Plot Interaction Formation and Loss Distributions

Overview and Methodology

What it does

This tool visualizes the temporal distribution of interaction formation and loss events throughout a simulation. For each interaction type, such as hydrogen bonds, salt bridges, hydrophobic contacts, π-stacking, and cation–π interactions, it generates a bar plot showing when new contacts form and when existing ones disappear.

How it works

• Objective: Highlight the timing and frequency of transitions in interaction networks across the trajectory.
• Process:
  • Loads binary interaction matrices (e.g., hbonds_*.csv) generated by the ▶️ (Run First) Extract Pairwise Interaction from Trajectory tool.
  • Identifies formation events (transitions from 0 → 1) and loss events (transitions from 1 → 0) for all residue-residue interaction pairs.
  • For each time point (frame), counts the number of formation and loss events.
  • Displays this data as a time series bar plot, with gains plotted upward and losses plotted downward.

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Configuration and Inputs

Prerequisites

• Requires interaction CSVs generated using the same sel1_name and sel2_name from the extraction step.

Key configuration options

• Selection labels:

  • sel1_name, sel2_name: Must match the labels used during extraction. Used to locate interaction data files.

• Interaction mode:

  • interaction_mode: Must match the previous step (interchain + intrachain, interchain, or intrachain).

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Output

• Bar plots:

  • One plot per interaction type, such as:
    • hydrogen_bonds_transition_distribution.png
    • salt_bridges_transition_distribution.png
  • Each time point is represented by two bars:
    • Upward bar = number of formation events
    • Downward bar = number of loss events
  • Saved to the saved_results directory.

• Console output:

  • Reports file paths where each plot was saved.
  • Warns if interaction data is missing or no transitions are found.

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Interpreting the Results

• Formation vs. loss dominance:

  • If upward bars dominate, the system is building new contacts more frequently.
  • If downward bars dominate, contacts are breaking more often.

• Contact turnover dynamics:

  • Spikes in both formation and loss suggest rapid reorganization or transitions between states.
  • Quiet periods may indicate structural stability or equilibrium.

• Time-resolved patterns:

  • Early or late surges in transitions can reflect induced fit, binding events, or domain rearrangements.

• Comparison across types:

  • Running this tool across multiple interaction types reveals which contact classes are most dynamic.

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Example Scenarios

Detecting ligand-induced contact onset

• Scenario: A toxin binds to a voltage sensor domain during the first third of the simulation.
• Selections:
  • sel1 = 'segid VSD'
  • sel2 = 'resname TOX', sel2_is_ligand = True
• Observation:
  • A sharp peak in hydrogen bond and hydrophobic contact formation in the early frames.
• Interpretation:
  • Indicates initial binding event that stabilizes via specific contacts. May guide binding site refinement.

Monitoring contact dissolution during unbinding

• Scenario: A substrate gradually unbinds from a catalytic pocket.
• Selections:
  • sel1 = 'resid 100-130' (pocket)
  • sel2 = 'resname SUB'
• Observation:
  • Gradual increase in contact loss events, especially hydrogen bonds and π-stacking, over time.
• Interpretation:
  • Reflects disassembly of interaction network supporting the unbinding process.

Visualizing contact churn during domain rearrangement

• Scenario: Two protein domains explore multiple configurations over the trajectory.
• Selections:
  • sel1 = 'segid A'
  • sel2 = 'segid B'
• Observation:
  • Repeated alternating peaks in both gain and loss across all interaction types.
• Interpretation:
  • Suggests flexible interface with multiple metastable contact networks, characteristic of hinge or swivel motion.

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Usage Tips

• Loss Events:
  • Loss events are plotted as negative bars to distinguish them from formations; consider this when interpreting plot symmetry.

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