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January 25, 2026The Journal of Chemical Physics4 citationsOpen Access

Visualizing the energy landscape for a molecular dynamics trajectory

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VNVilmos NeumanPWPatryk A. WesołowskiKBKrzysztof K. Bojarski

Key Points

  • The aim is to visualize energy landscapes from molecular dynamics trajectories using disconnectivity graphs.
  • Introduced an open-source program for data processing.
  • Applied Savitzky–Golay smoothing to thermodynamic traces.
  • Identified local extrema for minima and transition states.
  • Generated disconnectivity graphs without geometry optimization.
  • Processed large data sets efficiently on standard laptops.
  • The method captures explored structures and pathways in the energy landscape.
  • Analysis is compatible with all-atom and coarse-grained simulations.
  • Graphs provide interpretable summaries of conformational hierarchies with minimal postprocessing.
  • The workflow quickly processes 104–105 frames in seconds.

Abstract

We introduce an open-source program that converts molecular dynamics trajectories into disconnectivity graphs, providing a concise and interpretable visualization of the energy landscape that has been traversed. Our approach applies Savitzky–Golay smoothing to per-frame thermodynamic traces (potential energy in NVE/NVT or enthalpy in NPT ensembles) to identify local extrema as proxies for minima and transition states, and generates the necessary files for disconnectivity graph construction. This workflow requires no additional geometry optimization. The method is ensemble-agnostic and compatible with both all-atom and coarse-grained simulations. For some representative biochemical systems, it processes 104–105 frames in seconds on a standard laptop and produces an approximate representation of the underlying landscape topology. The resulting graphs capture the structures that are visited and pathways between them for a selected energy and time resolution, offering an interpretable structural summary of conformational hierarchies with minimal postprocessing. Because extrema are detected directly from the trajectory, the graphs reflect the organization of the explored region of the landscape on the molecular dynamics timescale. Our approach basically substitutes local minima and maxima from the smoothed time series as proxies for the true stationary points of the underlying landscape.

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Cite This Study

Neuman et al. (2026) studied this question.

synapsesocial.com/papers/6975b306feba4585c2d6e8edhttps://doi.org/10.1063/5.0310206
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