March 2026
February 2026
Cover image provided by X3DNA-DSSR, an NIGMS National Resource for Structural Bioinformatics of Nucleic Acids (R24GM153869; skmatics.x3dna.org). Image generated using DSSR and PyMOL (Lu XJ. 2020. Nucleic Acids Res 48: e74).
As the developer of DSSR, I am thrilled to see its application in cutting-edge research across multiple disciplines. Below is a list of four recent publications that highlight how DSSR has been utilized, underscoring its versatility and significance in structural bioinformatics.
In the Geng et al. (2025) Nucleic Acids Research (NAR) paper, titled 'Revealing hidden protonated conformational states in RNA dynamic ensembles', DSSR is simply cited as follows:
All bp geometries, hydrogen-bond, backbone, stacking, and sugar dihedral angles were calculated using X3DNA-DSSR [77].
In the preprint by Gordan et al. (2025), titled 'High-throughput characterization of transcription factors that modulate UV damage formation and repair at single-nucleotide resolution', DSSR is cited as follows:
Step base stacking, base pair shift, base pair slide, interbase angle, pseudorotation angle, and sugar puckering classifications of nucleobases were computed using X3DNA-DSSR (v2.5.0)75. Base stacking was defined as the overlapping polygon area in Å2 when projecting the dipyrimidine base ring atoms (excluding exocyclic atoms) into the mean base pair plane76. The sugar ring pseudorotation phase angle of each pyrimidine was also calculated using X3DNA-DSSR as described by Altona, C. & Sundaralingam, M.77 Interbase angle was defined as sqrt(propeller2+buckle2) per the X3DNA-DSSR documentation.
Figure 6: TF Binding Induces Structural Distortion Favorable to UV Dimerization is highly informative, particularly panel (a), which illustrates the ensemble of structural parameters that predispose dipyrimidines to cyclobutane pyrimidine dimers (CPD) or 6-4 pyrimidine-pyrimidones (6-4 PP) formation. DSSR is designed as an integrated software tool, offering a comprehensive suite of structural parameters not found in any other single tool I am aware of. Despite this, the innovative use of DSSR by Gordan et al. exceeds my expectations and demonstrates its versatility.
In the preprint by Kubaney et al. (2025) from the Baker group, titled 'RNA sequence design and protein-DNA specificity prediction with NA-MPNN', DSSR is cited as follows:
On the pseudoknot subset, we evaluate additional structure‐ and reactivity‐based metrics. DSSR v2.3.241 is used to extract the ground‐truth secondary structure from the native crystal structures. For each designed sequence, RibonanzaNet predicts 2A3 reactivity profiles, from which we compute predicted OpenKnot scores (see https://github.com/eternagame/OpenKnotScore)31 using the predicted reactivity together with the DSSR ground truth.
In a recent NSMB paper from the Baker group, titled 'Computational design of sequence-specific DNA-binding proteins', 3DNA is cited as follows:
RIF docking of scaffolds onto DNA targets (DBP design step 1) Structures of B-DNA for each target (Supplementary Table 2) were generated by (1) using the DNA portion of PDB 1BC8 (ref. 60), PDB 1YO5 (ref. 61), PDB 1L3L (ref. 51) or PDB 2O4A (ref. 62) or (2) using the software X3DNA63, followed by a constrained Rosetta relax of the DNA structure.
Please note that 3DNA has been replaced by DSSR. The functionality for constructing B-DNA models, previously provided by 3DNA, is now directly available in DSSR via its fiber and rebuild modules.
In the preprint by Si et al. (2025), titled 'End-to-End Single-Stranded DNA Sequence Design with All-Atom Structure Reconstruction', DSSR is cited as follows:
Since ViennaRNA and NUPACK require secondary structures as input, we used DSSR35 to extract secondary structures from the corresponding ssDNA three-dimensional structures.
The above use cases are merely a sample of how DSSR is utilized in the scientific literature. It is reasonable to state that DSSR has emerged as a de facto standard tool within the field of nucleic acid structural bioinformatics. Overall, DSSR is a mature, robust, and efficient software product that is actively developed and maintained. I am committed to making DSSR synonymous with quality and value. Its unmatched functionality, usability, and support save users significant time and effort compared to alternative solutions.
DSSR is available free of charge for academic users. Additionally, it has been integrated into other high-profile bioinformatics resources, including NAKB, PDB-redo, and N•ESPript.
References
- Geng A, Roy R, Ganser L, Li L, Al-Hashimi HM. Revealing hidden protonated conformational states in RNA dynamic ensembles. Nucleic Acids Research. 2025;53:gkaf1366. https://doi.org/10.1093/nar/gkaf1366.
- Gordan R, Wasserman H, Chi B, Bohm K, Duan M, Sahay H, et al. High-throughput characterization of transcription factors that modulate UV damage formation and repair at single-nucleotide resolution. 2025. https://doi.org/10.21203/rs.3.rs-8197218/v1.
- Kubaney A, Favor A, McHugh L, Mitra R, Pecoraro R, Dauparas J, et al. RNA sequence design and protein–DNA specificity prediction with NA-MPNN. 2025. https://doi.org/10.1101/2025.10.03.679414.
- Glasscock CJ, Pecoraro RJ, McHugh R, Doyle LA, Chen W, Boivin O, et al. Computational design of sequence-specific DNA-binding proteins. Nat Struct Mol Biol. 2025;32:2252–61. https://doi.org/10.1038/s41594-025-01669-4.
- Si Y, Xu Y, Chen L. End-to-end single-stranded DNA sequence design with all-atom structure reconstruction. 2025. https://doi.org/10.64898/2025.12.05.692525.
I’ve created a web API to DSSR and SNAP, and fiber models. The overall help message is available via http://api.x3dna.org. Individually, each program is accessed as below.
Usage with 'http' (HTTPie):
http -f http://api.x3dna.org/dssr [options] url=|model@
http http://api.x3dna.org/dssr/help -- display this help message
Options:
json=true-or-FALSE(default) [e.g., json=true # JSON output]
pair=true-or-FALSE(default) [e.g., pair=1 # base-pair only]
hbond=true-or-FALSE(default) [e.g., hbond=t # H-bonding info]
more=true-or-FALSE(default) [e.g., more=y # further details]
Required parameter:
url=URL-to-coordinate-file [e.g., url=https://files.rcsb.org/download/1ehz.pdb.gz]
model@coordinate-file [e.g., model@1ehz.cif]
# Only one must be specified. 'url' precedes 'model' when both are specified.
# The coordinate file must be in PDB or PDBx/mmCIF format, optionally gzipped.
Examples:
http -f http://api.x3dna.org/dssr url=https://files.rcsb.org/download/1ehz.pdb.gz
http -f http://api.x3dna.org/dssr model@1ehz.cif pair=1
# with 'curl'
curl http://api.x3dna.org/dssr -F 'url=https://files.rcsb.org/download/1ehz.pdb.gz'
curl http://api.x3dna.org/dssr -F 'model=@1msy.pdb' -F 'pair=1'
Note:
The web API has an upper limit on coordinate file size (gzipped): < 6 MB
Usage with 'http' (HTTPie):
http -f http://api.x3dna.org/snap [options] url=|model@
http http://api.x3dna.org/snap/help -- display this help message
Options:
json=true-or-FALSE(default) [e.g., json=true # JSON output]
hbond=true-or-FALSE(default) [e.g., hbond=t # H-bonding info]
Required parameter:
url=URL-to-coordinate-file [e.g., url=https://files.rcsb.org/download/1oct.pdb.gz]
model@coordinate-file [e.g., model@1oct.cif]
# Only one must be specified. 'url' precedes 'model' when both are specified.
# The coordinate file must be in PDB or PDBx/mmCIF format, optionally gzipped.
Examples:
http -f http://api.x3dna.org/snap url=https://files.rcsb.org/download/1oct.pdb.gz
http -f http://api.x3dna.org/snap model@1oct.cif json=1
# with 'curl'
curl http://api.x3dna.org/snap -F 'url=https://files.rcsb.org/download/1oct.pdb.gz'
curl http://api.x3dna.org/snap -F 'model=@1oct.cif' -F 'json=1'
Note:
The web API has an upper limit on coordinate file size (gzipped): < 6 MB
Usage with 'http' (HTTPie):
http http://api.x3dna.org/fiber/help # display this help message
http http://api.x3dna.org/fiber/list # show a list of available fiber models (56 in total)
http http://api.x3dna.org/fiber/str_id # build model 'str_id' in the range of [1, 56]
http http://api.x3dna.org/fiber/name # generate a model with common names as shown below:
A-DNA, B-dna, C_DNA, D-DNA, ZDNA, RNA, RNAduplex, PaulingTriplex, G4
Case does not matter, and the separator can be '-' or '_' or omitted.
So a-dna, A-dNA, a_DNA, or ADNA is valid for building an A-DNA model.
Options (via query strings, or form fields):
seq=base-sequence # A, C, G, T, U for generic model
repeat=number # number of repeats of the sequence
cif=1 # output file in mmCIF format
Examples with 'http' (HTTPie):
http http://api.x3dna.org/fiber/1 # model no. 1 (i.e., calf thymus A-DNA model)
http -f http://api.x3dna.org/fiber/1 seq=A3TTT repeat=2 # specific sequence, repeated twice
http http://api.x3dna.org/fiber/rna # single-stranded RNA model
http http://api.x3dna.org/fiber/rna-ds # double-stranded RNA model
http http://api.x3dna.org/fiber/pauling # the triplex model of Pauling & Corey
http http://api.x3dna.org/fiber/g4 # G-quadruplex model
# with 'curl'
curl http://api.x3dna.org/fiber/1
curl http://api.x3dna.org/fiber/1 -d 'seq=A3TTT' -d 'repeat=2'
curl http://api.x3dna.org/fiber/rna
curl http://api.x3dna.org/fiber/rna-ds
curl http://api.x3dna.org/fiber/pauling
curl http://api.x3dna.org/fiber/g4
Note:
The web API has two upper limits: repeats < 1,000, and nucleotides < 10,000.
The skmatic.x3dna.org website (see screenshot below) aims to showcase DSSR-enabled cartoon-block schematics of nucleic acid structures using PyMOL. It presents a simple interface to browse pre-calculated PDB entries with a set of default settings: long rectangular blocks for Watson-Crick base-pairs, square blocks for G-tetrads in G-quadruplexes, with minor-groove edges in black. Users can also specify an URL to a PDB- or mmCIF-formatted file or upload such an atomic coordinates file directly, and set several common options to customerize to the rendered image.
Moreover, a web API to DSSR-PyMOL schematics is available to allow for its easy integration into third-party tools.
Input a PDB id
Pre-calculated cartoon-block images together with summary information are available for PDB entries of nucleic-acid-containing structures. Note that gigantic structures like ribosomes that are only represented in mmCIF format are excluded from the resource. The base block images are most effective for small to medium-sized structures.
Here are a few examples:
- 1ehz, the crystal structure of yeast phenylalanine tRNA at 1.93-Å resolution
- 2lx1, the major conformation of the internal loop 5’GAGU/3’UGAG
- 2grb”, the crystal structure of an RNA quadruplex containing inosine-tetrad
- 4da3, the crystal structure of an intramolecular human telomeric DNA G-quadruplex 21-mer bound by the naphthalene diimide compound MM41
- 1oct, crystal structure of the Oct-1 POU domain bound to an octamer site
- 2hoj, the crystal structure of an E. coli thi-box riboswitch bound to thiamine pyrophosphate, manganese ions
Each entry is shown with images in six orthogonal perspectives: front, back, right, left, top, bottom. The ‘front’ image (upper-left in the panel) is oriented into the most-extended view with the DSSR --blocview option. The corresponding PyMOL session file and PDB coordinate file are available for download. One can also visualize the structure interactively via 3Dmol.js.
Sample PDB entries
Users can browse random samples of pre-calculated PDB entries. The number should be between 3 and 99, with a default of 12 entries (see below for an example). Simply click the ‘Submit’ button or the “Random samples (3 to 99)”: http://skmatic.x3dna.org/pdb_entry link to see results of randomly picked 12 PDB entries each time.
Specify a coordinate file
The atomic coordinate file must be in PDB or mmCIF format, and can be optionally gzipped (.gz). One can either specify an URL to or select a coordinate file. Several common options are available to allow for user customizations.
Web API help message
Usage with 'http' (HTTPie):
http -f http://skmatic.x3dna.org/api [options] url=|model@
http http://skmatic.x3dna.org/api/pdb/pdb_id -- for a pre-calculated PDB entry
http http://skmatic.x3dna.org/api/help -- display this help message
Options:
block_file=styles-in-free-text-format [e.g., block_file=wc-minor]
block_color=nt-selection-and-color [e.g., block_color='A:pink']
block_depth=thickness-of-base-block [e.g., block_depth=1.2]
r3d_file=true-or-FALSE(default) [e.g., r3d_file=true]
raw_xyz=true-or-FALSE(default) [e.g., raw_xyz=true]
Required parameter
url=URL-to-coordinate-file [e.g., url=https://files.rcsb.org/download/1ehz.pdb.gz]
model@coordinate-file [e.g., model@1ehz.cif]
# Only one must be specified. 'url' precedes 'model' when both are specified.
# The coordinate file must be in PDB or PDBx/mmCIF format, optionally gzipped.
Examples
http -f http://skmatic.x3dna.org/api block_file='wc-minor' model@1ehz.cif r3d_file=t
http -f http://skmatic.x3dna.org/api url=https://files.rcsb.org/download/1ehz.pdb.gz -d -o 1ehz.png
http http://skmatic.x3dna.org/api/pdb/1ehz -d -o 1ehz.png
# with 'curl'
curl http://skmatic.x3dna.org/api -F 'model=@1msy.pdb' -F 'block_file=wc-minor' -F 'r3d_file=1'
curl http://skmatic.x3dna.org/api -F 'url=https://files.rcsb.org/download/1ehz.pdb.gz' -o 1ehz.png
curl http://skmatic.x3dna.org/api/pdb/1ehz -o 1ehz.png
Sample images
While reading DNAproDB: an expanded database and web-based tool for structural analysis of DNA–protein complexes, I noticed SNAP and DSSR being mentioned. The detailed citations are as below:
Information about individual nucleotide–residue interactions is also provided, such as hydrogen bonding, interaction geometry (based on SNAP (10)), buried solvent accessible surface areas and identification of the interacting residue and nucleotide moieties …
DNAproDB assigns a geometry for every nucleotide–residue interaction identified using SNAP, a component of the 3DNA program suite (10). The residues for which probabilities are shown are those with planar side chains so that a stacking conformation can be defined.
Base pairing and base stacking between nucleotides are identified using the program DSSR (20).
SNAP and DSSR are two (relatively) new programs in the 3DNA software suite. As the author, I am always glad to see them being cited explicitly in literature. The fact that SNAP and DSSR are cited together by DNAproDB, however, is especially significant. I am aware of the initial version of DNAproDB, but I definitely like the updated one better. This is what I recently wrote in response to a question on the 3DNA Forum:
Regarding DNA-protein interactions in general, you may want to have a look of DNAproDB from the Remo Rohs laboratory. A new paper has just been published in NAR, ‘DNAproDB: an expanded database and web-based tool for structural analysis of DNA–protein complexes’.
I’ve no doubt that SNAP and DSSR would be widely used in applications related to DNA/RNA structural bioinformatics. DSSR (to a lesser extent, SNAP) represents my view of what a scientific software tool should be.
Recently I noticed two new citations to DSSR, an integrated software tool for dissecting the spatial structure of RNA. One is from the Yesselman et al. article Computational design of three-dimensional RNA structure and function in Nature Nanotechnology, and the other is from the Wang et al. article 3dRNA v2.0: An Updated Web Server for RNA 3D Structure Prediction in International Journal of Molecular Sciences.
Yesselman et al. has used DSSR in RNAMake for building the motif library. The relevant section is as follows:
We processed each RNA structure to extract every motif with Dissecting the Spatial Structure of RNA (DSSR)54 with the following command:
x3dna-dssr –i file.pdb –o file_dssr.out
We manually checked each extracted motif to confirm that it was the correct type, as DSSR sometimes classifies tertiary contacts as higher-order junctions and vice versa. For each motif collected from DSSR, we ran the X3DNA find_pair and analyze programs to determine the reference frame for the first and last base pair of each motif to allow for the alignment between motifs:
find_pair file.pdb 2> /dev/null stdout | analyze stdin >& /dev/null
It is worth noting the sentence that “DSSR sometimes classifies tertiary contacts as higher-order junctions and vice versa.” Presumably. the authors are referring to the inclusion of ‘isolated canonical pairs’ in junctions by default in DSSR. Overall, the default DSSR settings follow the most common practice in RNA literature. In the meantime, I am aware that the community may not agree on every detail. Thus DSSR provide many options (documented or otherwise) to cater for other potential use cases. See the Stems of junction structure have only one base pair and Junction definition threads on the 3DNA Forum for two examples. In the long run, DSSR is likely to help consolidate RNA nomenclature that can be applied in a pragmatic, consistent manner.
Note also that DSSR provides the reference frame of each identified base pair via the JSON option. Using 1ehz as an example, the following command provides detailed information about base pairs:
x3dna-dssr -i=1ehz.pdb --json --more | jq .pairs
In the 3dRNA 2.0 paper, DSSR is cited as below. This is the first time DSSR is integrated in the 3dRNA pipeline.
The predicted structures are built from the sequence and secondary structure, while the former is obtained from their native structures fetched from PDB (https://www.rcsb.org/), and the latter is calculated from DSSR (Dissecting the Spatial Structure of RNA) [39].
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.
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.
Nucleic acids structural bioinformatics starts with the identification of nucleotides (nts) from atomic coordinates. As biopolymers, RNA and DNA have standard IUPAC names of atoms for the five bases (see the Figure below), sugars (ending with prime, e.g., C1’, O2’), and the phosphate (P, OP1, and OP2). The atomic coordinates (in PDB or mmCIF format) from the Protein Data Bank (PDB) follow the convention.
Trained as a chemist, I am aware that the bases are aromatic, heterocyclic compounds (purines and pyrimidines). Moreover, the five standard bases (A, C, G, T, and U) also share a six-membered ring, with atoms named consecutively (N1, C2, N3, C4, C5, C6). This special feature can be employed to identify nts automatically, from PDB atomic coordinates. The ring skeleton is not influenced by protonation states, tautomeric forms, or modifications in base, sugar or phosphate. Early versions of 3DNA (up to v2.0) used only N1, C2, and C6 atoms to identify an nt: an additional N9 as purine, otherwise as pyrimidine. In 3DNA v2.3 and DSSR, the procedure has been refined to take advantage of all available rings atoms. It is thus more robust against distortions and still works even when any of the N1, C2, C6, or N9 atoms are mutated or missing. This blog post provides further technical details on how the method works.
The template used to identify nts is a purine, with nine base ring atoms. Purine is chosen since it contains atoms of the six-membered ring and N7, C8, and N9. Its atomic coordinates in PDB format are shown below. The coordinates are taken from ‘G’ in the standard reference frame ($X3DNA/config/Atomic_G.pdb). Using ‘A’ as reference won’t make any difference since the RMSD between them is only 0.038 Å.
ATOM 1 N9 G A 1 -1.289 4.551 0.000 1.00 0.00 N
ATOM 2 C8 G A 1 0.023 4.962 0.000 1.00 0.00 C
ATOM 3 N7 G A 1 0.870 3.969 0.000 1.00 0.00 N
ATOM 4 C5 G A 1 0.071 2.833 0.000 1.00 0.00 C
ATOM 5 C6 G A 1 0.424 1.460 0.000 1.00 0.00 C
ATOM 6 N1 G A 1 -0.700 0.641 0.000 1.00 0.00 N
ATOM 7 C2 G A 1 -1.999 1.087 0.000 1.00 0.00 C
ATOM 8 N3 G A 1 -2.342 2.364 0.001 1.00 0.00 N
ATOM 9 C4 G A 1 -1.265 3.177 0.000 1.00 0.00 C
The nt-identification process begins with a mapping of at least three atoms in the purine, followed by a least-squares fit between corresponding atoms. For the five standard bases and most modified ones, the RMSD is normally less than 0.12 Å, as seen in the Figure below. Even the unsaturated dihydrouridine in tRNA has an RMSD of less than 0.25 Å: for the yeast phenylalanine tRNA (PDB id: e1ehz), for example, it is 0.205 Å for H2U-16, and 0.226 Å for H2U-17. DSSR uses a cutoff of 0.28 Å, covering essentially all nucleotides in the PDB. As an extreme case, the DA1 residue on chain T of PDB id 4ki4 has only three base atoms: N7, C8, and N9 (i.e., no atoms from the six-membered ring). With an RMSD of only 0.005 Å, DSSR still takes it as an nt, properly assigned as ‘A’.
Molecular dynamics (MD) simulations sometimes produce heavily distorted bases, which is over the default cutoff. Users may change the cutoff to a larger value to accommodate such unusual cases.
In addition to dihydrouridine, the above Figure also shows pseudouridine (PSU), 1-methyladenosine (1MA), 4-thiouridine (4SU), and the heavily modified YYG in tRNA. They are all easily identified using the same scheme. Since the nt-identification method concentrates on base rings, modifications in sugar or the phosphate group do not pose any problem. For example, in tRNA 1ehz, DSSR also identifies O2’-methylguanosine (OMG) and O2’-methylcytidine (OMC) as modified nts.
Two special cases worth mentioning. The ligand IMD in PDB id 1r8e has a five-membered ring. Its atoms are named similarly to those of an nt, and the fitted RMSD is only 0.29 Å. IMD can be filtered out by its missing of the C6 atom and having an N1—C5 covalent bond. The ligand SPM in PDB id 355d is a linear molecule, and its RMSD (1.86 Å) is clearly far off to be taken as an nt.
Another particular case (of a different kind) is the abasic sites, especially in X-ray crystal structures in the PDB. By definition, abasic sites do not have base atoms available. Thus the described method is not applicable to their characterization as nts. As of v1.7.3-2017dec26, however, DSSR has also incorporated abasic sites into the analysis pipeline, by default. The program checks backbone linkage and residue name for appropriate nt assignment. The abasic sites could constitute part of (internal) loops which would otherwise be broken into segments by DSSR.
Overall, I feel confident to say that 3DNA-DSSR has practically solved the problem of identifying nts from atomic coordinates. The method detailed herein (and outlined in the DSSR paper) is simple and easy to understand/implement. Moreover, it has been extensively tested in real-world applications for well over a decade. I’ve yet to find a single case where it does not work as expected.
Over the past couple of months, I’ve further enhanced the DSSR-derived structural features for Q-quadruplexes (G4). One was the implementation of the single descriptor of intramolecular canonical G4 structures with three connecting loops recently proposed by Dvorkin et al. The descriptor contains the number of guanines in the G4 stem, the type and relative direction of loops linking G-tracts of the stem, and the groove-widths associated with lateral loops. For example, PDB entry 2GKU (see the DSSR-enabled PyMOL schematic image below, Fig. 1A) has the following DSSR output.
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-Lw-Ln) note=hybrid-1(3+1) UUDU anti-parallel
1 glyco-bond=ss-s groove=-wn- mm(<>,outward) area=14.24 rise=3.58 twist=16.8 nts=4 GGGG A.DG3,A.DG9,A.DG17,A.DG21
2 glyco-bond=--s- groove=-wn- pm(>>,forward) area=13.12 rise=3.71 twist=25.9 nts=4 GGGG A.DG4,A.DG10,A.DG16,A.DG22
3 glyco-bond=--s- groove=-wn- nts=4 GGGG A.DG5,A.DG11,A.DG15,A.DG23
strand#1 U DNA glyco-bond=s-- nts=3 GGG A.DG3,A.DG4,A.DG5
strand#2 U DNA glyco-bond=s-- nts=3 GGG A.DG9,A.DG10,A.DG11
strand#3 D DNA glyco-bond=-ss nts=3 GGG A.DG17,A.DG16,A.DG15
strand#4 U DNA glyco-bond=s-- nts=3 GGG A.DG21,A.DG22,A.DG23
loop#1 type=propeller strands=[#1,#2] nts=3 TTA A.DT6,A.DT7,A.DA8
loop#2 type=lateral strands=[#2,#3] nts=3 TTA A.DT12,A.DT13,A.DA14
loop#3 type=lateral strands=[#3,#4] nts=3 TTA A.DT18,A.DT19,A.DA20
The descriptor=3(-P-Lw-Ln) means that the G4 structure has three layers of G-tetrads, connected via three loops: the first is the Propeller loop in anti-clockwise (negative) direction, then the Lateral loop passing a wide groove anti-clockwise, and finally another Lateral loop passing a narrow groove, also anti-clockwise. The DSSR symbols follow those of Dvorkin et al. but with capital letters L, P, and D for lateral, propeller, and diagonal loops instead of lower case letters (l, p, d) to avoid using subscript for groove-width info. So the 2GKU descriptor 3(-P-Lw-Ln) from DSSR corresponds to 3(-p-lw-ln) of Dvorkin et al.
The DSSR-enabled, PyMOL-rendered, block image in Fig. 1A makes the three G-tetrad layers (squared green blocks) immediately obvious. Other base identities and stacking interactions also become clear — for example, the A24 (in red) stacks on the top G-tetrad, and T1-A20 pair stacks with the bottom G-tetrad.
Two other PDB entries (2LOD and 2KOW) are illustrated in Fig. 1B and Fig. 1C. They have different topologies than 2GKU (Fig. 1A). DSSR is able to characterize all of them consistently.
Figure 1. DSSR-enabled, PyMOL-rendered, block images of five G-quadruplexes. A in red, C in yellow, G (and G-tetrad) in green, and T in blue.
Another G4-related new feature in DSSR is the detection of V-shaped loops in noncanonical G4 structures where one of the four G-G columns (strands) that link adjacent G-tetrads is broken. Two of recent PDB examples with V-loops are shown in Fig. 1D (5ZEV) and Fig. 1E (6H1K). An excerpt of DSSR output for the PDB entry 6H1K is shown below.
List of 1 G4-helix
Note: a G4-helix is defined by stacking interactions of G4-tetrads, regardless
of backbone connectivity, and may contain more than one G4-stem.
helix#1[1] stems=[#1] layers=3 INTRA-molecular
1 glyco-bond=-sss groove=w--n mm(<>,outward) area=12.76 rise=3.47 twist=18.2 nts=4 GGGG A.DG2,A.DG19,A.DG15,A.DG26
2 glyco-bond=s--- groove=w--n pm(>>,forward) area=12.84 rise=3.07 twist=33.4 nts=4 GGGG A.DG1,A.DG20,A.DG16,A.DG27
3 glyco-bond=s--- groove=w--n nts=4 GGGG A.DG25,A.DG21,A.DG17,A.DG28
strand#1 DNA glyco-bond=-ss nts=3 GGG A.DG2,A.DG1,A.DG25
strand#2 DNA glyco-bond=s-- nts=3 GGG A.DG19,A.DG20,A.DG21
strand#3 DNA glyco-bond=s-- nts=3 GGG A.DG15,A.DG16,A.DG17
strand#4 DNA glyco-bond=s-- nts=3 GGG A.DG26,A.DG27,A.DG28
****************************************************************************
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=2 INTRA-molecular loops=3 descriptor=2(D+PX) note=UD3(1+3) UDDD anti-parallel
1 glyco-bond=s--- groove=w--n mm(<>,outward) area=12.76 rise=3.47 twist=18.2 nts=4 GGGG A.DG1,A.DG20,A.DG16,A.DG27
2 glyco-bond=-sss groove=w--n nts=4 GGGG A.DG2,A.DG19,A.DG15,A.DG26
strand#1 U DNA glyco-bond=s- nts=2 GG A.DG1,A.DG2
strand#2 D DNA glyco-bond=-s nts=2 GG A.DG20,A.DG19
strand#3 D DNA glyco-bond=-s nts=2 GG A.DG16,A.DG15
strand#4 D DNA glyco-bond=-s nts=2 GG A.DG27,A.DG26
loop#1 type=diagonal strands=[#1,#3] nts=12 GAGGCGTGGCCT A.DG3,A.DA4,A.DG5,A.DG6,A.DC7,A.DG8,A.DT9,A.DG10,A.DG11,A.DC12,A.DC13,A.DT14
loop#2 type=propeller strands=[#3,#2] nts=2 GC A.DG17,A.DC18
loop#3 type=diag-prop strands=[#2,#4] nts=5 GACTG A.DG21,A.DA22,A.DC23,A.DT24,A.DG25
****************************************************************************
List of 2 non-stem G4 loops (INCLUDING the two terminal nts)
1 type=lateral helix=#1 nts=5 GACTG A.DG21,A.DA22,A.DC23,A.DT24,A.DG25
2 type=V-shaped helix=#1 nts=4 GGGG A.DG25,A.DG26,A.DG27,A.DG28
Note that here a new loop type (diag-prop) and topology description symbol (X) are introduced. In developing DSSR in general, and G4-related features in particular, I’ve always tried to follow conventions widely used by the community. Whereas inconsistency exists, I pick up the ones that are in line with other parts of DSSR. For unique DSSR features lacking outside references, I came up my own nomenclature. When DSSR becomes more widely used, it may serve to standardize G4 nomenclatures.
