization to adapt the protein as the ligand moves. The results are computational candidates to inspect—not a substitute for careful model preparation or interpretation.
Start with a model you can trust
Before searching, make sure the system is minimized. The tutorial uses Universal Force Field (UFF) for interaction evaluation and the FIRE state updater; it also specifies a FIRE step size of 1 fs and one step. These choices are part of the documented workflow, so they are useful starting settings when reproducing the example.
If you are working with your own protein, preparation matters. The documentation recommends removing alternate locations, water, and ions, adding hydrogens, and fixing the structure when needed. A search can only be as meaningful as the model and assumptions supplied to it.
For a first run, the sample system provides a concrete reference: lactose permease with the ligand thiodigalactosid (TDG). Its minimized bound conformation is named bound_minimized. Starting from a named conformation also makes the setup easier to review and repeat.
Three choices shape the search
1. Define the ligand clearly. Select the ligand atoms—in the sample, the group is named TDG—and set them in the app. The remaining atoms are treated as protein atoms. Confirm the atom count in Advanced information; this quick check can catch an incomplete selection before a long run.
2. Choose motion-control and anchor atoms. Active ARAP atoms control ligand motion, while passive ARAP atoms follow them. In the example, the sulfur atom S1 is active. Fixed ARAP atoms help prevent the protein from drifting along with the ligand; the sample uses a backbone CA atom from HIS 205. The fixed-atom choice can influence the pathways, so select atoms in regions expected to remain relatively static. The app’s Select buttons let you inspect assignments, and Reset lets you redo them.
3. Treat the sampling box as a hypothesis. The box defines the sampling region for active atoms. Its position and size bias the motion and therefore the paths the planner can find. In the sample, the box is set to favor motion toward the periplasmic side. Before running, check that the box covers the route you want to explore. Also orient the system thoughtfully: the search domain is Cartesian, so alignment affects how efficiently the box captures possible exits.
Make runs interpretable
For a reproducible search, enable Use seed and record the seed value. The seed increments after each run; if disabled, a random seed is used. The tutorial’s example uses two runs, 20 ARAP-modeling iterations, 20 constrained-minimization iterations, and a 1 Å RRT extension step. It also sets a 40 Å maximum ligand displacement. These are example settings, not universal values: the right search region and parameters depend on the model and the question being asked.
While the planner runs, monitor elapsed time, tree nodes, run number, and paths found under Planning information. You can pause and resume, or stop the search. This makes it easier to assess progress rather than treating the run as a black box.
Read the results as candidates
The Results tab lists paths and reports quantities such as the number of states, minimum and maximum energies, saddle, barrier, and search time. Select a path to display its energy curve, then move the slider to inspect conformations in the molecular model. Comparing multiple paths can help reveal how different candidate routes behave under the same setup.
Remember what these values represent: they describe the conformations and energies produced by this modeled search. A low or high entry in the table should be interpreted in the context of the force field, preparation, constraints, and sampling choices—not in isolation. You can export paths as trajectories, export conformations at a chosen interval, or copy table and energy data for further analysis. The documented next step for improving candidate paths is refinement with the P-NEB app.
For the complete setup, parameter descriptions, and export instructions, see the Ligand Path Finder tutorial.
Note: SAMSON and all SAMSON Extensions are free for non-commercial use. Get SAMSON.