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!

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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

  1. 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.
  2. 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.
  3. Multimer Assembly: Higher-order complexes were modeled by screening AlphaFold 3 across candidate stoichiometries and ionic/cofactor conditions, supplemented by manual assembly in PyMOL.
  4. 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
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The article on G.A pairs in ACS Biochemistry

After many years of efforts, it is a great pleasure to see our paper Effects of Noncanonical Base Pairing on RNA Folding: Structural Context and Spatial Arrangements of G·A Pairs published in ACS Biochemistry. The abstract is shown below:

Noncanonical base pairs play important roles in assembling the three-dimensional structures critical to the diverse functions of RNA. These associations contribute to the looped segments that intersperse the canonical double-helical elements within folded, globular RNA molecules. They stitch together various structural elements, serve as recognition elements for other molecules, and act as sites of intrinsic stiffness or deformability. This work takes advantage of new software (DSSR) designed to streamline the analysis and annotation of RNA three-dimensional structures. The multiscale structural information gathered for individual molecules, combined with the growing number of unique, well-resolved RNA structures, makes it possible to examine the collective features deeply and to uncover previously unrecognized patterns of chain organization. Here we focus on a subset of noncanonical base pairs involving guanine and adenine and the links between their modes of association, secondary structural context, and contributions to tertiary folding. The rigorous descriptions of base-pair geometry that we employ facilitate characterization of recurrent geometric motifs and the structural settings in which these arrangements occur. Moreover, the numerical parameters hint at the natural motions of the interacting bases and the pathways likely to connect different spatial forms. We draw attention to higher-order multiplexes involving two or more G·A pairs and the roles these associations appear to play in bridging different secondary structural units. The collective data reveal pairing propensities in base organization, secondary structural context, and deformability and serve as a starting point for further multiscale investigations and/or simulations of RNA folding.

Sample G.A pair characterized by DSSR

This work represents a multifaceted, fundamental application enabled by DSSR. Even at the base-pair (bp) level, DSSR provides unique features that complement the Leontis-Westhof (LW) notation of 12 geometric types.

At the review stage, we were asked by a referee to comment on the differences between DSSR and LW on bp classifications. The following paragraph in the “DISCUSSION” section of the paper is our response, expanded on the original writing that focused on DSSR’s capabilities:

Qualitative descriptions of noncanonical RNA base pairing, pioneered by Leontis and Westhof9,41 and linked in this work to the rigid-body parameters of interacting bases, have proven valuable in deciphering the connections between RNA primary, secondary, and tertiary structures. The present categorization is based on the positions of the hydrogen-bonded atoms with respect to a standard, embedded base reference frame30 defined in terms of an idealized Watson−Crick base pair. The major- and minor-groove base edges used here correspond in most cases to what are termed the Hoogsteen and sugar edges in the Leontis−Westhof scheme (one can compare the two classification schemes in Table S2). The + and − symbols introduced in 3DNA24 and DSSR27 unambiguously distinguish the relative orientations of the two bases. The trans and cis designations used in the earlier literature, however, are qualitative in nature and often uncertain. There are many “nc” (near cis, as in ncWW) and “nt” (near trans, as in ntSH) annotations listed in the RNA Structure Atlas; see, for example, the base-pair interactions in the sarcin−ricin domain of E. coli 23S rRNA found by entering PDB entry 1msy at http://rna.bgsu.edu/rna3dhub/pdb. The assignment of qualitative descriptors of RNA associations on the basis of atomic identity alone is generally not clear-cut. Numerical differences in the rigid-body parameters are critical to differentiating pairing schemes that share a common hydrogen bond, e.g., the G(N3)···A(N6) interaction found in m−WII and m−MI arrangements of G and A (Table 1 and Figures 4 and S3). The numerical data also provide a basis for following conformational transitions and may potentially be of value in making functional and other meaningful distinctions among RNA base pairs.

See also a recent thread Noncanonical base pair standards on the 3DNA Forum and the section titled “3.2.2 Base pairs” in the DSSR User Manual.

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Web 3DNA 2.0 paper published in NAR

It is a great pleasure to announce the publication of Web 3DNA 2.0 for the analysis, visualization, and modeling of 3D nucleic acid structures in Nucleic Acids Research (NAR). The paper will appear in the web server issue of NAR in July 2019. At nine-page in length and with several new structural parameters, this w3DNA 2.0 paper is certainly not a typical NAR web-server publication. It represents a significant contribution to the field of 3D nucleic acids structural bioinformatics, and will undoubtedly push the popularity of 3DNA to a new level.

The abstract is shown below:

Web 3DNA (w3DNA) 2.0 is a significantly enhanced version of the widely used w3DNA server for the analysis, visualization, and modeling of 3D nucleic-acid-containing structures. Since its initial release in 2009, the w3DNA server has continuously served the community by making commonly-used features of the 3DNA suite of command-line programs readily accessible. However, due to the lack of updates, w3DNA has clearly shown its age in terms of modern web technologies and it has long lagged behind further developments of 3DNA per se. The w3DNA 2.0 server presented here overcomes all known shortcomings of w3DNA while maintaining its battle-tested characteristics. Technically, w3DNA 2.0 implements a simple and intuitive interface (with sensible defaults) for increased usability, and it complies with HTML5 web standards for broad accessibility. Featurewise, w3DNA 2.0 employs the most recent version of 3DNA, enhanced with many new functionalities, including: the automatic handling of modified nucleotides; a set of ‘simple’ base-pair and step parameters for qualitative characterization of non-Watson–Crick double- helical structures; new structural parameters that integrate the rigid base plane and the backbone phosphate group, the two nucleic acid components most reliably determined with X-ray crystallography; in silico base mutations that preserve the backbone geometry; and a notably improved module for building models of single-stranded RNA, double- helical DNA, Pauling triplex, G-quadruplex, or DNA structures ‘decorated’ with proteins. The w3DNA 2.0 server is freely available, without registration, at http://web.x3dna.org.

Moreover, details on reproducing our reported results are available in a dedicated section ‘web 3DNA 2.0 (http://web.x3dna.org)’ on the 3DNA Forum.

Graphical abstract of web 3DNA 2.0

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3DNA blocview image in the cover of the RNA journal

While browsing the June 2019 issue of the RNA journal, I was surprised to see a cover image with familiar schematic representations:

Crystal structure of ykoY-mntP riboswitch chimera bound to cadmium

The caption is as below:

Crystal structure of ykoY-mntP riboswitch chimera bound to cadmium (Protein Data Bank code: 6cc3; Bachas ST, Ferré-D’Amaré AR. 2018. Convergent use of heptacoordination for cation selectivity by RNA and protein metalloregulators. Cell Chem Biol 25: 962–973.e5). The RNA backbone is displayed as a red ribbon; bases are shown as blocks with NDB coloring: A—red, C—yellow, G—green, U—cyan; cadmium ions are shown as red spheres. The image was generated using 3DNA/blocview and PyMol software. Cover image provided by the Nucleic Acid Database (ndbserver.rutgers.edu).

In addition to the blocview script distributed with 3DNA v2.x, the block-view has been integrated into DSSR via the --blocview option. Notably, the DSSR-plugin introduces the dssr_block command to PyMOL for interactive visualization of nucleic acid structures. See the DSSR User Manual for more information.

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DSSR is used for the analysis of CRISPR PbuCas13b-crRNA

Recently I read with great interest the article High-Resolution Structure of Cas13b and Biochemical Characterization of RNA Targeting and Cleavage by Slaymaker et al., published in Cell Reports (2019, 26, 3741–3751). This 1.65-Å structure (PDB id: 6dtd) “provides a mechanistic model for Cas13b target RNA recognition and identifies features responsible for target and cleavage specificity.”

I am pleased to see that DSSR is listed in the “KEY RESOURCES TABLE” under the category “Software and Algorithms”, and mentioned in the “Structure Analysis” section:

RNA structure was analyzed using DSSR (Lu et al., 2015). Protein conservation mapping to the structure was done using the Consurf server (Ashkenazy et al., 2016). Protein secondary structure was analyzed using the PDBSUM webserver (de Beer et al., 2014) (Figure S1E). APBS as part of the PyMOL visualization program was used to calculate electrostatics (Jurrus et al., 2018). Structure validation statistics were generated with MolProbity (Chen et al., 2010)

In the main text, the authors cited DSSR for the detection of a base multiplet. Running DSSR on PDB entry 6dtd, I found two base triplets, as shown below:

In the figure above, each of the two adenines is interacting with a G–C pair in the minor-groove edge (m) of the pair: A30 (left) is using its Watson-Crick edge (W), whilst A23 (right) is employing its major-groove edge (M). Thus they do not belong to the canonical A-minor motifs (types I or II) where the minor-groove edge of A interacts with the minor-groove edge of a WC pair. In DSSR, they are classified as type=X, a general category of noncanonical A-minor motifs.

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DSSR on PDB entry 6neb

Via PDB weekly update, I recently came across PDB entry 6neb, which is solved by NMR and described as an “MYC promoter G-quadruplex with 1:6:1 loop length”. I downloaded the atomic coordinates of the entry and ran DSSR on it. Indeed, DSSR readily identifies a three-layered parallel G-quadruplex (G4) with three propeller-type loops of 1, 6 and 1 nucleotides (i.e., 1:6:1), as shown below.

List of 1 G4-stem
  Note: a G4-stem is defined as a G4-helix with backbone connectivity.
        Bulges are also allowed along each of the four strands.
  stem#1[#1] layers=3 INTRA-molecular loops=3 descriptor=3(-P-P-P) note=parallel(4+0) UUUU parallel
   1  glyco-bond=---- groove=---- WC-->Major nts=4 GGGG A.DG3,A.DG7,A.DG16,A.DG20
      pm(>>,forward)  area=14.54 rise=3.36 twist=24.7
   2  glyco-bond=---- groove=---- WC-->Major nts=4 GGGG A.DG4,A.DG8,A.DG17,A.DG21
      pm(>>,forward)  area=9.67  rise=3.48 twist=30.3
   3  glyco-bond=---- groove=---- WC-->Major nts=4 GGGG A.DG5,A.DG9,A.DG18,A.DG22
    strand#1  U DNA glyco-bond=--- nts=3 GGG A.DG3,A.DG4,A.DG5
    strand#2  U DNA glyco-bond=--- nts=3 GGG A.DG7,A.DG8,A.DG9
    strand#3  U DNA glyco-bond=--- nts=3 GGG A.DG16,A.DG17,A.DG18
    strand#4  U DNA glyco-bond=--- nts=3 GGG A.DG20,A.DG21,A.DG22
    loop#1 type=propeller strands=[#1,#2] nts=1 A A.DA6
    loop#2 type=propeller strands=[#2,#3] nts=6 TTTTAA A.DT10,A.DT11,A.DT12,A.DT13,A.DA14,A.DA15
    loop#3 type=propeller strands=[#3,#4] nts=1 T A.DT19

I then read the associated paper titled Solution Structure of a MYC Promoter G-Quadruplex with 1:6:1 Loop Length lately published in the new, open-access ACS Omega journal. The reported structure 6neb has a 27-nt sequence (termed Myc1245) of bases 5’-TTGGGGAGGGTTTTAAGGGTGGGGAAT-3’. Myc1245 is based on the 27-nt long, purine-rich MycPu27 which has 5 tracts of guanines of G4-forming motif within the MYC promoter. In Myc1245, the third G-tract of MycPu27 has been replaced by TTTA, thus it uses only G-tracts 1, 2, 4, 5 for G4 formation. Previously, it was shown that Myc2345 (using G-tracts 2-5 of MycPu27) adopts a parallel G4 structure with three propeller loops of 1:2:1 nt length.

The MycPu27 sequence is representative of the G4-forming nuclease hypersensitive element (NHE III1) within the promoter region of the MYC oncogene. Formation of G4 structures suppresses MYC transcription, thus ligand-induced G4 stabilization in the DNA level is a promising strategy for cancer therapy. The NHE III1 motif can fold into multiple G4 structures depending on factors such as protein binding. The paper on 6neb illustrates that nucleolin, a protein shown to bind MYC G4 and repress MYC transcription, preferably binds the 1:6:1 loop length conformer than the 1:2:1 conformer (the major form under physiological conditions).

The DSSR analysis of 6neb shows that the two G-tetrad steps have different overlapping areas and twist angles. The top step comprising G3 and G4 (Fig. 1A) has better stacking interactions (14.5 Å2) and smaller twist (25º) than the bottom step containing G4 and G5 (9.7 Å2 and 30º, respectively).

area=14.54 rise=3.36 twist=24.7
area=9.67  rise=3.48 twist=30.3

The analysis characterizes the T1–A15 pair as a reverse Hoogsteen pair (rHoogsteen), which is distinct from the T+A Hoogsteen pair. In DSSR, the rHoogsteen pair is of type M–N (anti-parallel), whilst the Hoogsteen pair is of type M+N (parallel). With the local base-reference frames attached (Fig. 1B), it is easy to visualize that the z-axis of T1 is pointing out of the base-pair plane, and the z-axis of A15 is pointing inwards. See also my blog post Hoogsteen and reverse Hoogsteen base pairs.

Fig. 1C shows the ATG-triad automatically identified by DSSR. As is clear in Fig. 1A, the ATG-triad stacks on the 3-layered G4 structure on the 5’ side. Moreover, with color-coded base blocks (G in green, T in blue, and A in red), the two stacks (T10–T11, and T12–T13–A14) in the 6-nt central propeller loop is immediately obvious.


Figure 1. DSSR-derived structural features in PDB entry 6neb. The images were created using DSSR and PyMOL.

In the 6neb paper, the author stated that “The central loop of 6 nt connects the outer tetrads by spanning the G-core. A single nucleotide is the minimal length of this structural motif, so the five additional residues can significantly increase the loop’s conformational flexibility.” (p.2536) It is worth noting that in PDB entry 2m53, described in G-rich VEGF aptamer with locked and unlocked nucleic acid modifications exhibits a unique G-quadruplex fold, it was observed that:

An unprecedented all parallel-stranded monomeric G-quadruplex with three G-quartet planes exhibits several unique structural features. Five consecutive guanine residues are all involved in G-quartet formation and occupy positions in adjacent DNA strands, which are bridged with a no-residue propeller-type loop.

The G4 structure is polymorphic. It seems every imaginable or even unexpected form is possible, depending on the context.

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Non-G base tetrads

In addition to the well-known G-tetrad serving as the building block of G-quadruplexes (G4), other types of homogeneous or heterogeneous base-tetrads are also possible. In DSSR, all these base tetrads are generally termed multiplets where three or more bases associate in a co-planar fashion via H-bonding interactions.

In the context of G4 structures, U-tetrads are the most common. Fig. 1A shows an example of U-tetrads in PDB entry 4rne reported in the paper titled Structural Variations and Solvent Structure of r(UGGGGU) Quadruplexes Stabilized by Sr2+ Ions.. In the structure (Fig. 1B), two terminal U-tetrads cap the six-layered G4 structure in the middle. The four U’s in the U-tetrad are paired in parallel orientation (i.e., U+U), just as the G+G pairs in the G-tetrad of G4 structures (Fig. 1C). On the other hand, there is only one H-bond (O4…N3) in the U+U pair of the U-tetrad, in contrast to the two H-bonds in the G+G pair of the G-tetrad (Fig. 1C). In the PDB entry 4rne, DSSR also detects two octads where the middle G-tetrad is surrounded by four U’s in anti-parallel orientation (G’s filled in green vs. U’s empty, see Fig. 1C for an example).

Similarly orientated C-tetrad (C+C pair, Fig. 1D) or A-tetrad (A+A pair, Fig. 1E) are also possible. PDB entry “6a85”, associated with the paper High-resolution DNA quadruplex structure containing all the A-, G-, C-, T-tetrads., reported a high-resolution crystal structure of sequence 5'-AGAGAGATGGGTGCGTT-3' which contains all the homogeneous A-, G-, C-, T-tetrads, and the heterogeneous A:T:A:T tetrads. As of this writing (Feb. 19, 2019), the status for the PDB entry “6a85” is still “HPUB” (‘processing complete, entry on hold until publication’) even though the paper was published several months ago. Using mutate_bases in 3DNA, I generated a C-tetrad and an A-tetrad as shown in Fig. 1D and 1E. As the U-tetrad (Fig. 1A), the C- and A-tetrads also have only one H-bond in their M+N type pairs. The G-tetrad, with two H-bonds in its connecting pairs, is more stable than the other homogeneous base tetrads, leading to wide-spread G4 structures.

In the homogeneous base tetrads shown in Fig.1A-E, pairs are of the parallel M+N type and the bases are associated via their Watson-Crick and major-groove (Hoogsteen) edges. Two canonical (WC or G—U wobble) pairs can also associate via their minor-groove edges, as seen in PDB entries 2hk4 and 2lsx. Fig. 1F gives an example with two G—U wobble pairs (of anti-parallel M—N type, filled U in blue vs. empty G) in PDB entry 2lsx reported in the paper titled A minimal i-motif stabilized by minor groove G:T:G:T tetrads..

DSSR-derived non-G base tetrads
Figure 1. Non-G base tetrads automatically identified or modeled by 3DNA-DSSR. The images were created using DSSR and PyMOL.

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G-tetrad and pseudo G-tetrads

A G-quadruplex (G4) is composed of stacks of G-tetrad where four guanines form four G•G pairs in a circular, planar fashion. Specifically, the G•G pairs of the G-tetrad (see Fig. 1A below) in G4 are of type M+N according to 3DNA/DSSR: i.e., G+G with the local z-axes of pairing guanines in parallel. Moreover, the G+G pair is uniquely quantified by three base-pair parameters: Shear, Stretch, and Opening with mean values [+1.6 Å, +3.5 Å, –90º] or [–1.6 Å, –3.5 Å, +90º], corresponding to the cWH (cW+M) or cHW (cM+W) types of LW (DSSR) classifications, respectively. This pair is numbered VI in the list of 28 base pairs with two or more H-bonds between base atoms, compiled by Saenger.

In addition to the standard G-tetrad configuration as normally seen in G4 structures, a so-called pseudo-G-tetrad form (see Fig. 1B below) is reported in a 2013 paper titled Duplex-quadruplex motifs in a peculiar structural organization cooperatively contribute to thrombin binding of a DNA aptamer. (PDB entry 4i7y). In a 2017 publication from the same group, Through-bond effects in the ternary complexes of thrombin sandwiched by two DNA aptamers, another form of pseudo-G-tetrad (Fig. 1C) is found in PDB entries 5ew1 and 5ew2.

Clearly, pseudo-G-tetrads are very different from the normal G-tetrad, in terms of base pairing patterns. The G-tetrad is highly regular with the same type of G+G pairs, with the O6 atoms pointing to the middle of the circle. The two pseudo-G-tetrads are less regular, and they differ from each other as well, by flipping G12 from syn (Fig. 1B) to trans (Fig. 1C).

These distinctions stand out even more by filling the up-face (+z-axis outwards) of a guanine base in green while leaving the down-face (+z-axis inwards) empty (G5 in Fig. 1B, G5 and G12 in Fig. 1C). So in G-tetrad (Fig. 1A), all four guanines have their positive z-axis point towards the viewer, corresponding to all four G+G pairs. In one pseudo-G-tetrad (Fig. 1B), G5 has its positive z-axis pointing away from the viewer. So G5–G7 and G5–G16 pairs are of the M–N type. The other type of pseudo-G-tetrad (Fig. 1C) has the opposite orientation for G12. Finally, Fig. 1D shows schematically PDB entry 4i7y where the G-tetrad and a pseudo-G-tetrad are directly stacked, creating a two-layered pseudo-G-quadruplex.

DSSR-derived G-tetrads
Figure 1. (A) G-tetrad, (B-C) two types of pseudo-G-tetrads, and (D) the complex of a DNA-apatmer with thrombin. G-tetrads were automatically identified by 3DNA-DSSR. The images were created using DSSR and PyMOL.

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Starting DNA or RNA structures

A starting structure of suitable sequence is a prerequisite for many applications, including downstream use in X-ray crystallography, NMR, and molecular dynamics (MD) simulations. Browsing through the literature, I’ve noticed the following tools for such a purpose.

  • The make-na server, a web-based automated tool for making nucleic acid helices powered by NAB. It supports abasic sites via the underscore character (_). According to the help page, “The structure file represents the abasic as the 3-letter code ‘3DR’ in DNA strands and ‘ N’ in RNA strands. These are Protein Data Bank conventions.” An example input is shown below:
    ATACCGATACG_TAGAC
      TG_CTATGCTATCTGT_
  • The NAB itself, and the standalone fd_helix.c program which supports 6 fiber-based models of DNA or RNA.
  • The NUCGEN program from the Bansal group. “The NUCGEN software generates double helical models with the backbone fixed in B-form DNA, but with appropriate modifications in the input data, it can also generate A-form DNA and RNA duplex structures.”
  • 3DNA and its web interface. The ‘rebuild’ program can be used for constructing customized, single or duplex DNA/RNA structures based on a set of base-pair and step (helical) parameters. Moreover, the sugar-phosphate backbone in A-, B- or RNA conformation is allowed. The ‘fiber’ program incorporates a comprehensive list of 56 regular models, based mostly on fiber diffraction data. The list includes single, duplex, triplex, quadruplex, DNA, RNA structures or their hybrids. Notable, the classic Pauling’s triplex model is also available. The 3DNA web 2.0 makes these model-building features readily accessible to a large user base.

Overall, each of the tools listed above has its unique features and may fit better for different applications. It is to the benefit of the user community to have a choice.

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misc tips and tricks

Nowadays, I’ve been used to google searches as a quick way to solve problems. Once in a while, I come across a tip or trick that fixes an issue at hand and then move on. However, I may late on meet a similar problem, but only vaguely remember how I solved it previously. So I’d need to start googling around again. This list is a remedy for such situations, and it will be continuously updated. While the list is created for my own reference, it may also be useful to other viewers of the post, presumably reaching here via google.

  • icdiff — show diff with color
  • scc — strip C comments
  • Taskwarrior (taks) — manage TODO list from terminal
  • httpie as a replacement of curl and wget
  • byebug and pry for debugging Ruby
  • ag to search for PATTERN in source files, replacing grep
  • fd to find files and directories
  • bat to view files with syntax highlighting (in place of cat)
  • exa as an alternative to ls
  • bench to benchmark code
  • asciinema and svg-term to record terminal activity as an SVG animation. Another option is termtosvg. Moreover, the trio ttyrec, ttyplay, ttygif can record, play terminal screen recordings, and convert it into smooth GIF
  • wrk to benchmark HTTP APIs
  • hub — git wrapper for GitHub
  • tail -n +2 to skip the first line (starting from the second line)
  • sudo -i -u user_id, the -i or --login option invokes login shell
  • Understanding Shell Script’s idiom: 2>&1 — redirect ‘stderr’ to ‘stdout’ via ’2>&1’ in bash shell.
  • Ruby one-liners
    • ruby -pi.bak -e "gsub(/SOME_PATTERN/, 'other_text')" files for global replacement of SOME_PATTERN by other_text in files
    • ruby -pe 'gsub(/_/, ".")' globally replace ‘_’ with ‘.’

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