One of DSSR’s noteworthy features is the auto-detection of helical junctions in nucleic acids structures, be it RNA, DNA, or chimeric DNA/RNA, consisting of one or multiple chains. Helical junctions are created at the interface of three and more stems composed of canonical pairs (Watson-Crick A—T/U and G—C, or wobble G—U). A three-way junction model is illustrated below (copied from Figure 1 of the Bindewald et al. RNAJunction paper). Note that the three chains are each continuous (i.e., consecutive nts are covalently connected), and together with the three inner bps, forming a loop in the middle. Here, the three-way junction is of type [3×2×3], and the loop is composed of a total of 3×2+3+2+3 = 14 nts.

DSSR automatically detects all existing helical junctions in a nucleic acid structure, as illustrated by the following examples.

1l6b [all DNA Holliday junction structure of d(CCGGTACm5CGG)]

This is a simple four-way junction of type [0×0×0×0], where all bases are paired, leaving no connecting nts. The related portion of DSSR output is:

List of 1 junction(s)
   1 4-way junctions: 8 nts; [0x0x0x0]; linked by [#1, #2, #4, #3]
       1:A.DA6+1:A.DC7+2:B.DG14+2:B.DT15+2:A.DA6+2:A.DC7+1:B.DG14+1:B.DT15 [ACGTACGT]
       0 nts junction ; 1:A.DA6-->1:A.DC7 [AC]
       0 nts junction ; 2:B.DG14-->2:B.DT15 [GT]
       0 nts junction ; 2:A.DA6-->2:A.DC7 [AC]
       0 nts junction ; 1:B.DG14-->1:B.DT15 [GT]

Technically, note the following points:

• The four-way junction is derived from the biological assembly 1 (PDB file 1l6b.pdb1), which contains two copies of the asymmetric unit, delineated by MODEL/ENDMDL. By default, DSSR/3DNA works one structure at a time, corresponding to the first structure/model in a given PDB or mmCIF file. To take the biological assembly as a whole, and to avoid confusions with MODEL/ENDMDL delineated NMR entries, the ENDMDL record of the first model is commented out in the file (1l6b.pdb1), as below:

#ENDMDL                                                                          
MODEL        2                                                                  

• With the modified PDB file 1l6b.pdb1, the DSSR command can be run as x3dna-dssr -i=1l6b.pdb1, with the output going to stdout.

• The simplified schematic block png image was generated with the command below to create the Raster3D .r3d file (1l6b.r3d), which was then ray-traced using PyMOL.

blocview -r 1l6b.r3d 1l6b.pdb1

1egk [a four-way DNA/RNA junction]

This four-way junction consists of both DNA and RNA chains. Here the helical junction may not be that obvious by directly looking at the 3D image.

List of 1 junction(s)
   1 4-way junctions: 10 nts; [0x0x1x1]; linked by [#3, #-1, #4, #5]
       B.DC37+B.DT38+B.DA45+B.DC46+C.G109+C.A110+C.U111+D.DA130+D.DG131+D.DG132 [CTACGAUAGG]
       0 nts junction ; B.DC37-->B.DT38 [CT]
       0 nts junction ; B.DA45-->B.DC46 [AC]
       1 nts junction C.A110 [A]; C.G109-->C.U111 [GAU]
       1 nts junction D.DG131 [G]; D.DA130-->D.DG132 [AGG]

1ehz [yeast phenylalanine tRNA]

As shown below, DSSR correctly detects the classic L-shaped 3D structure and the cloverleaf 2D structure of a tRNA.

List of 1 junction(s)
   1 4-way junctions: 16 nts; [2x1x5x0]; linked by [#1, #2, #3, #4]
       A.U7+A.U8+A.A9+A.2MG10+A.C25+A.M2G26+A.C27+A.G43+A.A44+A.G45+A.7MG46+A.U47+A.C48+A.5MC49+A.G65+A.A66 [UUAgCgCGAGgUCcGA]
       2 nts junction A.U8+A.A9 [UA]; A.U7-->A.2MG10 [UUAg]
       1 nts junction A.M2G26 [g]; A.C25-->A.C27 [CgC]
       5 nts junction A.A44+A.G45+A.7MG46+A.U47+A.C48 [AGgUC]; A.G43-->A.5MC49 [GAGgUCc]
       0 nts junction ; A.G65-->A.A66 [GA]

2fk6 [RNAse Z/tRNA(Thr) complex]

In a recent paper Predicting Helical Topologies in RNA Junctions as Tree Graphs by Laing et al., this PDB entry was selected in Table 1 as containing a three-way junction. However, DSSR fails to detect any junction in this structure, even though the program does find co-axial stacks. It turns out that the PDB entry 2fk6 does not possess the anti-codon stem/loop, thus nts C25 and G46 are not covalently connected. While three-way junctions may be defined differently, the DSSR result follows the above mentioned chain-continuity requirement.

Overall, DSSR can consistently find all helical junctions in a given nucleic acid structure. Try DSSR on a ribosomal structure, you may well appreciate what it reveals. Moreover, it is straightforward to apply the program to all RNA/DNA-containing entries in the PDB via a script.

Given the primary sequence of an RNA molecule, there are numerous methods for predicting its secondary (2D) structures. To judge their accuracy, three-dimensional (3D) RNA structures solved experimentally by X-ray or NMR as deposited in the PDB are often used as benchmarks. DSSR is a handy tool to derive an RNA 2D structure from its 3D coordinates in PDB or mmCIF format. The 2D structure is specified in the dot-bracket notation (dbn), which can be fed directly into drawing programs such as VARNA for interactive display and easy generation of publication quality 2D diagrams.

Over the past few months, I’ve been asked a few times on the details of how the diagrams in the DSSR post were created. The answer is really simple, and has already been mentioned above and in the post. Here are two concrete examples to show how the process works.

1zc5 (structure of the RNA signal essential for translational frame shifting in HIV-1)

This is the structure used in the VARNA paper. Let the PDB file be named 1zc5.pdb, the DSSR program can be run like this:

x3dna-dssr -i=1zc5.pdb

The output is sent to stdout by default, with the following three lines towards the end:

>1zc5-A #1 RNA with 41 nts
GGCGAUCUGGCCUUCCUACAAGGGAAGGCCAGGGAAUUGCC
(((((((((((((((((....)))))))))))...))))))

Simply copy and paste the last two lines (sequence and the 2D structure in dbn notation) into the Seq: and Str: fields of the VARNA demo page, the diagram will be updated automatically, as shown in the screenshot:

1ehz (crystal structure of yeast phenylalanine tRNA at 1.93 Å resolution)

This example (1ehz.pdb) is used to illustrate tRNA’s classic cloverleaf 2D structure. The related command and result are:

x3dna-dssr -i=1ehz.pdb -o=1ehz.out

# the output is sent to file '1ehz.out'
# towards its end are the following 3 lines

>1ehz-A #1 RNA with 76 nts
GCGGAUUUAgCUCAGuuGGGAGAGCgCCAGAcUgAAgAPcUGGAGgUCcUGUGuPCGaUCCACAGAAUUCGCACCA
(((((((..((((.....[..)))).((((.........)))).....(((((..]....))))))))))))....

I’ve used a local copy of the JAVA web start version of VARNA (VARNA-WebStart.jnlp) to generate the following 2D diagram. Here, in addition to the customized title, I have set the number period to 5 nts, adopted the simple base-pair style, and manually adjusted the T arm (upper right corner) to make the long line connecting G19 and C56 a bit more unobtrusive. Right-click to see the context menu.

Note that the G19—C56 pair creates a pseudo-knot (specified by the matching [] pair in the dbn notation above) in tRNA. I was not aware of this salient feature from previous knowledge of relevant literature. It was indeed a surprise when I first saw it in the 2D diagram.

As illustrated above, DSSR serves well as a bridge from RNA 3D to 2D structures. Give DSSR a try, you will find the program actually has much more to offer!

As of June 24, 2013, the number of 3DNA Forum registrations has passed the 1000 mark. On September 16, 2012, I wrote the post The number of 3DNA forum registrations has reached 500. Thus, in slightly over 9 months, the number has doubled, with approximately 2 registrations per day.

I am glad to see the steady increase of the 3DNA user base. Over the time, I have strived to be responsive to user questions, and made every effort to keep the forum spam free. By and large, employing simple 3DNA-related questions has turned out to be an effective anti-spam strategy. Since the launch of the new forum.x3dna.org in March 2012, I’ve received less than five requests (to the best of my memory) asking for help on registrations. As a recently example, a potential user got stuck with the question about what ‘w’ means in w3DNA. Based on user feedback, I have added hints to some questions to make their answers more obvious. Whatever the reasons, each reported issue has been promptly resolved.

With the release of DSSR and the continuous support of an enthusiastic user community, I have every reason to believe that 3DNA will gain more popularity in the years to come.

As of the beta-r14-on-20130626 release, DSSR has the functionality to identify kink-turns and reverse k-turns given an RNA structure in PDB format.

The k-turn motif was first described by Klein et al. (2001) in the paper The kink-turn: a new RNA secondary structure motif, based on analyses of the H. marismortui large ribosomal unit. It turns out to be a widespread structural motif, now with a dedicated k-turn database hosted by the Lilley laboratory.

Geometrically, k-turn is composed of an asymmetric internal loop, with a sharp kink between the two framing helices and characteristic loop features (including at least one sheared G-A pair and A-minor interactions). Overall, k-turn is a complicated motif, and I am not aware of any published method or available software for its auto-detection.

Previous releases of DSSR has built up all the necessary components to detect key features of a k-turn. Over the past few weeks, I have been focusing on connecting the dots to implement an algorithm for its auto-identification. As of beta-r14-on-20130626, DSSR can locate ‘simple’ k-turns or reverse k-turns from an RNA structure in PDB format. I understand the subtleties and variations of k-turns, and will refine the algorithm in future releases of DSSR.

Without putting k-turns under its umbrella, DSSR appears incomplete in its functionality. Hopefully, detection of k-turns will help DSSR gain more attention from the RNA structure community.

A new paper titled Analyzing and Building Nucleic Acid Structures with 3DNA has been published in JoVE (Journal of Visualized Experiments). Specifically, the article illustrates 3DNA’s unique capability to characterize and modify DNA structures at the level of the constituent base-pair steps, and highlights a new feature in v2.1 to analyze and align an ensemble of related structures determined with NMR or generated by MD simulations.

Here is the abstract:

The 3DNA software package is a popular and versatile bioinformatics tool with capabilities to analyze, construct, and visualize three-dimensional nucleic acid structures. This article presents detailed protocols for a subset of new and popular features available in 3DNA, applicable to both individual structures and ensembles of related structures. Protocol 1 lists the set of instructions needed to download and install the software. This is followed, in Protocol 2, by the analysis of a nucleic acid structure, including the assignment of base pairs and the determination of rigid-body parameters that describe the structure and, in Protocol 3, by a description of the reconstruction of an atomic model of a structure from its rigid-body parameters. The most recent version of 3DNA, version 2.1, has new features for the analysis and manipulation of ensembles of structures, such as those deduced from nuclear magnetic resonance (NMR) measurements and molecular dynamic (MD) simulations; these features are presented in Protocols 4 and 5. In addition to the 3DNA stand-alone software package, the w3DNA web server, located at http://w3dna.rutgers.edu, provides a user-friendly interface to selected features of the software. Protocol 6 demonstrates a novel feature of the site for building models of long DNA molecules decorated with bound proteins at user-specified locations.

A new section dedicated to the JoVE paper will be set up on the 3DNA Forum soon. It will contain all the data files and scripts so our published results can be strictly reproduced. The section should also serve as a platform for open discussions of related protocols.

Over the past six months or so¹, I’ve been focusing mostly on developing DSSR, a new addition to the 3DNA suite of programs. So what is DSSR, specifically? Why did I bother to create it? How would it be relevant to the nucleic acid structure community?

Literally, DSSR stands for Defining the (Secondary) Structures of RNA². Starting from an RNA structure in PDB format, DSSR employs a set of simple criteria to identify all existent base pairs (bp): both canonical Watson–Crick (WC) pairs and non-canonical pairs with at least one H-bond, made up of normal or modified bases, regardless of tautomeric or protonation state. The classification is based on the six standard rigid-body bp parameters (shear, stretch, stagger, propeller, buckle, and opening), which together rigorously quantify the spatial disposition of any two interacting bases. Moreover, the program characterizes each bp by commonly used names (WC, reverse WC, Hoogsteen, reverse Hoogsteen, wobble, sheared, imino, Calcutta, and dinucleotide platform), the Saenger classification scheme of 28 types, and the Leontis-Westhof nomenclature of 12 basic geometric classes. DSSR also checks for non-pairing interactions (H-bonds or base stacking).

DSSR detects triplets and even higher-order base associations by searching horizontally in the plane of the associated bp for further H-bonding interactions. The program determines helical regions by exploring each bp’s neighborhood vertically for base-stacking interactions, regardless of backbone connection (e.g., coaxial stacking of helices or pseudo helices). Moreover, each helix/stem is characterized by a least-squares fitted helical axis to allow for easy quantification of relative helical geometry. DSSR calculates commonly used backbone (including the virtual η/θ) torsion angles, classifies the main chain backbone into BI/BII conformation and the sugar into C2’/C3’-endo like pucker, identifies A-minor interactions (types I and II), ribose zippers, G quartets, hairpin loops, kissing loops, bulges, internal loops and multi-branch loops (junctions). It also detects the existence of pseudo-knots, and outputs RNA secondary structure in the dot-bracket notation.

Experienced 3DNA users may notice that some of the above outlined functionality (e.g., calculation of torsion angles, identification of all pairs, higher order base associations, and helices) have existed for over a decade. Over the years, I have written several posts (see What can 3DNA do for RNA structures?, and links therein) to advocate 3DNA’s applications in RNA structural analysis. Nevertheless, 3DNA has never been widely used in the RNA structure community, for various possible reasons: (1) the misconception that 3DNA is only for DNA (but not RNA); (2) the basic functionality is split into two programs (find_pair and analyze), and needs to be run several times with different options (default find_pair, and with -s, or -p). Thus even though 3DNA is applicable to RNA structures, it is unnecessarily complicated and confusing (especially to new 3DNA users); (3) 3DNA is command-line driven, consisting of many C programs and scripts, with different styles in specifying options. It has the ‘reputation’ of being powerful, but cryptic and hard to use.

I’ve created DSSR from scratch to take consideration of these factors, by employing my extensive experience in supporting 3DNA, an increased knowledge in RNA structures and refined C programming skills. Implemented in ANSI C as a stand-alone command-line program, DSSR is self-contained. Its executables (on MacOS X, Linux and Windows) have zero runtime dependencies. No setup is necessary; simply put the program into a folder of your choice (preferably one on your command PATH), and it should work. DSSR has sensible default settings and an intuitive output, making it directly accessible to a much broader audience than 3DNA per se. Since its initial release on March 3, 2013, I’ve yet to hear any installation or usage problem. So far, all reported bugs have been verified and fixed promptly. The latest beta release has been checked against all nucleic-acid-containing entries in the PDB, without any known issues.

Overall, DSSR consolidates, refines, and significantly extends 3DNA’s functionality for RNA structural analysis. There are more in DSSR than its simple interface suggests. Piecewise, DSSR may appear nothing new, yet combined together, it has unique features not available anywhere else. Its value will be gradually appreciated as DSSR becomes more widely used by the community. Want to know if your structure contains any Hoogsteen pair, sheared G•A pair, or a dinucleotide platform? DSSR can check it for you, easily.

DSSR-beta already possesses all the basic functionality and has been well tested to serve as a handy tool for RNA structural analysis. I stand firmly behind DSSR, and strive to continuously improve the program. Give it a try, and report back on the 3DNA Forum any issues you have. As always, I respond quickly and concretely to all questions posted there. I hope you enjoying using DSSR as much as I enjoy creating and supporting it!

¹ This post was published on March 29, 2013, shortly after the beta releases of DSSR [note added on March 15, 2014].

² DSSR also works for DNA, or DNA-protein complexes, as far as the basic functionality is concerned. Moreover, the acronym could have two other possible interpretations, as would be obvious when the program gains a wider recognition.

Early on when I started on DNA structures, I read Saenger’s book Principles of Nucleic Acid Structure and became familiar with his classification of the 28 possible base-pairs (bps) for A, G, U(T), and C involving at least two (cyclic) hydrogen bonds (see figure below).

Later on, I read from the 2nd edition of The RNA World book a list of 29 bps compiled by Burkard, Turner & Tinoco. While the one bp discrepancy (28 vs 29) has been in my mind for quite a long while, I had never paid much attention to the issue until recently while adding classifications of RNA bps (among many other functionalities) to 3DNA. A Google search did not help solve the puzzle, so I decided to dig it out by comparing the two lists.

The Burkard et al. list is titled Structures of Base Pairs Involving at Least Two Hydrogen Bonds and it mentions specifically Saenger’s list:

The structures of 29 possible base pairs that involve at least two hydrogen bonds are given in Figures 1–5 (for further descriptions, see Saenger, in Principles of nucleic acid structure, p. 120. Springer-Verlag [1984]).

However, in the five figures, Burkard et al. do not provide the corresponding Saenger numbers (I to XXVIII, 1—28) for the 28 common bps; thus it is not immediately obvious which one (i.e., the new addition by Burkard et al.) is missing from Saenger’s list. Under careful scrutiny, the absent bp turns out to be the “G•C N3-amino, amino-N3” pair in Figure 3: “Six possible flipped purine-pyrimidine mismatches.” One example of such G+C pair is found in the 5S ribosomal RNA (chain 9, G3022—C3026) of Haloarcula marismortui in PDB entry 1vq8.

The above figure shows clearly that the G+C bp does indeed have two canonical H-bonds between base atoms, and it is difficult to speculate how it escaped Saenger’s selection criteria. In the upcoming new 3DNA component, I am listing this bp as number XXIX (29), along with the other 28 base pairs.

Recently, I came across the so-called Calcutta U-U base pair (bp) [see figure below] while reading articles on C-H…O contacts in nucleic acid structures. Not familiar with this named pair before, I was curious to find out what it’s about. After some searching, I traced the origin of the Calcutta U-U bp to the following two papers published by Sundaralingam’s group during the middle 1990s:

• Wahl et al. (1996). The structure of r(UUCGCG) has a 5’-UU-overhang exhibiting Hoogsteen-like trans UU base pairs. Nat. Struct. Biol., 3(1), 24-31. In Note added in proof, the author wrote:

We have called the novel U•U base pair, where the Hoogsteen face of one of the pyrimidines is involved in a C5-H—O4 hydrogen bond, the ‘Calcutta Base Pair’, since it was announced at the International Seminar-cum-School on Macromolecular Crystallographic Data held in Calcutta, November 16-20, 1995.

• Wahl & Sundaralingam (1997). C-H…O hydrogen bonding in biology. Trends Biochem Sci., 22(3), 97-102. In this review article, the authors noted:

We recently discovered a novel U•U base pair, referred to as the Calcutta base pair, in the crystal structure of an RNA hexamer UUCGCG (Ref. 18). The two uracil bases form a conventional N(3)-H…O(4) and an unconventional C(5)-H…O(2) hydrogen bond (Fig. 3a). The C-H…O interaction is entirely ‘voluntary’ and not ‘forced’, underlining its importance in base mispairing.

3DNA has no problem to identify the Calcutta U-U bps (or any pair for that matter); an example is shown below based on the RNA hexamer UUCGCG structure (PDB entry: 1osu) solved by Sundaralingam and colleagues.

In the new 3DNA component I’ve been working on (and to be released soon), the Calcutta U-U pair is characterized as below:

1/A.U1 3/A.U2 [U-U] Calcutta 00-n/a tHW -MW
  anti C3'-endo 8.9 --- anti C3'-endo 30.3
  dcc=11.18  dnn=8.48  dmm=7.58  tor=-174.1
  H-bonds[2]: "O4(carbonyl)-N3(imino)[2.76]; C5-O4(carbonyl)[3.27]"

  Shear=-3.67   Stretch=-0.52     Stagger=-0.89
  Buckle=-1.41  Propeller=-16.03  Opening=-90.67

The Calcutta pair is explicitly named, along with other named base pairs (e.g., Watson-Crick [WC], Wobble, and Hoogsteen bps). It is classified as type tHW (trans with Hoogsteen/WC interacting edges), following the commonly used Leontis-Westhof nomenclature. It does not belong to any of the 28 bps (00-n/a) with at least two conventional H-bonds, as categorized by Saenger. In 3DNA, the Calcutta U-U pair is of M-N type, designated as -MW.

Among the well-known named base pairs, some are after the scientists who discovered them (e.g., WC and Hoogsteen bps), while others are based on chemical/geometrical features (e.g., Wobble and Sheared G-A bps), or a combination of both (e.g., reversed WC/Hoogsteen bps). The Calcutta U-U pair is unique in that it is named after a place in India:

Kolkata, or Calcutta, is the capital of the Indian state of West Bengal. … While the city’s name has always been pronounced Kolkata or Kolikata in Bengali, the anglicized form Calcutta was the official name until 2001, when it was changed to Kolkata in order to match Bengali pronunciation.

Prior to v2.1, 3DNA does not provide any direct support for the analysis of molecular dynamics (MD) simulations trajectories of nucleic acid structures. Nevertheless, over the years, I noticed some significant applications of 3DNA in the active MD field; see my blog post (December 6, 2009) titled 3DNA in the PCCP nucleic acid simulations themed issue. In January 2011, I released a set of two Ruby scripts specifically aimed to facilitate the analysis of MD simulations trajectories. Thereafter (as of 3DNA v2.1), I have significantly refined and expanded the Ruby scripts, and consolidated the functionality under one umbrella, x3dna_ensemble with multiple sub-commands (analyze, block_image, extract, and reorient). I believe x3dna_ensemble would make it straightforward to analyze ensembles (NMR or MD simulations trajectories) of nucleic acid structures.

Under this background, I am glad to read recently an article titled Structure, Stiffness and Substates of the Dickerson-Drew Dodecamer in J. Chem. Theory Comput. where 3DNA was used extensively. This work represents a re-visit of the classic Dickerson−Drew B-DNA dodecamer d-[CGCGAATTCGCG]2 using state-of-the-art MD simulations with different ionic conditions and solvation models, and compares the MD trajectories with modern crystallographic and NMR data. Among the author list (Tomas Drsata, Alberto Perez, Modesto Orozco, Alexandre Morozov, Jiri Sponer, and Filip Lankas) are some well-known figures in the MD field of nucleic acid structures.

Reading through the text, I am not sure if the newly available functionality of x3dna_ensemble was used. From the excerpts of the citations given below, however, it seems obvious that 3DNA is now well-accepted by the MD community.

Snapshots taken in 10 ps intervals were analyzed using the 3DNA program.43 From 3DNA outputs, time series of conformational parameters were extracted. These included the intra-base-pair coordinates (buckle, propeller, opening, shear, stretch, and stagger), inter-base-pair or step coordinates (tilt, roll, twist, shift, slide, and rise) as well as groove widths (based on P−P distances), backbone torsions, and sugar puckers.

Contrary to the original work of Lankas et al.,31 the intra-base-pair and step coordinates used here are those defined by 3DNA.43

Here, we apply this model together with the 3DNA definitions of the intra-base-pair and step coordinates.43

However, important differences remain, and non- negligible differences are in fact observed between individual experimental structures also in the central part of DD, even though the intra-base-pair and step coordinates are computed using the same coordinate definitions64 (we consistently use the 3DNA coordinates in this work).