By following citations related to 3DNA/DSSR, I recently discovered the paper “Computational Insights into the Structural and Energetic Properties of an A/C stacked Three-Way DNA Junction” by Singh et al. (2025), published in the new journal Computational and Structural Biotechnology Reports. The study investigates the conformational dynamics, stability, and compactness of a DNA three-way junction (3WJ) through molecular dynamics (MD) simulations.

3WJs are the simplest and most common branched nucleic acids, consisting of three double-helical stems (A, B, and C), connected at a junction point. Two of these stems can be coaxially stacked, forming either an A/B-stacked or A/C-stacked structure. The Singh et al. study utilized the A/C-stacked 3WJ PDB entry 1snj as the starting point for their simulations. DSSR efficiently identifies the three stems and two helices, with one helix formed by the coaxial stacking of two stems.

The entire section '2.2. Conformational Analysis of the DNA Junction' from the Singh et al. paper has been quoted below. I am delighted to see 3DNA/DSSR referenced in this manner.

In this work, 10 snapshots were gathered at periodic intervals of 100 ns from the 1000.0 ns molecular dynamics simulation trajectory. We have utilized the X3DNA program [48,49,50] to analyze, recreate, and visualize three-dimensional nucleic acid structures. X3DNA is capable of both the antiparallel and the parallel double-helices, the single-stranded structures, the triplexes, the quadruplexes, as well as the other intricate tertiary motifs which is present within the DNA and the RNA structures. This analysis procedures classify and identify all the fundamental interactions and also categorize the suitable base-pair-steps double-helical properties. This program uses a reference frame for the explanation of the nucleic acid basepair geometry as well as a rigorous matrix-based approach to compute the local conformational- parameters and also reconstruct structure using these parameters. The helicoidal parameters and the torsion-angle parameters are essential in comprehending folding and the rotation of the bases during the dynamical pathway.

Although there are specialized software tools designed for analyzing MD trajectories, the features available in DSSR appear to be adequate for applications like those described in the Singh et al. paper. DSSR has no external dependencies, is easy to use, and provides a more detailed characterization of nucleic acid structures than other tools. Furthermore, it is actively maintained and supported. If you have any questions or feature requests, feel free to reach out—I am here to help!

For completeness, I’ve included the relevant parts from the DSSR User Manual in this post.

The DSSR --nmr (or --md) option automates the analysis of an ensemble, such as NMR structures in the PDB or snapshots from MD simulations. The input coordinates file must be in either the classic PDB format where each model is delineated by MODEL/ENDMDL tags, or the mmCIF format where each ATOM/HETATM record has an associated model number.

The --json option makes it easy to parse the output of multiple models pragmatically. In addition to NMR structures, trajectories from MD simulations can also be processed. Popular MD packages (AMBER, GROMACS, CHARMM, etc.) all have their own specialized binary formats for trajectories. By design, DSSR does not work on these binary files. They must be converted to the standard PDB or mmCIF format to be analyzed by DSSR. The combination of --nmr and --json makes DSSR directly accessible to the MD community.

See also the threads "Do I need gromacs to use dnaMD for simulations?"" and "Update of do_x3dna package" on the 3DNA Forum.

References

Singh,A. et al. (2025) Computational Insights into the Structural and Energetic Properties of an A/C stacked Three-Way DNA Junction. Computational and Structural Biotechnology Reports, 100055.