DSSR-Jmol paper in NAR

[xiangjun]

I am pleased to announce the (advance online, May 3, 2017) publication of a new paper titled ["DSSR-enhanced visualization of nucleic acid structures in Jmol"](https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkx365) in *Nucleic Acids Research* (NAR). Co-authored by Robert Hanson (Jmol) and me (DSSR), the article will appear in the July 2017 web-server issue of NAR. Here are the key links related to the paper:

* [DSSR-Jmol website](http://jmol.x3dna.org/)
* [PDF version (DSSR-Jmol paper)](https://academic.oup.com/nar/article-pdf/doi/10.1093/nar/gkx365/14134996/gkx365.pdf)
* [Online HTML (DSSR-Jmol paper)](https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkx365)
* [DSSR-Jmol manual](http://jmol.x3dna.org/dssr-jmol-manual.pdf)
* [Materials to reproduce reported results](http://forum.x3dna.org/dssr-jmol-integration/)

The DSSR-Jmol integration project was initiated in October 2013 when I approached Bob at a meeting organized by RCSB PDB at Rutgers. Thereafter, we met only once in July 2014 in Paris. Over the years, we have mostly communicated via email, occasionally facilitated by Skype. Our work bridges the DSSR command-line analyzing tool and the Jmol molecular viewer together via a simple JSON interface and a powerful query language. Users can now select DSSR-derived RNA structural features (such as base pairs, double helices, and various loops) as easily as they can select protein alpha-helices and beta-strands. Moreover, fine-grained characteristics of these features can be queried via Jmol SQL for DSSR (see examples below). Notably, the novel representation styles (step diagram and base blocks) and coloring schemes bring RNA visualization to an entirely new level (see [Figure 3 of the paper](http://forum.x3dna.org/dssr-jmol-integration/figure-3)).

Code: Bash

1.     load =1ehz/dssr   # load yeast phenylalanine tRNA to Jmol with DSSR annotation
2.     SELECT hairpins   # select the three hairpin loops
3.     SELECT junctions  # select the four-way junction loop
4.     select within(dssr, "nts WHERE is_modified")  # select modified nucleotides (14 total)
5.     SELECT within(dssr, "pairs WHERE name != 'WC'")  # select non-Watson-Crick pairs
6.     SELECT within(dssr, "pairs WHERE name = 'WC' OR name = 'Wobble'")  # select canonical pairs
7.     Select within(dssr, "pairs WHERE name != 'WC' AND name != 'Wobble'")  # select non-canonical pairs
8.     SELECT within(dssr, "pairs WHERE LW = 'tSW'")  # select pairs of type tSW per Leontis-Westhof

The DSSR-Jmol integration fills a gap in RNA structural bioinformatics, serving a huge user base of researchers, educators, and students alike. Its functionality is freely accessible either via the **Jmol application**, or the **JSmol-based website** (http://jmol.x3dna.org). By adhering to web standards, the website is fully functional in all modern browsers on various computer/operating systems (including handheld devices, such as tablets and smart phones). The web interface is simple and intuitive, and new users can get started easily. It also allows power users to take full advantage of Jmol scripting via a command-line console.

This work also provides an example for integrating DSSR-derived features into other molecular graphics programs or bioinformatics pipelines involving nucleic acid structures. By design, DSSR is a stand-alone, command-line program written in ANSI C. The binary executables are only ~1MB in size, and *self-contained*. With zero dependencies, no setup or configuration, it is trivial to get DSSR up and running. DSSR uncovers a wide range of RNA/DNA structural features in a consistent, easily accessible framework. It possesses a much richer set of functionalities for nucleic acid structural analysis (see the [DSSR User Manual](http://x3dna.bio.columbia.edu/docs/dssr-manual.pdf)) than any other existing tools I am aware of. Moreover, the program is efficient and robust, making it an ideal component to be integrated into other pipelines, especially via the standard and structured **JSON** interface.

Collaborating with Bob has been a truly exciting experience. The NAR-web publication represents a gratifying intermediate result along an on-going journey. Hopefully, others (may be some of you) can join us in pushing forward the field of RNA structural bioinformatics.

Best regards,

Xiang-Jun