Integrating DSSR into Jmol and PyMOL

Over the past couple of years, one of the most significant achievements of DSSR has been its integration into Jmol and PyMOL, two widely used molecular graphics programs. None of the projects had been ‘planned’, and I am honored to have the opportunities collaborating directly with Bob Hanson (Jmol) and Thomas Holder (PyMOL). The integrations make salient features of DSSR readily accessible to the Jmol and PyMOL user communities. Moreover, Jmol and PyMOL take different approaches to interoperate with DSSR, and so far they have employed separate features that the program has to offer.

Key features of DSSR

DSSR was implemented in strict ANSI C as a self-contained command-line program. The binaries for common operating systems (Mac OS X, Linux and Windows) are tiny (<1MB), and without runtime dependencies on third-party libraries. DSSR also comes with an extensive PDF user manual.

Since its initial release in early 2013, DSSR has been continuously refined/expanded based on user feedback and my improved knowledge of RNA structures. User questions are always promptly addressed on the public 3DNA Forum. Over the years, DSSR has gradually established itself as an accountable software product.

The small size, zero configuration, extensive features, and robust performance make DSSR ideal to be integrated into other bioinformatics tools.

DSSR and Jmol

From the very beginning, Jmol has been employing a web-service at Columbia University, where all DSSR analyses take place. In addition to the sample DSSR-Jmol web interface, DSSR is also directly accessible from the console (see Fig.1 below). Jmol includes a sophisticated SQL syntax to drill down the various DSSR-derived structure features. Search ‘DSSR’ on the Jmol/JSmol interactive scripting documentation for details.

DSSR is accessible in Jmol console via scripting Fig. 1 DSSR is available from the Jmol/JSmol console via scripting.

The initial version of the integration (Jmol v14.2) was facilitated by the DSSR --jmol option to produce a Jmol-specific (e.g., residue id [C]2658:A) plain text output. However, ad hoc text file are rigid and fragile for programs to communicate with. As DSSR had been evolving, changes to existing features or newly added functionality were known to break the established DSSR-Jmol interface. Having to write extra code to maintain the same old --jmol output did not feel right.

JSON (JavaScript Object Notation) came to the rescue! The current DSSR-Jmol integration (Jmol v14.4) takes advantage of JSON, a standard, lightweight data-interchange format. Since JSON is structured, parsing its contents is straightforward. DSSR and Jmol can evolve independently, as always, but they no longer need to worry about touching each other’s toes.

Overall, Jmol has incorporated the most fundamental analysis features of DSSR. The Jmol SQL mini-language is very powerful for selecting arbitrary DSSR parameters. Background information about this collaboration can be found in the blog post Jmol and DSSR.


So far, the DSSR-PyMOL integration has focused on visualization, i.e., the cartoon-block schematic representations of DNA/RNA structures. Moreover, instead of relying on a remote DSSR web-service as for Jmol, the PyMOL dssr_block command calls a locally installed DSSR executable for the job. As illustrated in the blogpost DSSR base blocks in PyMOL, interactively, the ‘dssr_block’ command makes it trivial to incorporate the highly effective rectangular blocks into PyMOL.

From early on, 3DNA includes the blocview script (first written in Perl, later converted to Ruby) to generate schematic images in the ‘best view’, by combining block representation of bases with backbone ribbon of proteins or nucleic acids. The script is essentially a glue, calling MolScript, Raster3D, ImageMagick, and several 3DNA utility programs to perform various tasks. With these dependencies, it’s a bit involved to set up blocview. Nevertheless, the resultant images are simple and revealing, and are still being used by NDB and RCSB PDB (among others) as of today.

DSSR does not depend on MolScript and Raster3D, or any other programs to generate .r3d output of rectangular blocks. The schematic blocks can be directly fed into PyMOL, combined with other representations, and ray-traced for high resolution images. The integration of DSSR into PyMOL by the dssr_block command is likely to prompt an even wider adoption of the cartoon-block representation. In this regard, it is well worth noting the news item “dssr_block is a wrapper for DSSR (3dna) and creates block-shaped nucleic acid cartoons” on the main page of PyMOLWiki (see Fig. 2 below). It will certainly bring this neat feature into the attention of many PyMOL users.

dssr_block news item on PyMOLWiki
Fig. 2 Screenshot of the PyMOLWiki main page (2016-01-27) with ‘dssr_block’ in the news. A sample cartoon-block image of 355d is inserted as an example.

Integration of DSSR analysis results into PyMOL is underway, using the same JSON output. Before long, PyMOL users should be able to have access to the numerous DNA/RNA structural features derived by DSSR as in Jmol, along with the cartoon-block images enabled by dssr_block. Background information about DSSR-PyMOL can be found in blog post Open invitation on writing a DSSR plugin for PyMOL.


  • The DSSR-Jmol and DSSR-PyMOL integrations are two salient examples of what can be achieved via direct collaboration of dedicated scientists with complementary expertise. In addition to benefit the involved projects in particular and the (structural biology) community at large, technical and scientific advances are more likely to be achieved.
  • Both projects are still on going, with continued refinements of existing functionality and additions of new features. As an example, it is desirable and likely that Jmol would allow local access to DSSR for efficiency and data privacy.
  • JSON is the way to go for connecting DSSR to the outside world. Period. The obsolete --jmol will be removed from the next release of DSSR (v1.5). The default plain text output is useful for easy comprehension and will stilled be maintained. But do not count on its exact format for computer parsing — occasional changes to existing items are likely, and new features are bound to be added.
  • If you’d like to incorporate DSSR into your pipeline and need some customizations of its output, please let me know. It’s always easier to set things right at the source than to fix them downstream. Where practical, I’ll try to implement your requested features, quickly. Working together, we can and will build a better world.




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