X3DNA-DSSR: a resource for structural bioinformatics of nucleic acids
(An NIGMS National Resource supported by NIH grant R24GM153869)

I recently came across a Bioinformatics article VeriNA3d: an R package for nucleic acids data mining by Gallego et al. from IRB Barcelona. VeriNA3d can perform dataset analysis, single-structure analysis, and exploratory data analyses, with an emphasis on complex RNA structures. I am glad to see the DSSR is one of the third-party utilities that have been integrated into VeriNA3d, as shown below

VeriNA3d offers integration with third-party utilities such as the non-redundant lists of RNA structures (Leontis and Zirbel, 2012), the eRMSD suggested to compare RNA structures (Bottaro et al., 2014), a wrapper to the DSSR (Dissecting the Spatial Structure of RNA) software (Lu et al., 2015) and query functions to access the PDBe REST API (Velankar et al., 2016).

I browsed the GitLab repository and read through the supplemental documents. Clearly, VeriNA3d is a handy tool for the R community to perform RNA 3D structural analyses.

To DSSR users, Section “9 The dssr wrapper: getting the base pairs” of the supplemental PDF “VeriNA3d: introduction and use cases” is particularly relevant. The three paragraphs (with minor edits) are excerpted below:

The DSSR software (Dissecting the Spatial Structure of RNA) (Lu, Bussemaker, and Olson 2015) represents an invaluable resource to handle RNA structures. Some of the functions of veriNA3d overlap with the functionalities of DSSR, and both applications provide unique different features. We implement a wrapper to execute DSSR directly from R and get the best of both worlds in one place.

Note that installing veriNA3d does not automatically install DSSR, since we don’t redistribute third-party software. Before any user can use our wrapper, the dssr function, DSSR should be installed separately. To address this installation we redirect you to the DSSR manual, where anyone can find the specific instructions for their system. Once DSSR is installed and working in your computer, you will also be able to use it with our wrapper. If the DSSR executable (named x3dna-dssr) is in your path, dssr will find it automatically. If the wrapper does not find it, you can still use it specifying the absolute path to the executable with the argument exefile. Find more information running ?dssr.

One of the DSSR capabilities that users might be interested in is the detection and classification of base pairs. The following code shows a simple example. The output of the dssr wrapper is an object got from the json DSSR output. From R, json objects are parsed in the form of a tree of lists, with different types of information. Most of the interesting data is under the list models, sublist parameters, as shown herein.

I echo the authors’ policy of not redistributing third-party software with VeriNA3d. DSSR is under active development. Users should always visit the 3DNA Forum for downloading the latest version of DSSR, reporting bugs, and asking questions.

The R interface to DSSR (via JSON output) in VeriNA3d represents one of the intended use cases of DSSR’s many possible applications. No doubt DSSR is being increasingly integrated into other resources of RNA structural bioinformatics. Hopefully, more advanced DSSR features (than the detection and classification of base pairs) will also be widely appreciated in the future. Users would love DSSR better when they gain more experience in structural bioinformatics.

It is a great pleasure to see that our article Web 3DNA 2.0 for the analysis, visualization, and modeling of 3D nucleic acid structures has been highlighted in the cover page of the web server issue of NAR’19. According to the editor, This year, 331 proposals were submitted and 122, or 37%, were approved for manuscript submission. Of those approved, 94, or 77%, were ultimately accepted for publication. Overall, that corresponds to a ~28% acceptance rate.

The cover image and its caption are shown below. Moreover, details on how the cover image was created are available on the 3DNA Forum.

Caption: Examples of customized molecular models that can be generated with 3DNA: (top) a chromatin-like, nucleosome-decorated DNA with the structures of known histone-DNA assemblies placed at user-defined binding sites; (lower left) molecular schematic of a DNA trinucleotide diphosphate illustrating the base planes and reference frames used to construct and analyze 3D nucleic acid-containing structures; (lower right) customized single-stranded tRNA model built from a user-defined base sequence and a set of rigid-body parameters describing the desired placement of successive bases. Color code of base blocks: A, red; C, yellow; G, green; T, blue; U, cyan.

A paper titled DNA Conformational Changes Play a Force-Generating Role during Bacteriophage Genome Packaging has just been officially published in the Biophysical Journal (Volume 116, Issue 11, P2172-2180, June 04, 2019). I am glad to have the opportunity to collaborate with Kim Sharp, Gino Cingolani and Stephen Harvey on this interesting project that has big implications in understanding the mechanism of bacteriophage genome packaging. The abstract of the paper is shown below:

Motors that move DNA, or that move along DNA, play essential roles in DNA replication, transcription, recombination, and chromosome segregation. The mechanisms by which these DNA translocases operate remain largely unknown. Some double-stranded DNA (dsDNA) viruses use an ATP-dependent motor to drive DNA into preformed capsids. These include several human pathogens as well as dsDNA bacteriophages—viruses that infect bacteria. We previously proposed that DNA is not a passive substrate of bacteriophage packaging motors but is instead an active component of the machinery. We carried out computational studies on dsDNA in the channels of viral portal proteins, and they reveal DNA conformational changes consistent with that hypothesis. dsDNA becomes longer (“stretched”) in regions of high negative electrostatic potential and shorter (“scrunched”) in regions of high positive potential. These results suggest a mechanism that electrostatically couples the energy released by ATP hydrolysis to DNA translocation: The chemical cycle of ATP binding, hydrolysis, and product release drives a cycle of protein conformational changes. This produces changes in the electrostatic potential in the channel through the portal, and these drive cyclic changes in the length of dsDNA as the phosphate groups respond to the protein’s electrostatic potential. The DNA motions are captured by a coordinated protein-DNA grip-and-release cycle to produce DNA translocation. In short, the ATPase, portal, and dsDNA work synergistically to promote genome packaging.

Significantly, our work is highlighted in a “New and Notable” article, May the Road Rise to Meet You: DNA Deformation May Drive DNA Translocation by Paul Jardine (Volume 116, Issue 11, Pages 2060-2061, 4 June 2019):

Regardless of what drives conformational change in the portal, the idea that the linear DNA substrate is deformed in a way that makes it an energetic participant in its own movement opens new possibilities for how motors work. Large paddling or rotational motions by motor components may not be required if linear motion can be achieved by stretching or compressing the linear substrate, with rectified, cyclic conformational changes in the DNA rather than lever motions doing the work. If borne out by experiments, further simulation, and more structural information, this proposed mechanism may require a reappraisal of how we think about translocating motors.

For this project, I developed the x3dna-search program to survey similar fragments of single-stranded or double helical structures in the PDB.

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.

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 Westhof^9,41 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−W_{II 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.

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.

• Figure 1. Summary of web 3DNA 2.0
• Figure 2. New structural parameters
• Figure 3. Fiber models and mutations
• Supplemental PDF
• Graphical abstract (taken from Fig. 1E):

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

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.

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 Ų) and smaller twist (25º) than the bottom step containing G4 and G5 (9.7 Ų 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.

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..

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

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.

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.