Modernizing the 3DNA/DSSR Ecosystem: Welcome to Our New GitHub Home
Over the past two decades, the 3DNA and DSSR software ecosystem has grown alongside the structural biology community. What began in 2003 with the classic 3DNA suite has evolved into DSSR—our automated engine for dissecting the spatial structure of RNA—and most recently into wDSSR, our registration-free web platform for 3D nucleic acid analysis and modeling.
As part of our ongoing efforts under the X3DNA-DSSR National Resource (supported by NIH/NIGMS grant R24GM153869), we are transitioning our development workflow and community support to modern, open infrastructure on GitHub.
A New GitHub Organization: x3dna-dssr
We have centralized our software repositories, plugins, and web resources under an official GitHub organization:
https://github.com/x3dna-dssr
This organization serves as the primary home for:
- wDSSR (Shuxiang Li): The official repository for our web interface, tracking front-end enhancements, feature roadmaps, and server releases.
- DSSR-PyMOL: (Eric Chen and Bener Dulger) an integrated PyMOL plugin that bridges 3D structural analysis, stylized cartoon block modeling, and an interactive pure-Python RNA 2D layout studio. Powered by DSSR (Dissecting the Spatial Structure of RNA), the plugin allows structural biologists to explore, identify, select, and edit secondary/tertiary nucleic acid features seamlessly in real time.
- Historical Source Code Archives: Preserving foundational codebases—including SCHNAaP/SCHNArP, 3DNA v1.5 (accompanying the 2003 NAR paper), and 3DNA v2.4—for long-term reproducibility.
Retiring the 3DNA Forum & Transitioning to GitHub Discussions
Since December 2011, the self-hosted 3DNA Forum (forum.x3dna.org) has been the primary venue for user support, troubleshooting, and scientific exchanges. Over nearly 15 years, our community has expanded to 5,918 members, generating 958 topics and 3,770 posts.
While the forum has served us well, maintaining a legacy Simple Machines Forum (SMF) board has become increasingly unsustainable due to broken SMTP email relays and relentless automated bot registrations.
To provide a modern, frictionless experience, community discussions and user support have moved to GitHub Discussions:
https://github.com/orgs/x3dna-dssr/discussions
Benefits of the New Discussion Platform
- No Separate Registration: Anyone with a GitHub account can participate immediately—no manual account approvals or verification delays.
- Reliable Email Notifications: Subscribe to threads or categories to receive immediate updates when someone replies.
- Native Markdown & Formatting: Easily paste command outputs, syntax-highlighted scripts, and inline mathematical notation.
- Seamless Screenshots: Drag and drop or paste images directly into posts to illustrate structural questions and bug reports.
The 3DNA Forum Is Now a Permanent Read-Only Archive
All 958 historical topics and 3,770 posts remain permanently online and searchable at forum.x3dna.org. To eliminate spam registrations and administrative overhead, new postings and account creations have been disabled, but no historical knowledge has been removed.
Key Community Resources
Whether you are looking for web-based analysis or downloads, here is where to find our core tools:
- Web Interface (wDSSR): web.x3dna-dssr.org
Analyze, Rebuild, Model, Circularize, Mutate, Assemble, and Visualize 3D nucleic acids directly in your browser without registration.
- Community Q&A & Support: github.com/orgs/x3dna-dssr/discussions
Ask questions, report edge cases, and share feature ideas across the entire tool suite.
- Legacy Downloads (DSSR v1.9.10): docs.x3dna-dssr.org/download.php
Freely accessible binaries accompanying our 2020 NAR DSSR-PyMOL publication.
- Software Releases & Legacy Downloads: github.com/x3dna-dssr
Access software distributions, including standalone binaries DSSR v1.9.10 (accompanying our 2020 NAR DSSR-PyMOL publication), 3DNA v2.4, 3DNA v1.5, and foundational SCHNAaP/SCHNArP packages.
Acknowledgements
We express our gratitude to every researcher, student, and collaborator who contributed questions, shared datasets, and reported edge cases on the 3DNA Forum over the past 15 years. Your feedback has directly guided the evolution of 3DNA and DSSR.
We invite you to star our repositories, join our discussions on GitHub, and help us shape the next generation of nucleic acid structural bioinformatics tools!
Standardized Annotation of CASP16 RNA Predictions Using DSSR
Overview & Background
The 16th Critical Assessment of Structure Prediction (CASP16) evaluated blind predictions for both monomeric RNAs and RNA–RNA multimeric complexes. In a study published in Bioinformatics, Chandran Nithin, Smita P. Pilla, and Sebastian Kmiecik (Laboratory of Computational Biology, University of Warsaw) examined their group's (LCBio, group G189) CASP16 submissions—which ranked first in the official CASP16 best-of-submitted-models assessment for RNA–RNA multimers—to diagnose where modeling accuracy degrades across the RNA structural hierarchy. Rather than relying solely on global superposition metrics (TM-score, RMSD), the authors established an automated evaluation pipeline centered on DSSR (Dissecting the Spatial Structure of RNA; Lu et al., 2015) to benchmark local, modular, and tertiary structural features.
Methodological & Parameter Details
To ensure objective comparisons between experimental reference structures and predicted 3D models, the authors relied on DSSR for consistent feature extraction:
Structural features were extracted from both reference and predicted RNA structures using DSSR (Lu et al. 2015) to ensure consistent annotation across all models.
As detailed in Supplementary Methods S3.2:
All structural features used in the analysis were derived from reference and predicted RNA structures using DSSR, which provided a standardized annotation of base pairs, stacking interactions, secondary structure elements, junctions, and tertiary motifs.
Using DSSR outputs, the authors computed F1-scores across key structural tiers:
- Base Pairs: Canonical Watson–Crick pairs were evaluated by strict residue correspondence. Non-Watson–Crick (nWC) pairs were scored on a 6-point rubric based on DSSR's Leontis–Westhof classifications (residue identity,
cis/trans orientation, and interacting edges).
- Base Stacking: Pairwise contacts from DSSR-annotated stacking segments were scored using residue identity, inter-planar distance (≤ 0.5 Å deviation), and base-ring normal angles (≤ 15° deviation).
- Secondary Structure & Junctions: Secondary structure elements—including hairpins, bulges, internal loops, and both helices (defined by DSSR via base-stacking interactions regardless of pairing type or backbone continuity) and stems (helices consisting strictly of canonical Watson–Crick/wobble pairs with a continuous backbone)—were matched at ≥ 50% residue overlap. Multi-helix junctions were evaluated via a topology-gated framework assessing branch count, helix connectivity, terminal base pairs, unpaired linkers, and coaxial stacking.
- Tertiary Motifs & Interfaces: A-minor interactions, ribose zippers, K-turns, kissing loops, pseudoknots, and multiplets were scored by residue overlap, while multimer interfaces were quantified by inter-chain base-pair recovery.
Step-by-Step Workflow
- Consensus 2D Restraints: Secondary structures were predicted using thermodynamic, probabilistic, pseudoknot-capable, and alignment-based tools (
RNAfold, RNAstructure, CentroidFold, IPknot, RNAalifold, ScanFold 2.0), then combined into dot-bracket restraints.
- 3D Modeling & Refinement: Monomers were generated via deep learning (
AlphaFold 3, DeepFoldRNA, RhoFold+, NuFold, trRosettaRNA) and physics/fragment-based tools (SimRNA, FARFAR2, RNAComposer, Vfold2, BriQ), refined with QRNAS, and filtered for entanglements with RNAspider.
- Multimer Assembly: Higher-order complexes were modeled by screening
AlphaFold 3 across candidate stoichiometries and ionic/cofactor conditions, supplemented by manual assembly in PyMOL.
- DSSR Benchmarking: Representative models were processed with
DSSR alongside experimental references to quantify feature recovery (F1-scores) across the structural hierarchy.
Conclusion & Paper References
Using DSSR's standardized annotations, Nithin et al. showed that while current prediction pipelines reliably recover Watson–Crick base pairs (monomer F1 ≈ 0.84), accuracy drops sharply for non-canonical pairs, stacking geometry, multi-helix junctions, and tertiary motifs—errors that compound across RNA–RNA multimer interfaces.
- Primary Publication: Nithin, C., Pilla, S. P., & Kmiecik, S. (2026). Hierarchical breakdown of RNA structure prediction in CASP16: from reliable local helices to speculative multimer assembly. Bioinformatics, 42(10), btag689. https://doi.org/10.1093/bioinformatics/btag689
- DSSR: Lu, X.-J., Bussemaker, H. J., & Olson, W. K. (2015). DSSR: an integrated software tool for dissecting the spatial structure of RNA. Nucleic Acids Research, 43(21), e142. https://doi.org/10.1093/nar/gkv716
Recently, PDB begins to release atomic coordinates of large (ribosomal) structures in mmCIF format. For nucleic-acid-containing structures, the largest one so far is 4v4g, the crystal structure of five 70S ribosomes from Escherichia coli in complex with protein Y. It is assembled from ten PDB entries (1voq, 1vor, 1vos, 1vou, 1vov, 1vow, 1vox, 1voy, 1voz, 1vp0), consisting of 22,345 nucleotides, and a total of 717,805 atoms.
This humongous structure poses no problems to DSSR at all, as shown below.
Command: x3dna-dssr -i=4v4g.cif -o=4v4g.out
Processing file '4v4g.cif' [4v4g]
total number of base pairs: 9277
total number of multiplets: 918
total number of helices: 1099
total number of stems: 1221
total number of isolated WC/wobble pairs: 603
total number of atom-base stacking interactions: 1736
total number of hairpin loops: 504
total number of bulges: 170
total number of internal loops: 775
total number of junctions: 214
total number of non-loop single-stranded segments: 429
total number of kissing loops: 5
total number of A-minor (type I and II) motifs: 100
total number of ribose zippers: 58 (1159)
total number of kink turns: 39
Time used: 00:00:10:45
It took less than 11 minutes to run on an iMac (and nearly 14 minutes on a Ubuntu Linux machine). Given the
With great pleasure, I read the following annoancement from Rajendra Kumar on the 3DNA Forum:
Re: do_x3dna: a tool to analyze DNA/RNA in molecular dynamics trajectories
« Reply #1 on: Today at 10:53:31 AM »
Hello,
I have now made a new website for do_x3dna
(http://rjdkmr.github.io/do_x3dna). This website contains detailed
documentation for do_x3dna program and Python APIs.
Documentation for Python API is now available
(http://rjdkmr.github.io/do_x3dna/apidoc.html).
Few tutorials about the Python APIs are also now available
(http://rjdkmr.github.io/do_x3dna/tutorial.html).
Thanks.
With best regards,
Rajendra
Browsing through the do_x3dna website, I am impressed by the extensive documentation and tutorial. Clearly, do_x3dna has pushed the boundaries (in applicability and documentation) of the x3dna_ensemble Ruby script distributed with 3DNA v2.1.
As noted in GitHub page, do_x3dna has been developed to analyze fluctuations in DNA or RNA structures in molecular dynamics (MD) trajectories. It can be used for GROMACS MD trajectories, as well as those from NAMD and AMBER. It leaves no doubt that do_x3dna will boost 3DNA’s applications in the increasingly active field of DNA/RNA MD simulations.
From early on, 3DNA and DSSR have native support of modified nucleotides. The currently distributed baselist.dat file with 3DNA contains over 700 entries. As of v1.1.4-2014aug09, a new section has been added to DSSR to list explicitly the modified nucleotides in an analyzed structure.
Using the 76-nucleotide long yeast phenylalanine tRNA (1ehz) as an example, the pertinent section in DSSR output is as below.
List of 11 types of 14 modified nucleotides
nt count list
1 1MA-a 1 A.1MA58
2 2MG-g 1 A.2MG10
3 5MC-c 2 A.5MC40,A.5MC49
4 5MU-t 1 A.5MU54
5 7MG-g 1 A.7MG46
6 H2U-u 2 A.H2U16,A.H2U17
7 M2G-g 1 A.M2G26
8 OMC-c 1 A.OMC32
9 OMG-g 1 A.OMG34
10 PSU-P 2 A.PSU39,A.PSU55
11 YYG-g 1 A.YYG37
So 1ehz has 14 modified nucleotides of 11 different type, as listed in the following rows after the header line. The meaning of each column should be obvious. For example, the third row means that 5MC (5-methylcytidine, abbreviated as 'c' in 1-letter code) occurs twice, identified as A.5MC40 and A.5MC49, respectively.
With the 3-letter id, one can search the RCSB ligand database for more information about a specified modified nucleotide. The URL would be like this, using pseudouridine (PSU) as an example, https://www.rcsb.org/ligand/PSU.
It is hoped that the newly added section, put at the very top of DSSR output, will draw more attention to modified nucleotides.
From v1.1.3-2014jun18, DSSR has an additional output of RNA secondary structures in BPSEQ format. A sample file for PDB entry 1msy is shown below.
![1msy [GUAA tetra loop] in 3d and 2d representations](http://forum.x3dna.org/images/1msy-3d-2d.png "1msy [GUAA tetra loop] in 3d and 2d representations")
Filename: dssr-2ndstrs.bpseq
Organism: DSSR-derived secondary structure [1msy]
Accession Number: DSSR v1.1.4-2014aug09 (xiangjun@x3dna.org)
Citation: Please cite 3DNA/DSSR (see http://x3dna.org)
1 U 0 # name=A.U2647
2 G 26 # name=A.G2648, pairedNt=A.U2672
3 C 25 # name=A.C2649, pairedNt=A.G2671
4 U 24 # name=A.U2650, pairedNt=A.A2670
5 C 23 # name=A.C2651, pairedNt=A.G2669
6 C 22 # name=A.C2652, pairedNt=A.G2668
7 U 0 # name=A.U2653
8 A 0 # name=A.A2654
9 G 0 # name=A.G2655
10 U 0 # name=A.U2656
11 A 0 # name=A.A2657
12 C 17 # name=A.C2658, pairedNt=A.G2663
13 G 0 # name=A.G2659
14 U 0 # name=A.U2660
15 A 0 # name=A.A2661
16 A 0 # name=A.A2662
17 G 12 # name=A.G2663, pairedNt=A.C2658
18 G 0 # name=A.G2664
19 A 0 # name=A.A2665
20 C 0 # name=A.C2666
21 C 0 # name=A.C2667
22 G 6 # name=A.G2668, pairedNt=A.C2652
23 G 5 # name=A.G2669, pairedNt=A.C2651
24 A 4 # name=A.A2670, pairedNt=A.U2650
25 G 3 # name=A.G2671, pairedNt=A.C2649
26 U 2 # name=A.U2672, pairedNt=A.G2648
27 G 0 # name=A.G2673
Based on online sources, BPSEQ has originated from the Comparative RNA Web site developed by the Gutell lab. CRW files contain four header lines, describing the file name, organism, accession number, and a general remark. Thereafter, there is one line per base in the molecule, listing the position of the base (starting from 1), the one-letter base name (A,C,G,U etc), and the position number of the base to which it is paired. If the base is unpaired, zero (0) is put in the third column. In the above sample BPSEQ file derived from DSSR, detailed information about the base and its paired base (if any) comes after the # symbol.
Compared to dot-bracket notation (dbn) and connect-table (.ct) format, BPSEQ is simpler but less expressive. Nevertheless, the format is well-supported in bioinformatic tools on RNA secondary structures. It only seems fitting that DSSR now produces secondary structures in .bpseq (with default file name dssr-2ndstrs.bpseq), in addition to .dbn and .ct. Technically, adding the BPSEQ output to DSSR is trivial given the infrastructure already in place.
From early on, DSSR-derived RNA secondary structures in dot-bracket notation (dbn) have taken pseudoknots into consideration. Nevertheless, in DSSR releases prior to v1.1.3-2014jun18, the dbn output had been simplified to the first level only, with matched []s, even for RNA structures with high-order pseudoknots. RNA pseudoknot is a (relatively) complicated issue, and I’d planned to put off the topic until DSSR is well-established.
In early May, I noticed the Antczak et al. article RNApdbee—a webserver to derive secondary structures from pdb files of knotted and unknotted RNAs. I was delighted to read the following citation:
In order to facilitate a more comprehensive study, the webserver integrates the functionality of RNAView, MC-Annotate and 3DNA/DSSR, being the most common tools used for automated identification and classification of RNA base pairs.
Even before any paper on DSSR has been published, the software has already be ranked in the top three for the identification and classification of RNA base pairs! Well familiar with RNAView and MC-Annotate, I am glad to see DSSR is now listed on a par with them. Note that DSSR has far more functionality than just identifying and classifying RNA base pairs.
Further down the RNApdbee paper, especially in Figure 2, I found the following remarks regarding DSSR’s capability on RNA structures with high-order pseudoknot.
An arc diagram to represent the secondary structure of 1DDY (chain A) generated by R-CHIE upon the dot-bracket notation. Arcs of the same colour define a paired region. Crossing arcs reflect a conflict observed between the corresponding regions. (a) RNApdbee recognizes pseudoknots of the first (dark green) and second (navy blue) order. (b) 3DNA/DSSR improperly classifies base pairs (within residues in red) and the structure is recognized as the first-order pseudoknot.
The above citation and the question Higher-order pseudoknots in DP output (from Jan Hajic, Charles University in Prague) on the 3DNA Forum prompted me to further refine DSSR’s algorithm for deriving secondary structures of RNA with high-order pseudoknots. The DSSR v1.1.3-2014jun18 release made this revised functionality explicit. For the above cited PDB entry 1ddy, the relevant output of running DSSR on it would be:
Running command: "x3dna-dssr -i=1ddy.pdb"
****************************************************************************
This structure contains 2-order pseudoknot(s)
****************************************************************************
Secondary structures in dot-bracket notation (dbn) as a whole and per chain
>1ddy nts=140 [whole]
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA&GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA&GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA&GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((.{[[....[[)))...].].}.]]..&......(((.{[[....[[)))...].].}.]]..&......(((.{[[....[[)))...].].}.]]..&......(((.{[[....[[)))...].].}.]]..
>1ddy-A #1 nts=35 [chain] RNA
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((.{[[....[[)))...].].}.]]..
>1ddy-C #2 nts=35 [chain] RNA
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((.{[[....[[)))...].].}.]]..
>1ddy-E #3 nts=35 [chain] RNA
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((.{[[....[[)))...].].}.]]..
>1ddy-G #4 nts=35 [chain] RNA
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((.{[[....[[)))...].].}.]]..
Note that the whole 1ddy entry contains four RNA chains (A, C, E, and G), and DSSR can handle each properly. So at least from DSSR v1.1.3-2014jun18, the following statement is no longer valid:
3DNA/DSSR improperly classifies base pairs (within residues in red) and the structure is recognized as the first-order pseudoknot.
A closely related issue is knot removal, a topic nicely summarized by Smit et al. in their publication From knotted to nested RNA structures: A variety of computational methods for pseudoknot removal. While not explicitly documented, the --nested (abbreviated to --nest) option has been available since DSSR v1.1.3-2014jun18. This option was first mentioned in the release note of DSSR v1.1.4-2014aug09. Again, using PDB entry 1ddy as an example, the relevant output of running DSSR with option --nested is as follows:
Running command: "x3dna-dssr -i=1ddy.pdb --nested"
****************************************************************************
This structure contains 2-order pseudoknot(s)
o You've chosen to remove pseudo-knots, leaving only nested pairs
****************************************************************************
Secondary structures in dot-bracket notation (dbn) as a whole and per chain
>1ddy nts=140 [whole]
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA&GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA&GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA&GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((..........))).............&......(((..........))).............&......(((..........))).............&......(((..........))).............
>1ddy-A #1 nts=35 [chain] RNA
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((..........))).............
>1ddy-C #2 nts=35 [chain] RNA
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((..........))).............
>1ddy-E #3 nts=35 [chain] RNA
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((..........))).............
>1ddy-G #4 nts=35 [chain] RNA
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((..........))).............
H-bonding interactions are crucial for defining RNA secondary and tertiary structures. DSSR/3DNA contains a geometrically based algorithm for identifying H-bonds in nucleic-acid or protein structures given in .pdb or .cif format. Over the years, the method has been continuously refined, and it has served its purpose quite well. As of v1.1.1-2014apr11, this functionality is directly available from DSSR thorough the --get-hbonds option.
The output for 1msy, which contains a GUAA tetraloop mutant of Sarcin/Ricin domain from E. Coli 23 S rRNA, is listed below. The first line gives the header (# H-bonds in '1msy.pdb' identified by DSSR ...). The second line provides the total number of H-bonds (40) identified in the structure. Afterwards, each line consists of 8 space-delimited columns used to characterize a specific H-bond. Using the first one (#1) as an example, the meaning of each of the 8 columns is:
- The serial number (15), as denoted in the .pdb or .cif file, of the first atom of the H-bond.
- The serial number (578) of the second H-bond atom.
- The H-bond index (#1), from 1 to the total number of H-bonds.
- A one-letter symbol showing the atom-pair type (p) of the H-bond. It is ‘p’ for a donor-acceptor atom pair; ‘o’ for a donor/acceptor (such as the 2′-hydorxyl oxygen) with any other atom; ‘x’ for a donor-donor or acceptor-acceptor pair (as in #17); ‘?’ if the donor/acceptor status is unknown for any H-bond atom.
- Distance in Å between donor/acceptor atoms (2.768).
- Elemental symbols of the two atoms involved in the H-bond (O/N).
- Identifier of the first H-bond atom (O4@A.U2647).
- Identifier of the second H-bond atom (N1@A.G2673).
Command: x3dna-dssr -i=1msy.pdb --get-hbonds –o=1msy-hbonds.txt
# H-bonds in '1msy.pdb' identified by 3DNA version 3 (xiangjun@x3dna.org)
40
15 578 #1 p 2.768 O:N O4@A.U2647 N1@A.G2673
35 555 #2 p 2.776 O:N O6@A.G2648 N3@A.U2672
36 554 #3 p 2.826 N:O N1@A.G2648 O2@A.U2672
55 537 #4 p 2.965 O:N O2@A.C2649 N2@A.G2671
56 535 #5 p 2.836 N:N N3@A.C2649 N1@A.G2671
58 534 #6 p 2.769 N:O N4@A.C2649 O6@A.G2671
76 513 #7 p 2.806 N:N N3@A.U2650 N1@A.A2670
78 512 #8 p 3.129 O:N O4@A.U2650 N6@A.A2670
95 492 #9 p 2.703 O:N O2@A.C2651 N2@A.G2669
96 490 #10 p 2.853 N:N N3@A.C2651 N1@A.G2669
98 489 #11 p 2.987 N:O N4@A.C2651 O6@A.G2669
115 466 #12 p 2.817 O:N O2@A.C2652 N2@A.G2668
116 464 #13 p 2.907 N:N N3@A.C2652 N1@A.G2668
118 463 #14 p 2.897 N:O N4@A.C2652 O6@A.G2668
123 151 #15 o 2.622 O:O OP2@A.U2653 O2'@A.A2654
135 443 #16 p 2.898 O:N O2@A.U2653 N4@A.C2667
147 192 #17 x 3.054 O:O O4'@A.A2654 O4'@A.U2656
158 408 #18 p 2.960 N:O N6@A.A2654 OP2@A.C2666
173 188 #19 o 2.923 O:O O2'@A.G2655 OP2@A.U2656
173 378 #20 o 3.093 O:O O2'@A.G2655 O6@A.G2664
173 379 #21 o 3.343 O:N O2'@A.G2655 N1@A.G2664
181 386 #22 p 2.768 N:O N1@A.G2655 OP2@A.A2665
183 203 #23 p 2.754 N:O N2@A.G2655 O4@A.U2656
183 387 #24 p 2.887 N:O N2@A.G2655 O5'@A.A2665
188 379 #25 p 3.044 O:N OP2@A.U2656 N1@A.G2664
188 381 #26 p 2.944 O:N OP2@A.U2656 N2@A.G2664
200 401 #27 p 3.122 O:N O2@A.U2656 N6@A.A2665
201 398 #28 p 2.759 N:N N3@A.U2656 N7@A.A2665
220 381 #29 p 3.035 N:N N7@A.A2657 N2@A.G2664
223 371 #30 o 2.963 N:O N6@A.A2657 O2'@A.G2664
223 382 #31 p 3.039 N:N N6@A.A2657 N3@A.G2664
242 358 #32 p 2.821 O:N O2@A.C2658 N2@A.G2663
243 356 #33 p 2.890 N:N N3@A.C2658 N1@A.G2663
245 355 #34 p 2.887 N:O N4@A.C2658 O6@A.G2663
258 305 #35 o 2.604 O:N O2'@A.G2659 N7@A.A2661
258 308 #36 o 3.264 O:N O2'@A.G2659 N6@A.A2661
268 315 #37 p 2.973 N:O N2@A.G2659 OP2@A.A2662
268 327 #38 p 2.864 N:N N2@A.G2659 N7@A.A2662
371 390 #39 o 2.751 O:O O2'@A.G2664 O4'@A.A2665
550 566 #40 o 3.372 O:O O2'@A.U2672 O4'@A.G2673
In its default settings, DSSR detects 117 H-bonds for 1ehz (yeast phenylalanine tRNA), and 5,809 for 1jj2 (the H. marismortui large ribosomal subunit). Note that the program can identify H-bonds not only in RNA and DNA, but also in proteins, or their complexes. By default, however, DSSR only reports H-bonds within nucleic acids. As shown above, it is trivial to run DSSR with the --get-hbonds option to get all H-bonds in a given structure, and the plain text output is straightforward to work on.
While there exist dedicated tools for finding H-bonds, such as HBPLUS or HBexplore, DSSR may well be sufficient to fulfill most practical needs. If you notice any weird behaviors with this H-bond finding functionality, please let me know. I strive to address reported issues promptly, to the extent practical. At the very least, I should be able to explain why the program is working the way it does.
From the very first release up until recently, the DSSR distribution had included two executables for Windows: one version was compiled on MinGW/MSYS, and the other on Cygwin. The executables are supposed to be run under the corresponding shells of the two environments respectively.
Since DSSR is a simple self-contained command-line tool, the MinGW/MSYS version also works directly under the Command Prompt of native Windows. So Windows users had the following three options to use DSSR:
- Download the MinGW/MSYS version to run it under the Command Prompt of native Windows. No need to install MinGW/MSYS.
- Download the MinGW/MSYS version to run it under the MinGW/MSYS environment, which must be installed separately.
- Download the Cygwin version to run it under the Cygwin environment, which must be installed separately.
Over times, I have observed some confusions among DSSR users as to which of the two executables to use on Windows. Luckily, I noticed by chance recently that the DSSR executable compiled under MinGW/MSYS runs just fine in the Cygwin shell. So as of v1.1.0-2014apr09, the DSSR distribution contains only one executable for Windows: compiled under MinGW/MSYS on 32-bit Windows XP, the same DSSR executable runs under the Command Prompt of native Windows, MinGW/MSYS, and Cygwin, either on a 32-bit or 64-bit Windows (XP, Vista, 7 or 8) machine.
A size fits all: I no longer need to provide two compiled versions of DSSR for Windows, and users have just one executable to download (no more space for confusions).
Note added on 2024-11-25: DSSR is distributed by the CTV (Columbia Technology Ventures). See https://x3dna.org
In addition to VARNA, the draw program in the RNAstructure package from the Mathews Laboratory can also be used to depict DSSR-derived RNA secondary structures in connect table (.ct) format. The draw program produces images in PostScript (or svg) format, in different styles from those generated by VARNA. Given below are a couple of examples on how to connect DSSR with draw.
The secondary structure of the PDB entry 1msy in DSSR-derived .ct file is as below:
27 DSSR-derived secondary structure in '1msy'
1 U 0 2 0 2647
2 G 1 3 26 2648
3 C 2 4 25 2649
4 U 3 5 24 2650
5 C 4 6 23 2651
6 C 5 7 22 2652
7 U 6 8 0 2653
8 A 7 9 0 2654
9 G 8 10 0 2655
10 U 9 11 0 2656
11 A 10 12 0 2657
12 C 11 13 17 2658
13 G 12 14 0 2659
14 U 13 15 0 2660
15 A 14 16 0 2661
16 A 15 17 0 2662
17 G 16 18 12 2663
18 G 17 19 0 2664
19 A 18 20 0 2665
20 C 19 21 0 2666
21 C 20 22 0 2667
22 G 21 23 6 2668
23 G 22 24 5 2669
24 A 23 25 4 2670
25 G 24 26 3 2671
26 U 25 27 2 2672
27 G 26 0 0 2673
Let the DSSR-derived .ct file for 1msy be named 1msy.ct, the following two draw-command runs will produce the secondary structure in PostScript (1msy.eps) and svg (1msy.svg) respectively.
draw 1msy.ct 1msy.eps
draw 1msy.ct 1msy.svg --svg -n 1
![1msy [GUAA tetra loop] 2nd structure produced with the RNAstructure 'draw' program](http://forum.x3dna.org/images/1msy.svg "1msy [GUAA tetra loop] 2nd structure produced with the RNAstructure 'draw' program")
The PDB entry 1ehz (yeast phenylalanine tRNA) has a pseudo knot, so the draw program will create a ‘circularized’ structure as shown below:
![1ehz [yeast phenylalanine tRNA] 2nd structure produced with the RNAstructure 'draw' program](http://forum.x3dna.org/images/1ehz.svg "1ehz [yeast phenylalanine tRNA] 2nd structure produced with the RNAstructure 'draw' program")
Note the following two caveats:
As of v1.0.3-2014mar09, DSSR has a decent user manual in PDF! Currently of 45 pages long, the DSSR manual contains everything a typical user needs to know to get started using the program effectively. The contents the manual are listed below.
Table of Contents
List of Figures
Introduction
Download and installation
Usages
Command-line help
Default run on PDB entry 1msy – detailed explanations
Summary section
List of base pairs
List of multiplets
List of helices
List of stems
List of lone canonical pairs
List of various loops
List of single-stranded fragments
Secondary structure in dot-bracket notation
List of backbone torsion angles and suite names
Default run on PDB entry 1ehz (tRNAPhe) – summary notes
Brief summary
Specific features
Default run on PDB entry 1jj2 – four auto-checked motifs
Kissing loops
A-minor (types I and II) motifs
Ribose zippers
Kink turns
The --more option
Extra parameters for base pairs
Extra parameters for helices/stems
The –-non-pair option
The –-u-turn option
The --po4 option
The –-long-idstr option
Frequently asked questions
How to cite DSSR?
Does DSSR work for DNA?
Does DSSR detect RNA tertiary interactions?
Revision history
Acknowledgements
References
With the User Manual available, I feel confident to claim that DSSR is now mature, stable, ready for real world applications. While only time would tell, I have no doubt that DSSR will become an essential tool in RNA structural bioinformatics.
