3DNA is a versatile, integrated software system for the analysis, rebuilding, and visualization of three-dimensional nucleic-acid-containing structures. The software is applicable not only to DNA (as the name 3DNA may imply) but also to complicated RNA structures and DNA-protein complexes. In 3DNA, structural analysis and model rebuilding are two sides of the same coin: the description of the structure is rigorous and reversible, thus allowing for its exact reconstruction based on the derived parameters. 3DNA automatically detects all non-canonical base pairs, base triplets and higher-order associations (collectively termed multiplets), and coaxially stacked helices; provides a comprehensive collection of fiber models of regular DNA and RNA helices; generates highly effective schematic presentations that reveal key features of nucleic-acid structures; performs undisturbed base mutations, and have facilities for the analysis of molecular dynamics simulation trajectories.

DSSR is an integrated software tool for dissecting the spatial structure of RNA. It is a representative of what would become the brand new version 3 of 3DNA. DSSR consolidates, refines, and significantly extends the functionality of 3DNA v2.x for RNA structural analysis. Among other features, DSSR denotes base-pairs by common names (e.g., WC, reverse WC, Hoogsteen A+U, reverse Hoogsteen A—U, wobble G—U, sheared G—A), the Saenger classification of 28 H-bonding types, and the Leontis-Westhof nomenclature of 12 basic geometric classes; determines double-helical regions, differentiates stems from helices, and provides a pragmatic definition of coaxial stacking interactions; identifies hairpin loops, bulges, internal loops, and multi-branch (junction) loops; characterizes pseudoknots of arbitrary complexity; outputs RNA secondary structure in commonly used formats (including the dot-bracket notation and connectivity table); identifies A-minor interactions, splayed-apart dinucleotide conformations, base-capping interactions, ribose zippers, G quadruplexes, i-motifs, kissing loops, U-turns, and k-turns etc. By connecting dots in RNA structural bioinformatics, it makes many common tasks simple and advanced applications feasible. DSSR comes with a professional User Manual, and some of its features have been integrated into Jmol and PyMOL. Moreover, the DSSR-Jmol paper, titled DSSR-enhanced visualization of nucleic acid structures in Jmol, has been featured in the cover image of the 2017 Web-server issue of Nucleic Acids Research (NAR).

3DNA version 3 is under active development. The SNAP program has been created from scratch for an integrated characterization of the three-dimensional Structures of Nucleic Acid-Protein complexes. Sharing the same new codebase as DSSR, SNAP works for DNA-protein as well as RNA-protein interactions. Other 3DNA v2.x programs (e.g., fiber, rebuild etc) are gradually distilled into version 3, and a new atomic coordinates-based homology searching tool is also being developed. In the end, 3DNA version 3 will consist of a suite of fully independent (as DSSR and SNAP) yet closely related programs, serving as cornerstones of DNA/RNA structural bioinformatics.

All 3DNA-related questions are welcome and should be directed to the 3DNA Forum. For the benefit of the community at large, I do not provide private support of 3DNA via email or personal message. As a general rule, I strive to provide a prompt and concrete response to each and every question posted on the Forum.

More info · Seeing is believing · Cover image · What’s new · 3DNA Forum · Download


Pauling's triplex model of nucleic acids is available in 3DNA

In 1953, Pauling and Corey published an influential paper, titled A proposed structure for the nucleic acids, in Proc. Natl. Acad. Sci. (PNAS). Key features of the proposed model is summarized in their Letter to Nature, Structure of the Nucleic Acids, published in Nature on February 21, 1953.

We have formulated a structure for the nucleic acids which is compatible with the main features of the X-ray diagram and with the general principles of molecular structure, and which accounts satisfactorily for some of the chemical properties of the substances. The structure involves three intertwined helical polynucleotide chains. Each chain, which is formed by phosphate di-ester groups and linking β-D-ribofuranose or β-D-deoxyribofuranose residues with 3′, 5′ linkages, has approximately twenty-four nucleotide residues in seven turns of the helix. The helixes have the sense of a right-handed screw. The phosphate groups are closely packed about the axis of the molecule, with the pentose residues surrounding them, and the purine and pyrimidine groups projecting radially, their planes being approximately perpendicular to the molecular axis. The operation that converts one residue to the next residue in the polynucleotide chain is rotation by about 105° and translation by 3.4 Å.

This triplex model of nucleic acids, with phosphates in the center and bases on the outside, turned out to be fundamentally flawed. Yet, it played a significant role by prompting Watson and Crick in their discovery of the DNA double helix structure. While I’ve been aware of the Pauling triplex model from long ago, I had not read the original Pauling & Corey PNAS paper. Not surprisingly, I did not know what the triplex structure really looks like, other than some general ideas.

In a recent trip to Rutgers, Dr. Wilma Olson and I discussed the applications of fiber models collected in 3DNA. She drew my attention to the Pauling triplex model, and showed me Table 1 of the PNAS paper (see below), where the atomic coordinates for a nucleic acid repeating unit are listed.

Atomic coordinates of the Pauling triplex

The cylindrical format is the same as that for the fiber models in 3DNA. It thus seems fitting to add this historically significant triplex model to the collection. Googling revealed many interesting historical notes and comments, e.g. The Pauling-Corey Structure of DNA, and a short video Linus Pauling’s triple DNA helix model, 3D animation with basic narration. However, I failed to find a program that I can use to generate such a triplex model with generic base sequence. I decided to add the fiber --pauling option so users can easily create such a triplex model in 3D, just as they do for a classic A- and B-DNA duplex. This process has turned out to be very educational (detailed below), and the end result should be of general interest.

3D image of the repeating unit (cytosine) in Pauling triplex

  • The left 3D image shows the nomenclature of atoms used by Pauling & Corey (see Table 1 above), which is dramatically different from current conventions. As an example, it should be the N1 atom of cytosine (a pyrimidine base), not N3, that is connected to the sugar C1′ atom in nowadays nomenclature. The corrections apply not only to base atoms, but also to the sugar and phosphate groups. The revised atom labeling (as used in the PDB) is illustrated in the 3D image on the right.
  • Table 1 corresponds to the ribose sugar since it contains an O2′ atom (see also the figure above). The triplex model constructed would be RNA, but can be ‘converted’ to DNA by simply removing the O2′ atom (see below).
  • Only the atomic coordinates for cytosine are listed in Table 1. The 3DNA mutate_bases program came handy to get the corresponding atomic coordinates for A, G, T, and U. This expansion allows for the generation of Pauling’s triplex models with an arbitrary combination of the five common bases (A, C, G, T, and U).
  • With the new fiber --pauling option, now users can conveniently generate a Pauling’s triplex RNA/DNA model as shown below. Note that the one dash variant -pauling also works fine, with the additional -dna for DNA deoxyribose sugar. The PDB file (Pauling-triplex-mixed.pdb) with mixed DNA sequences can be downloaded, and the corresponding 3D image in top and side views is shown in the following figure.
        fiber -pauling triplex-C10C10C10.pdb        # default: 10 Cs per strand
        fiber -pauling -seq=AAA triplex-A3A3A3.pdb  # 3 As per strand
        fiber -pauling -seq=AAAA:CCCC:GGGG Pauling-triplex-A4C4G4.pdb
        fiber -pauling -seq=ACGGUU,UUGGAC,GGAACC  Pauling-triplex-mixed.pdb
        fiber --pauling-dna -seq=ACGGTT,TTGGAC,GGAACC  Pauling-triplex-DNA.pdb

Sample Pauling DNA triplex generated with 3DNA

  • With 3DNA’s find_pair/analyze pair of programs, one can get the structural parameters corresponding to the Pauling triplex model. Not surprising, the repeating dinucleotide along each strand has a twist of 105°, and a rise of 3.4 Å. Notably, the sugar has a C2′-endo conformation.



3DNA fiber models

3DNA contains 55 fiber models compiled from literature, plus a derived RNA model (as of v2.1). To the best of my knowledge, this is the most comprehensive collection of regular DNA/RNA models. Please see Table 4 of the 2003 3DNA NAR paper for detailed structural features of these models and references.

The 55 models are based on the following works:

  • Chandrasekaran & Arnott (from #1 to #43) — the most well-known set of fiber models
  • Alexeev et al. (#44-#45)
  • van Dam & Levitt (#46-#47)
  • Premilat & Albiser (#48-#55)

The utility program fiber makes the generation of all these fiber models in a simple, consistent interface, and produces coordinate files in either PDB or PDBML format. Of those models, some can be built with an arbitrary sequence of A, C, G and T (e.g., A-/B-/C-DNA from calf thymus), while others are of fixed sequences (e.g., Z-DNA with GC repeats). The sequence can be specified either from command-line or a plain text file, in either lower, UPPER, or MixED cases.

Once 3DNA in properly installed, the command-line interface is the most versatile and convenient way to generate, e.g., a regular double-stranded DNA (mostly, B-DNA) of arbitrary sequence. The command-help message (generated with fiber -h) is as below:

        fiber - generate 55 fiber models based on Arnott and other's work
        fiber [OPTION] PDBFILE
        generate 55 fiber models based on the repeating unit from Arnott's
        work, including the canonical A-, B-, C- and Z-DNA, triplex, etc
        -xml     output structure coordinates in PDBML format
        -num     a structure identification number in the range (1-55)
        -m, -l   brief description of the 55 fiber structures
        -a, -1   A-DNA model (calf thymus)
        -b, -4   B-DNA (calf thymus, default)
        -c, -47  C-DNA (BII-type nucleotides)
        -d, -48  D(A)-DNA  ploy d(AT) : ploy d(AT) (right-handed)
        -z, -15  Z-DNA poly d(GC) : poly d(GC)
        -rna     for RNA with arbitrary base sequence
        -seq=string specifying an arbitrary base sequence
        -single  output a single-stranded structure
        -h       this help message (any non-recognized options will do)
        An structural identification number (symbol)
        fiber fiber-BDNA.pdb
            # fiber -4 fiber-BDNA.pdb
            # fiber -b fiber-BDNA.pdb
        fiber -a fiber-ADNA.pdb
        fiber -seq=AAAGGUUU -rna fiber-RNA.pdb
        fiber -seq=AAAGGUUU -rna -single fiber-ssRNA.pdb
        PDB file
        analyze, anyhelix, find_pair
        3DNA v2.3-2016sept06, created and maintained by Xiang-Jun Lu (PhD)

Please post questions/comments on the 3DNA Forum: http://forum.x3dna.org/

Moreover, the w3DNA, 3D-DART web-interfaces, and the PyMOL wrapper make it easy to generate a regular DNA (or RNA) model, especially for occasional users or for educational purposes.

In principle, nothing is worth showing off with regard to 3DNA’s fiber model generation functionality. Nevertheless, this handy tool serves as a clear example of the differences between a “proof of concept” and a pragmatic software application. I initially decided to work on this tool simply for my own convenience. At that time, I had access to A-DNA and B-DNA fiber model generators, each as a separate program. Moreover, the constructed models did not comply to the PDB format in atom naming, among other subtitles.

I started with the Chandrasekaran & Arnott fiber models which I had a copy of data files. However, there were many details to work out, typos to correct, etc. to put them in a consistent framework. For other models, I had to read each original publication, and to type raw atomic cylindrical coordinates into computer. Again, quite a few inconsistencies popped up between the different publications with a time span over decades.

Overall, it was a quite tedious undertaking, requiring great attention to details. I am glad that I did that: I learned so much from the process, and more importantly, others can benefit from my effort. As I put in the 3DNA Nature Protocol paper (BOX 6 | FIBER-DIFFRACTION MODELS),

In preparing this set of fiber models, we have taken great care to ensure the accuracy and consistency of the models. For completeness and user verification, 3DNA includes, in addition to 3DNA-processed files, the original coordinates collected from the literature.

For those who want to understand what’s going on under the hood, there is no better way than to try to reproduce the process using, e.g., fiber B-DNA as an example.

From the very beginning, I had expected the 3DNA fiber functionality to serve as a handy tool for building a regular DNA duplex of chosen sequence. Over the years, the fiber program has gradually attracted attention from the community. The recent PyMOL wrapper by Thomas Holder is a clear sign of its increased popularity, and has prompted me to write this post, adapted largely from the one titled Fiber models in 3DNA make it easy to build regular DNA helices (dated Friday, October 9, 2009).

See also PyMOL wrapper to 3DNA fiber models


Given below is the content of the README file for fiber models in 3DNA:

1. The repeating units of each fiber structure are mostly based on the
   work of Chandrasekaran & Arnott (from #1 to #43). More recent fiber
   models are based on Alexeev et al. (#44-#45), van Dam & Levitt (#46
   -#47) and Premilat & Albiser (#48-#55).

2. Clean up of each residue
   a. currently ignore hydrogen atoms [can be easily added]
   b. change ME/C7 group of thymine to C5M
   c. re-assign O3' atom to be attached with C3'
   d. change distance unit from nm to A [most of the entries]
   e. re-ordering atoms according to the NDB convention

3. Fix up of problem structures.
   a. str#8 has no N9 atom for guanine
   b. str#10 is not available from the disk, manually input
   c. str#14 C5M atom was named C5 for Thymine, resulting two C5 atoms
   d. str#17 has wrong assignment of O3' atom on Guanine
   e. str#33 has wrong C6 position in U3
   f. str#37 to #str41 were typed in manually following Arnott's
        new list as given in "Oxford Handbook of Nucleic Acid Structure"
        edited by S. Neidle (Oxford Press, 1999)
   g. str#38 coordinates for N6(A) and N3(T) are WRONG as given in the
        original literature
   h. str#39 and #40 have the same O3' coordinates for the 2nd strand

4. str#44 & 45 have fixed strand II residues (T)

5. str#46 & 47 have +z-axis upwards (based on BI.pdb & BII.pdb)

6. str#48 to 55 have +z-axis upwards

List of 55 fiber structures

id#  Twist   Rise        Structure description
    (dgrees)  (A)
 1   32.7   2.548  A-DNA  (calf thymus; generic sequence: A, C, G and T)
 2   65.5   5.095  A-DNA  poly d(ABr5U) : poly d(ABr5U)
 3    0.0  28.030  A-DNA  (calf thymus) poly d(A1T2C3G4G5A6A7T8G9G10T11) :
                                        poly d(A1C2C3A4T5T6C7C8G9A10T11)
 4   36.0   3.375  B-DNA  (calf thymus; generic sequence: A, C, G and T)
 5   72.0   6.720  B-DNA  poly d(CG) : poly d(CG)
 6  180.0  16.864  B-DNA  (calf thymus) poly d(C1C2C3C4C5) : poly d(G6G7G8G9G10)
 7   38.6   3.310  C-DNA  (calf thymus; generic sequence: A, C, G and T)
 8   40.0   3.312  C-DNA  poly d(GGT) : poly d(ACC)
 9  120.0   9.937  C-DNA  poly d(G1G2T3) : poly d(A4C5C6)
10   80.0   6.467  C-DNA  poly d(AG) : poly d(CT)
11   80.0   6.467  C-DNA  poly d(A1G2) : poly d(C3T4)
12   45.0   3.013  D-DNA  poly d(AAT) : poly d(ATT)
13   90.0   6.125  D-DNA  poly d(CI) : poly d(CI)
14  -90.0  18.500  D-DNA  poly d(A1T2A3T4A5T6) : poly d(A1T2A3T4A5T6)
15  -60.0   7.250  Z-DNA  poly d(GC) : poly d(GC)
16  -51.4   7.571  Z-DNA  poly d(As4T) : poly d(As4T)
17    0.0  10.200  L-DNA  (calf thymus) poly d(GC) : poly d(GC)
18   36.0   3.230  B'-DNA alpha poly d(A) : poly d(T) (H-DNA)
19   36.0   3.233  B'-DNA beta2 poly d(A) : poly d(T) (H-DNA  beta)
20   32.7   2.812  A-RNA  poly (A) : poly (U)
21   30.0   3.000  A'-RNA poly (I) : poly (C)
22   32.7   2.560  Hybrid poly (A) : poly d(T)
23   32.0   2.780  Hybrid poly d(G) : poly (C)
24   36.0   3.130  Hybrid poly d(I) : poly (C)
25   32.7   3.060  Hybrid poly d(A) : poly (U)
26   36.0   3.010  10-fold poly (X) : poly (X)
27   32.7   2.518  11-fold poly (X) : poly (X)
28   32.7   2.596  Poly (s2U) : poly (s2U) (symmetric base-pair)
29   32.7   2.596  Poly (s2U) : poly (s2U) (asymmetric base-pair)
30   32.7   3.160  Poly d(C) : poly d(I) : poly d(C)
31   30.0   3.260  Poly d(T) : poly d(A) : poly d(T)
32   32.7   3.040  Poly (U) : poly (A) : poly(U) (11-fold)
33   30.0   3.040  Poly (U) : poly (A) : poly(U) (12-fold)
34   30.0   3.290  Poly (I) : poly (A) : poly(I)
35   31.3   3.410  Poly (I) : poly (I) : poly(I) : poly(I)
36   60.0   3.155  Poly (C) or poly (mC) or poly (eC)
37   36.0   3.200  B'-DNA beta2  Poly d(A) : poly d(U)
38   36.0   3.240  B'-DNA beta1  Poly d(A) : poly d(T)
39   72.0   6.480  B'-DNA beta2  Poly d(AI) : poly d(CT)
40   72.0   6.460  B'-DNA beta1  Poly d(AI) : poly d(CT)
41  144.0  13.540  B'-DNA  Poly d(AATT) : poly d(AATT)
42   32.7   3.040  Poly(U) : poly d(A) : poly(U) [cf. #32]
43   36.0   3.200  Beta Poly d(A) : Poly d(U) [cf. #37]
44   36.0   3.233  Poly d(A) : poly d(T) (Ca salt)
45   36.0   3.233  Poly d(A) : poly d(T) (Na salt)
46   36.0   3.38   B-DNA (BI-type nucleotides; generic sequence: A, C, G and T)
47   40.0   3.32   C-DNA (BII-type nucleotides; generic sequence: A, C, G and T)
48   87.8   6.02   D(A)-DNA  ploy d(AT) : ploy d(AT) (right-handed)
49   60.0   7.20   S-DNA  ploy d(CG) : poly d(CG) (C_BG_A, right-handed)
50   60.0   7.20   S-DNA  ploy d(GC) : poly d(GC) (C_AG_B, right-handed)
51   31.6   3.22   B*-DNA  poly d(A) : poly d(T)
52   90.0   6.06   D(B)-DNA  poly d(AT) : poly d(AT) [cf. #48]
53  -38.7   3.29   C-DNA (generic sequence: A, C, G and T) (depreciated)
54   32.73  2.56   A-DNA (generic sequence: A, C, G and T) [cf. #1]
55   36.0   3.39   B-DNA (generic sequence: A, C, G and T) [cf. #4]
List 1-41 based on Struther Arnott: ``Polynucleotide secondary structures:
     an historical perspective'', pp. 1-38 in ``Oxford Handbook of Nucleic
     Acid Structure'' edited by Stephen Neidle (Oxford Press, 1999).

     #42 and #43 are from Chandrasekaran & Arnott: "The Structures of DNA
     and RNA Helices in Oriented Fibers", pp 31-170 in "Landolt-Bornstein
     Numerical Data and Functional Relationships in Science and Technology"
     edited by W. Saenger (Springer-Verlag, 1990).

#44-#45 based on Alexeev et al., ``The structure of poly(dA) . poly(dT)
     as revealed by an X-ray fiber diffraction''. J. Biomol. Str. Dyn, 4,
     pp. 989-1011, 1987.

#46-#47 based on van Dam & Levitt, ``BII nucleotides in the B and C forms
     of natural-sequence polymeric DNA: a new model for the C form of DNA''.
     J. Mol. Biol., 304, pp. 541-561, 2000.

#48-#55 based on Premilat & Albiser, ``A new D-DNA form of poly(dA-dT) .
     poly(dA-dT): an A-DNA type structure with reversed Hoogsteen Pairing''.
     Eur. Biophys. J., 30, pp. 404-410, 2001 (and several other publications).



PyMOL wrapper to 3DNA fiber models

Recently, I heard from Thomas Holder, the PyMOL Principal Developer (Schrödinger, Inc.), that he had written a wrapper to the 3DNA fiber command. This PyMOL wrapper is implemented as part of his versatile PSICO library (see the PyMOL Wiki page Psico for details), and exposes the 55 fiber models based on Arnott and other’s work to the wide PyMOL user community. Moreover, the wrapper can be accessed directly from PyMOL (without installing PSICO), as shown below with an example:

PyMOL> run https://raw.githubusercontent.com/speleo3/pymol-psico/master/psico/creating.py

The resulting fiber model is the default B-form DNA of calf thymus, with twist of 36.0° and rise of 3.375 Å (see figure below). Note that cases in base sequence do not matter, so fiber ctagcg or fiber CTAgcg will give the same result.

The 3DNA fiber tool in PyMOL

Running PyMOL>help fiber gives the following detailed usages info, which should be sufficient to get one started with this fiber tool in PyMOL.

PyMOL> help fiber


    Run X3DNA's "fiber" tool.

    For the list of structure identification numbers, see for example:


    fiber seq [, num [, name [, rna [, single ]]]]


    seq = str: single letter code sequence or number of repeats for
    repeat models.

    num = int: structure identification number {default: 4}

    name = str: name of object to create {default: random unused name}

    rna = 0/1: 0=DNA, 1=RNA {default: 0}

    single = 0/1: 0=double stranded, 1=single stranded {default: 0}


    # environment (this could go into ~/.pymolrc or ~/.bashrc)
    os.environ["X3DNA"] = "/opt/x3dna-v2.3"

    # B or A DNA from sequence
    fiber CTAGCG
    fiber CTAGCG, 1, ADNA

    # double or single stranded RNA from sequence
    fiber AAAGGU, name=dsRNA, rna=1
    fiber AAAGGU, name=ssRNA, rna=1, single=1

    # poly-GC Z-DNA repeat model with 10 repeats
    fiber 10, 15 

Thanks to Thomas, for making another connection between PyMOL and 3DNA/DSSR. The other one is the DSSR-plugin for PyMOL to create “block” shaped cartoons for nucleic acid bases and base pairs.

See also 3DNA fiber models



3DNA C source code is available

As of release v2.3-2016sept06, the C source code of the 3DNA software package is available. The code can be found in the $X3DNA/src folder of the distributed tarballs for Linux, Mac OS X, and Windows. Since 3DNA is written in pure ANSI C, it can be compiled without changes on any platform with a modern C compiler.

The original codebase of 3DNA was written around year 2000. Up until v2.3, the infrastructure of 3DNA has remained stable for 16 years. During the time, 3DNA has been widely adopted in other bioinformatics pipelines and cited over 1,500 times. Over the years, I’ve received quite a few requests for 3DNA source code. However, due to complications of various factors (including software licensing), 3DNA had only been distributed in executable forms for the crucial C programs. Now, the C code of 3DNA is finally open source!

As before, users need to register on the 3DNA Forum to download the software. The download page also includes x3dna-v2.0.tar.gz that accompanied the 2008 Nature Protocols paper, and x3dna-v1.5.tar.gz that corresponded to the 2003 Nucleic Acids Research paper. Other than minor revisions to pass strict gcc compiler options, the v1.5 and v2.0 codebases are kept as they were. 3DNA is backward-compatible as far as the key base-pair parameters are concerned. Moreover, between v1.5 and v2.0, the command-line interface stays the same. The two previous versions are released for historical reasons. For example, one may notice some obvious “similarities” between 3DNA v1.5 and RNAView.

The development of DSSR and SNAP will push 3DNA into a brand new version (v3), which contains significant changes in functionality and interface, and is no longer compatible with previous versions. I intend to keep 3DNA v2.3 in a ‘maintenance’ mode: no new features are planed, but bug reports and user questions will be promptly addressed on the 3DNA Forum, as always. Making 3DNA open source should help further prompt its adoptions, and adaptations in structural bioinformatics of nucleic acids.

There are numerous types of software licenses, but none of them seems to be a good fit for my purpose. As a result, I’ve come up with a permissive “citation-ware” license with contents as below:

3DNA is a suite of software programs for the analysis,
rebuilding and visualization of 3-Dimensional Nucleic Acid
structures. Permission to use, copy, modify, and distribute
this suite for any purpose, with or without fee, is hereby
granted, and subject to the following conditions:

At least one of the 3DNA papers must be cited, including the
following two primary ones:

   1. Lu, X. J., & Olson, W. K. (2003). "3DNA: a software
      package for the analysis, rebuilding and visualization
      of three‐dimensional nucleic acid structures." Nucleic
      Acids Research, 31(17), 5108-5121.

   2. Lu, X. J., & Olson, W. K. (2008). "3DNA: a versatile,
      integrated software system for the analysis,
      rebuilding and visualization of three-dimensional
      nucleic-acid structures." Nature Protocols, 3(7),


Any 3DNA-related questions, comments, and suggestions are
welcome and should be directed to the open 3DNA Forum



The DSSR --block-color option

Upon user requests, I’ve recently introduced the --block-color option to DSSR, available as of v1.5.2-2016apr02. As its name implies, the --block-color option facilitate user customization of PyMOL rendered colors of the base rectangular blocks or their edges (e.g., the minor-groove) directly from the command-line. A simple example goes like this: --block-color='A blue; T red', which makes A colored blue and T colored red. As detailed below, the new option is very flexible with regard to the specification of colors, bases, or some edges to highlight. Before that, a little background is in order.

Background info

The DSSR cartoon-block representation follows the color convention of the original 3DNA blocview script, where A is red; C is yellow; G is green; T is blue; and U is cyan. If I remember correctly, the blocview coloring was based on the scheme adopted by the Nucleic Acid Database (NDB). To allow for some flexibility, 3DNA includes a config file named $X3DNA/config/raster3d.par where users can change the RGB values of the corresponding bases. However, I do not know if any user has ever bothered to play around with the configuration file for customized base colors.

Over the years, blocview-generated images have become popular, due to its simplicity, and (maybe more importantly) its endorsement by the NDB and PDB for nucleic acid structures. Via NDB, the blocview-generated images have also been used in RNA FRABASE 2.0 and RNA Structure Atlas. Nevertheless, the blocview script has several dependencies: MolScript for protein or DNA/RNA backbone ribbons, render from Raster3D for rendering, and ImageMagick for image processing. Moreover, the blocview script used by NDB/PDB is (likely to be) based on 3DNA v1.5, the last version before I left Rutgers in 2002.

Over the years, 3DNA has been continuously refined, with significant changes introduced in v2.0 around 2008 to accompany the Nature Protocols paper. Currently at v2.3, the codebase for 3DNA version 2 is in maintenance mode: the software will still be supported with identified bugs fixed, but no more new feature is planned. 3DNA version 3, as represented by DSSR and SNAP, is the way to go.

DSSR has no third-party dependencies

While creating DSSR, I set it as one of the design goals to make the program fully self-contained, without any third-party dependencies. Connections to other tools are clearly delineated via text files. If anything goes wrong, one can easily identify where the problem is. Experience over the past few years has unambiguously proved the effectiveness of this zero-dependency approach. Other than being directly distributed with an operating system, DSSR is the easiest to get up and running. Moreover, DSSR can be easily integrated into other pipelines, including Jmol and PyMOL, among many other bioinformatics tools.

For the cartoon-block representation, DSSR produces .r3d files that can be loaded into PyMOL, mixed and matched with other visualization styles PyMOL has to offer. No more direct dependencies on MolScript, Raster3D, and ImageMagick as is the case for blocview. It is also worth mentioning that DSSR does not need PyMOL to run. DSSR and PyMOL are connected via .r3d files, a process which can be streamlined with the Dssr_block PyMOL plugin.

DSSR releases before v1.5.2-2016apr02 have the color coding of base blocks fixed within the source code, following the default style of blocview. Over the past few months, I’ve received at least two explicit requests on customizing the default colors of DSSR-generated base blocks. The --block-color option has been introduced for this purpose.

Details of the --block-color option

The general format of the option is as follows:

--block-color='id color [; id2 color2 ...]'
  • id can be A, C, G, T, U, or the degenerated IUPAC code, including R, Y, N etc. See UPAC nucleotide code for details.
  • id can also be minor, major, upper, bottom, wc-edge to specify one of the six faces of a 3D rectangular block. See Fig.1D of the DSSR paper for details.

Fig.1D (DSSR 2015 NAR paper)

  • id can further be GC, AT, GU, pair, and variants thereof, to specify the colors of the corresponding long base-pair rectangular blocks.
  • color can be a common name (144 total), as specified in the RGB Color website. For example, red, magenta, light gray etc.
  • color can also be a single number in the range [0, 1] or [0, 255] to specify a shade of gray. DSSR repeat the number twice to get the RGB triple consisting of the same number.
  • color can further be a set of three space-delimited numbers to specify the RGB triple. Again, the number can be in [0, 1] or [0, 255]. Moreover, the three numbers can be put in square brackets. For example --block-color='A 0 1 1' and --block-color='A [0 1 1]' specify adenine to be colored with RGB triple [0 1 1] (aqua/cyan, corresponding to --block-color='A cyan').
  • More than one identity (bases) can be specified, separated by ; (,, :, or | also works). Note: within the PyMOL dssr_block plugin, only | or : can be used as a separator: comma (,) or semicolon (;) cannot be used as a separator within a PyMOL command argument (thanks to Thomas Holder for drawing this point to my attention).
  • Case does not matter when specifying id or color. So either ‘A’ or ‘a’, and ‘blue’ or ‘Blue’ or ‘BLUE’ can be used to make adenine blue: --block-color='a blue'.

Some example usages

While the above description may appears to be quite complicated, the actual usage of the --block-color option is very straightforward. As always, the cases are best made with concrete examples, as shown below using the classic Dickerson B-DNA dodecamer 355d.

# all bases in blue
x3dna-dssr -i=355d.pdb --cartoon-block=orient --block-color='N blue' -o=355d-all-blue.pml
# all WC-pairs in red, with the minor-groove edge in 'dim gary'
x3dna-dssr -i=355d.pdb --cartoon-block=orient --block-color='wc-pair red; minor dim gray' -o=355d-pair-minor.pml
# thymine (T) in purple, and the upper (+z) face in white
# see Figure below, which shows the two bases in WC-pairs are anti-parallel
x3dna-dssr -i=355d.pdb --cartoon-block=orient --block-color='T purple; upper 1' -o=355d-T-upper.pml

T-colord purple, +z (upper) faces white



Cartoon-block representation of quadruplex-duplex interface

Recently I read the article titled Structural Insights into the Quadruplex−Duplex 3′ Interface Formed from a Telomeric Repeat: A Potential Molecular Target by Krauss et al.. I quickly ran DSSR on the corresponding PDB entry is 5dww. Not surprisingly, DSSR can automatically identify reported key structural features (see output file 5dww.out for details), including the TAT triplet at the quadruplex−duplex junction, and the three G-quartets. Note that the result is based on biological assembly 1 in PDB file 5dww.pdb1 since the asymmetric unit contains four such molecules.

List of 4 multiplets
   1 nts=3 TAT 1:A.DT17,1:A.DA19,1:B.DT7
   2 nts=4 GGGG 1:A.DG1,1:A.DG5,1:A.DG9,1:A.DG14
   3 nts=4 GGGG 1:A.DG2,1:A.DG6,1:A.DG10,1:A.DG15
   4 nts=4 GGGG 1:A.DG3,1:A.DG7,1:A.DG11,1:A.DG16

As its title suggests, however, this blog post is about the cartoon-block representations. Four styles of such schematics are shown below, which can all be easily generated using DSSR/PyMOL.

Cartoon-block of 5dww in default style Cartoon-block of 5dww with base-pair blocks
in default style with base-pair blocks
Cartoon-block of 5dww with minor-groove highlighted Cartoon-block of 5dww with top-face highlighted
minor-groove highlighted top-face highlighted

The cartoon-block representations possess unique features not seen elsewhere. With the help of the dssr_block in PyMOL, they are extremely easy to generate. Such schematics are likely to become popular in illustrations of nucleic acid structures.



Integrating DSSR into Jmol and PyMOL

Over the past couple of years, one of the most significant achievements of DSSR has been its integration into Jmol and PyMOL, two widely used molecular graphics programs. None of the projects had been ‘planned’, and I am honored to have the opportunities collaborating directly with Bob Hanson (Jmol) and Thomas Holder (PyMOL). The integrations make salient features of DSSR readily accessible to the Jmol and PyMOL user communities. Moreover, Jmol and PyMOL take different approaches to interoperate with DSSR, and so far they have employed separate features that the program has to offer.

Key features of DSSR

DSSR was implemented in strict ANSI C as a self-contained command-line program. The binaries for common operating systems (Mac OS X, Linux and Windows) are tiny (<1MB), and without runtime dependencies on third-party libraries. DSSR also comes with an extensive PDF user manual.

Since its initial release in early 2013, DSSR has been continuously refined/expanded based on user feedback and my improved knowledge of RNA structures. User questions are always promptly addressed on the public 3DNA Forum. Over the years, DSSR has gradually established itself as an accountable software product.

The small size, zero configuration, extensive features, and robust performance make DSSR ideal to be integrated into other bioinformatics tools.

DSSR and Jmol

From the very beginning, Jmol has been employing a web-service at Columbia University, where all DSSR analyses take place. In addition to the sample DSSR-Jmol web interface, DSSR is also directly accessible from the console (see Fig.1 below). Jmol includes a sophisticated SQL syntax to drill down the various DSSR-derived structure features. Search ‘DSSR’ on the Jmol/JSmol interactive scripting documentation for details.

DSSR is accessible in Jmol console via scripting Fig. 1 DSSR is available from the Jmol/JSmol console via scripting.

The initial version of the integration (Jmol v14.2) was facilitated by the DSSR --jmol option to produce a Jmol-specific (e.g., residue id [C]2658:A) plain text output. However, ad hoc text file are rigid and fragile for programs to communicate with. As DSSR had been evolving, changes to existing features or newly added functionality were known to break the established DSSR-Jmol interface. Having to write extra code to maintain the same old --jmol output did not feel right.

JSON (JavaScript Object Notation) came to the rescue! The current DSSR-Jmol integration (Jmol v14.4) takes advantage of JSON, a standard, lightweight data-interchange format. Since JSON is structured, parsing its contents is straightforward. DSSR and Jmol can evolve independently, as always, but they no longer need to worry about touching each other’s toes.

Overall, Jmol has incorporated the most fundamental analysis features of DSSR. The Jmol SQL mini-language is very powerful for selecting arbitrary DSSR parameters. Background information about this collaboration can be found in the blog post Jmol and DSSR.


So far, the DSSR-PyMOL integration has focused on visualization, i.e., the cartoon-block schematic representations of DNA/RNA structures. Moreover, instead of relying on a remote DSSR web-service as for Jmol, the PyMOL dssr_block command calls a locally installed DSSR executable for the job. As illustrated in the blogpost DSSR base blocks in PyMOL, interactively, the ‘dssr_block’ command makes it trivial to incorporate the highly effective rectangular blocks into PyMOL.

From early on, 3DNA includes the blocview script (first written in Perl, later converted to Ruby) to generate schematic images in the ‘best view’, by combining block representation of bases with backbone ribbon of proteins or nucleic acids. The script is essentially a glue, calling MolScript, Raster3D, ImageMagick, and several 3DNA utility programs to perform various tasks. With these dependencies, it’s a bit involved to set up blocview. Nevertheless, the resultant images are simple and revealing, and are still being used by NDB and RCSB PDB (among others) as of today.

DSSR does not depend on MolScript and Raster3D, or any other programs to generate .r3d output of rectangular blocks. The schematic blocks can be directly fed into PyMOL, combined with other representations, and ray-traced for high resolution images. The integration of DSSR into PyMOL by the dssr_block command is likely to prompt an even wider adoption of the cartoon-block representation. In this regard, it is well worth noting the news item “dssr_block is a wrapper for DSSR (3dna) and creates block-shaped nucleic acid cartoons” on the main page of PyMOLWiki (see Fig. 2 below). It will certainly bring this neat feature into the attention of many PyMOL users.

dssr_block news item on PyMOLWiki
Fig. 2 Screenshot of the PyMOLWiki main page (2016-01-27) with ‘dssr_block’ in the news. A sample cartoon-block image of 355d is inserted as an example.

Integration of DSSR analysis results into PyMOL is underway, using the same JSON output. Before long, PyMOL users should be able to have access to the numerous DNA/RNA structural features derived by DSSR as in Jmol, along with the cartoon-block images enabled by dssr_block. Background information about DSSR-PyMOL can be found in blog post Open invitation on writing a DSSR plugin for PyMOL.


  • The DSSR-Jmol and DSSR-PyMOL integrations are two salient examples of what can be achieved via direct collaboration of dedicated scientists with complementary expertise. In addition to benefit the involved projects in particular and the (structural biology) community at large, technical and scientific advances are more likely to be achieved.
  • Both projects are still on going, with continued refinements of existing functionality and additions of new features. As an example, it is desirable and likely that Jmol would allow local access to DSSR for efficiency and data privacy.
  • JSON is the way to go for connecting DSSR to the outside world. Period. The obsolete --jmol will be removed from the next release of DSSR (v1.5). The default plain text output is useful for easy comprehension and will stilled be maintained. But do not count on its exact format for computer parsing — occasional changes to existing items are likely, and new features are bound to be added.
  • If you’d like to incorporate DSSR into your pipeline and need some customizations of its output, please let me know. It’s always easier to set things right at the source than to fix them downstream. Where practical, I’ll try to implement your requested features, quickly. Working together, we can and will build a better world.



Characterization of base-pair geometry

This post is a recap of the recently introduced ‘simple’ base-pair (bp) parameters (Fig. 1) useful for describing non-Waton-Crick pairs, and the highly effective cartoon-block representations of nucleic acid structures. Both features are readily available from 3DNA/DSSR, as detailed here using four examples of representative DNA/RNA structures (Fig. 2). Links to related blog posts are provided at the end.

Note added on Feb. 2, 2016: in fact, this post had been intended to supplement a short communication titled Characterization of base-pair geometry that Dr. Wilma Olson and I recently contributed to the January 2016 issue of Computational Crystallography Newsletter (CCN). That’s why the URL of this post is ‘http://home.x3dna.org/highlights/CCN-on-base-pair-geometry’ instead of what one would expect from the title. The data files, scripts, images, and linked herein should enable interested users a thorough understanding of the ‘simple’ base-pair parameters. If you have problems in reproducing our reported results, please do not hesitate to let me know (publicly). You are welcome to either leave comments to this post or ask any related questions on the 3DNA Forum.

Six rigid-body parameters

Schematic diagram of six rigid-body base-pair parameters

Fig. 1: Schematic diagrams of the six rigid-body parameters commonly used for the characterization of base-pair geometry.

Cartoon-block representations

Cartoon-block representations

Fig. 2: DSSR-introduced cartoon-block representations of DNA and RNA structures that combine PyMOL cartoon schematics with color-coded rectangular base blocks: A, red; C, yellow; G, green; T, blue; and U, cyan. (A) The Dickerson B-DNA dodecamer solved at 1.4-Å resolution [PDB id: 355d (Shui et al., 1998)], with significant negative Propeller. (B) The Z-DNA dodecamer [PDB id: 4ocb (Luo et al., 2014)], with virtually co-planar C–G pairs at the ends, and noticeable Buckle in the middle. © The GUAA tetraloop mutant of the sarcin/ricin domain from E. coli 23 S rRNA [PDB id: 1msy (Correll et al., 2003)], with large Buckle in the A+C pair, and base-stacking interactions of UAA in the GUAA tetraloop (upper-right corner). (D) The parallel double-stranded poly(A) RNA helix [PDB id: 4jrd (Safaee et al., 2013)], with up to +14° Propeller. The simple, informative cartoon-block representations facilitate understanding of the base interactions in small to mid-sized nucleic acid structures like these. The base identity, pairing geometry, and stacking interactions are obvious.

Scripts and data files (Lu-CCN-examples.tar.gz)

find_pair 355d.pdb | analyze   # 355d.out
x3dna-dssr -i=355d.pdb -more -o=355d-dssr.out
x3dna-dssr -i=355d.pdb --cartoon-block -o=355d.pml

find_pair 4jrd.pdb | analyze   # 4jrd.out
x3dna-dssr -i=4jrd.pdb -more -o=4jrd-dssr.out
x3dna-dssr -i=4jrd.pdb --cartoon-block -o=4jrd.pml

find_pair 1msy.pdb | analyze   # 1msy.out
x3dna-dssr -i=1msy.pdb -more -o=355d-dssr.out
x3dna-dssr -i=1msy.pdb --cartoon-block -o=1msy.pml

find_pair --symm 4ocb.pdb1 | analyze --symm  # 4ocb.out
x3dna-dssr -i=4ocb.pdb1 --symm -more -o=4ocb-dssr.out
x3dna-dssr -i=4ocb.pdb1 --symm --cartoon-block -o=4ocb.pml

Please note the following points:

  • The above examples are based on 3DNA v2.3-2016jan20 and DSSR v1.4.8-2016jan16.
  • All data files (including PyMOL ray-traced PNG images used in Fig. 2) are packed into a tarball named Lu-CCN-examples.tar.gz for download.
  • For PDB entry 4ocb, the biological unit (with suffix .pdb1) is used to get a complete duplex structure. The symm option must be specified.
  • PDB files are used in the above illustration. In fact, the corresponding mmCIF files (.cif) also work just fine.
  • The DSSR-derived .pml files can be fed into PyMOL for rendering. In addition to the directly generated *.pml files (e.g., 355d.pml), the PyMOL transformed version (i.e., orient; turn z, -90) are also included, with names *-orient.pml (e.g., 355d-orient.pml). The PNG images (as shown in Fig. 2) are ray-traced using these reoriented pml files for the most extended vertical view.
  • The ‘simple’ base-pair parameters for 4jrd is shown below.
This structure contains 10 non-Watson-Crick (with leading *) base pair(s)
Simple base-pair parameters based on RC8--YC6 vectors
      bp        Shear    Stretch   Stagger    Buckle  Propeller  Opening  angle
*    1 A+A      -7.96      0.41     -0.03    -13.64     -4.06   -179.47   14.2
*    2 A+A      -7.86      0.38     -0.33    -10.20     -3.53   -179.34   10.8
*    3 A+A      -7.96      0.43      0.02    -10.15      5.23    179.91   11.4
*    4 A+A      -7.95      0.50      0.10     -9.24      8.04    179.15   12.2
*    5 A+A      -7.95      0.46      0.08     -7.36     10.12   -179.98   12.5
*    6 A+A      -7.97      0.60      0.06     -5.15     12.87   -176.75   13.9
*    7 A+A      -7.88      0.66     -0.02     -7.82     11.89   -179.55   14.2
*    8 A+A      -7.91      0.56     -0.05     -7.03     13.68    179.22   15.4
*    9 A+A      -7.94      0.47     -0.03     -3.78     13.76   -179.24   14.3
*   10 A+A      -7.92      0.42      0.10     -3.03      4.34   -178.91    5.3

Related posts

Comment [2]


DSSR base blocks in PyMOL, interactively

In early 2015, Thomas Holder (the PyMOL Principal Developer at Schrodinger) and I agreed to work together on connecting DSSR to PyMOL. Moreover, we called for the community’s involvement in writing a DSSR plugin for PyMOL and received a few enthusiastic replies. Over the past few months, many significant progresses have been made in DSSR, including an article titled DSSR: an integrated software tool for dissecting the spatial structure of RNA published in Nucleic Acids Research (NAR) and a more streamlined DSSR-Jmol integration based on the --json output.

From the very beginning, Thomas and I had envisioned that the DSSR-PyMOL integration would include two components: one is to bring DSSR-derived RNA/DNA structural features into PyMOL (similar to the DSSR-Jmol interface, funcationality-wise), and the other is to render DSSR’s simple yet informative base-rectangular representations with PyMOL. While the ‘analysis’ component is a work in progress, the ‘visualization’ part is ready for the community to take advantage of.

Thomas has written a Python script named dssr_block.py. When the script is run in PyMOL, it adds the “dssr_block” command. The dssr_block.py script is less than 100 lines including documentation, with the real code taking no more than half of the total line number. The detailed documentation section (with two examples), when condensed, is as follows:

    Create a nucleid acid cartoon with DSSR
    dssr_block [selection [, state [, block_file [, block_depth [, name [, exe]]]]]]
    selection = str: atom selection {default: all}
    state = int: object state (0 for all states) {default: -1, current state}
    block_file = face|edge|wc|equal|minor|gray {default: face}
    block_depth = float: thickness of rectangular blocks {default: 0.5}
    name = str: name of new CGO object {default: dssr_block##}
    exe = str: path to "x3dna-dssr" executable {default: x3dna-dssr}
    fetch 1ehz, async=0
    as cartoon
    set cartoon_ladder_radius, 0.1
    set cartoon_ladder_color, gray
    set cartoon_nucleic_acid_mode, 1
    # multi-state
    fetch 2n2d, async=0
    dssr_block 2n2d, 0
    set all_states

Download the dssr_block.py script into a folder (directory) of your choice. Within PyMOL command window, type:

run dssr_block.py  # to make the 'dssr_block' command avaible
help dssr_block    # to get the help message, with contents shown above

The resultant cartoon-block image for running the documented commands (except for the additional orient command for best view) for case 1ehz is shown in Fig. 1 below.

DSSR block image for tRNA (1ehz)
Fig. 1: Cartoon-block image generated by dssr_block.py for PDB entry 1ehz (yeast phenylalanine tRNA)

For the NMR ensemble 2n2d, the corresponding image (after running orient) is illustrated in Fig. 2 as follows:

DSSR block image for an NMR ensemble (2n2d)
Fig. 2: Cartoon-block image generated by dssr_block.py for PDB entry 2n2d (an NMR ensemble).

In addition to the default settings, DSSR offers quite a few variations for the size and coloring of rectangular blocks, as demonstrated in Fig.3. The main settings are through the block_file option in PyMOL (note the underscore), corresponding to DSSR --block-file (or --block_file). The corresponding PyMOL commands are also listed for your reference. You can easily play around with the various styles interactively in PyMOL by toggling objects (dssr_block##) on or off. Enjoy!

DSSR block image for the Dickerson B-DNA dodecamer (355d)
Fig. 3: Cartoon-block image generated by dssr_block.py for PDB entry 355d (the Dickerson B-DNA dodecamer).

Fig. 3 is created with the following PyMOL commands:

fetch 355d, async=0
bg_color white

as cartoon
turn z, -90
turn y, 180

set cartoon_ladder_mode, 1
set cartoon_ladder_radius, 0.1
set cartoon_ladder_color, black

set cartoon_tube_radius, 0.5
set cartoon_nucleic_acid_mode, 1
set cartoon_color, gold

dssr_block 355d                  # default base blocks in solid color
dssr_block block_file=edge       # rectangular blocks in wireframe (black)
dssr_block block_file=face+edge  # solid color with outline
dssr_block block_file=equal      # bases blocks in equal size
dssr_block block_file=minor      # with minor-groove colord black
dssr_block block_file=wc         # Watson-Crick base pairs in long bp blocks
dssr_block block_file=wc-minor   # Watson-Crick pairs + minor-groove edge
dssr_block block_file=gray       # rectangular blocks all in gray
dssr_block block_depth=1.8       # with increased thickness


  • The dssr_block.py script described here is the original version Thomas communicated to me. Current version of this script and related topics can be found in the Dssr block PyMOLWiki page.
  • For this script to work, DSSR needs to be installed and x3dna-dssr in the PATH.
  • In PyMOL, set cartoon_nucleic_acid_mode, 1 employs C3′ instead of the default P (‘mode 0’) for the smooth backbone trace. Since 5′ terminal phosphate groups are normally not available from X-ray crystal structures (e.g., 355d), ‘mode 1’ is used to avoid orphan base blocks from the backbone trace.

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