G-quadruplexes (hereafter referred to as G4) are a common type of higher-order DNA and RNA structures formed from G-rich sequences. The building block of G4 is a tetrad of guanines in a cyclic planar alignment, with four G+G pairs (cW+M type, see Figure below). A G4 structure is formed by stacking of G-tetrads and stabilized by cations at the center of the layers. G4 structures are polymorphic: the four strands can be parallel or anti-parallel, and loops connecting them can be of different types: lateral (edgewise), diagonal, or propeller (double-chain reversal). Moreover, G4 structures can be intra- or intermolecular, and even contain bulges.
From its initial releases, DSSR was able to detect G-tetrads, and listed them in a separate section. As of v1.7.0-2017oct19, DSSR has integrated existing features and created a new module to automatically identify and fully characterize G4 structures. The underlying algorithms have been further refined in v1.7.1-2017nov01, which was tested against all nucleic-acid-containing structures in the PDB.
Characterizations of three representative G4 examples (PDB entries 2m4p, 2hy9, and 5hix) are shown below, illustrating salient features (e.g., different types of loops) automatically extracted by DSSR.
2m9p
stem#1[#1] layers=3 INTRA-molecular parallel bulged-strands=1
1 syn=---- WC-->Major area=8.38 rise=3.64 twist=33.34 nts=4 GGGG A.DG3,A.DG8,A.DG12,A.DG16
2 syn=---- WC-->Major area=10.73 rise=3.23 twist=32.42 nts=4 GGGG A.DG5,A.DG9,A.DG13,A.DG17
3 syn=---- WC-->Major nts=4 GGGG A.DG6,A.DG10,A.DG14,A.DG18
strand#1* +1 DNA syn=--- nts=3 GGG A.DG3,A.DG5,A.DG6 bulged-nts=1 T A.DT4
strand#2 +1 DNA syn=--- nts=3 GGG A.DG8,A.DG9,A.DG10
strand#3 +1 DNA syn=--- nts=3 GGG A.DG12,A.DG13,A.DG14
strand#4 +1 DNA syn=--- nts=3 GGG A.DG16,A.DG17,A.DG18
loop#1 type=propeller strands=[#1,#2] nts=1 T A.DT7
loop#2 type=propeller strands=[#2,#3] nts=1 T A.DT11
loop#3 type=propeller strands=[#3,#4] nts=1 T A.DT15
2hy9
stem#1[#1] layers=3 INTRA-molecular anti-parallel
1 syn=ss-s Major-->WC area=13.69 rise=3.14 twist=19.08 nts=4 GGGG 1.DG4,1.DG10,1.DG18,1.DG22
2 syn=--s- WC-->Major area=13.40 rise=3.05 twist=28.05 nts=4 GGGG 1.DG5,1.DG11,1.DG17,1.DG23
3 syn=--s- WC-->Major nts=4 GGGG 1.DG6,1.DG12,1.DG16,1.DG24
strand#1 +1 DNA syn=s-- nts=3 GGG 1.DG4,1.DG5,1.DG6
strand#2 +1 DNA syn=s-- nts=3 GGG 1.DG10,1.DG11,1.DG12
strand#3 -1 DNA syn=-ss nts=3 GGG 1.DG18,1.DG17,1.DG16
strand#4 +1 DNA syn=s-- nts=3 GGG 1.DG22,1.DG23,1.DG24
loop#1 type=propeller strands=[#1,#2] nts=3 TTA 1.DT7,1.DT8,1.DA9
loop#2 type=lateral strands=[#2,#3] nts=3 TTA 1.DT13,1.DT14,1.DA15
loop#3 type=lateral strands=[#3,#4] nts=3 TTA 1.DT19,1.DT20,1.DA21
5hix
stem#1[#1] layers=4 inter-molecular anti-parallel
1 syn=s--s Major-->WC area=12.93 rise=3.64 twist=16.82 nts=4 GGGG A.DG1,B.DG4,A.DG12,B.DG9
2 syn=-ss- WC-->Major area=18.96 rise=3.71 twist=35.87 nts=4 GGGG A.DG2,B.DG3,A.DG11,B.DG10
3 syn=s--s Major-->WC area=15.16 rise=3.64 twist=18.64 nts=4 GGGG A.DG3,B.DG2,A.DG10,B.DG11
4 syn=-ss- WC-->Major nts=4 GGGG A.DG4,B.DG1,A.DG9,B.DG12
strand#1 +1 DNA syn=s-s- nts=4 GGGG A.DG1,A.DG2,A.DG3,A.DG4
strand#2 -1 DNA syn=-s-s nts=4 GGGG B.DG4,B.DG3,B.DG2,B.DG1
strand#3 -1 DNA syn=-s-s nts=4 GGGG A.DG12,A.DG11,A.DG10,A.DG9
strand#4 +1 DNA syn=s-s- nts=4 GGGG B.DG9,B.DG10,B.DG11,B.DG12
loop#1 type=diagonal strands=[#1,#3] nts=4 TTTT A.DT5,A.DT6,A.DT7,A.DT8
loop#2 type=diagonal strands=[#2,#4] nts=4 TTTT B.DT5,B.DT6,B.DT7,B.DT8
The molecular structure of the G-tetrad and two G4 structures in schematics representation. Upper left: atomic structure of G-tetrad, the building block of G4 structures. Here the green ‘square’ is created by connecting the C1’ atoms of the guanosines, and it is used to simplify the representation of G4 structures of PDB entries 2m4p (lower left) and 5dww (right). Note that the asymmetric unit of 5dww contains four biological units, which are coaxially stacked in two columns.
The DSSR output for PDB entry 5dww is listed below, showing the differences of a G4-helix vs. a G4-stem.
5dww
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[#2] layers=6 inter-molecular stems=[#1,#2]
1 syn=---- WC-->Major area=10.64 rise=3.54 twist=28.10 nts=4 GGGG A.DG3,A.DG7,A.DG11,A.DG16
2 syn=.--- WC-->Major area=11.63 rise=3.65 twist=31.14 nts=4 GGGG A.DG2,A.DG6,A.DG10,A.DG15
3 syn=---- WC-->Major area=28.36 rise=3.31 twist=-9.78 nts=4 GGGG A.DG1,A.DG5,A.DG9,A.DG14
4 syn=---- Major-->WC area=11.60 rise=3.75 twist=29.43 nts=4 GGGG C.DG1,C.DG14,C.DG9,C.DG5
5 syn=---- Major-->WC area=10.35 rise=3.49 twist=28.74 nts=4 GGGG C.DG2,C.DG15,C.DG10,C.DG6
6 syn=---- Major-->WC nts=4 GGGG C.DG3,C.DG16,C.DG11,C.DG7
strand#1 DNA syn=-.---- nts=6 GGGGGG A.DG3,A.DG2,A.DG1,C.DG1,C.DG2,C.DG3
strand#2 DNA syn=------ nts=6 GGGGGG A.DG7,A.DG6,A.DG5,C.DG14,C.DG15,C.DG16
strand#3 DNA syn=------ nts=6 GGGGGG A.DG11,A.DG10,A.DG9,C.DG9,C.DG10,C.DG11
strand#4 DNA syn=------ nts=6 GGGGGG A.DG16,A.DG15,A.DG14,C.DG5,C.DG6,C.DG7
......
List of 4 G4-stems
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 parallel
1 syn=---- WC-->Major area=11.63 rise=3.65 twist=31.14 nts=4 GGGG A.DG1,A.DG5,A.DG9,A.DG14
2 syn=.--- WC-->Major area=10.64 rise=3.54 twist=28.10 nts=4 GGGG A.DG2,A.DG6,A.DG10,A.DG15
3 syn=---- WC-->Major nts=4 GGGG A.DG3,A.DG7,A.DG11,A.DG16
strand#1 +1 DNA syn=-.- nts=3 GGG A.DG1,A.DG2,A.DG3
strand#2 +1 DNA syn=--- nts=3 GGG A.DG5,A.DG6,A.DG7
strand#3 +1 DNA syn=--- nts=3 GGG A.DG9,A.DG10,A.DG11
strand#4 +1 DNA syn=--- nts=3 GGG A.DG14,A.DG15,A.DG16
loop#1 type=propeller strands=[#1,#2] nts=1 T A.DT4
loop#2 type=propeller strands=[#2,#3] nts=1 T A.DT8
loop#3 type=propeller strands=[#3,#4] nts=2 TT A.DT12,A.DT13
--------------------------------------------------------------------------
stem#2[#1] layers=3 INTRA-molecular parallel
1 syn=---- WC-->Major area=11.60 rise=3.75 twist=29.43 nts=4 GGGG C.DG1,C.DG5,C.DG9,C.DG14
2 syn=---- WC-->Major area=10.35 rise=3.49 twist=28.74 nts=4 GGGG C.DG2,C.DG6,C.DG10,C.DG15
3 syn=---- WC-->Major nts=4 GGGG C.DG3,C.DG7,C.DG11,C.DG16
strand#1 +1 DNA syn=--- nts=3 GGG C.DG1,C.DG2,C.DG3
strand#2 +1 DNA syn=--- nts=3 GGG C.DG5,C.DG6,C.DG7
strand#3 +1 DNA syn=--- nts=3 GGG C.DG9,C.DG10,C.DG11
strand#4 +1 DNA syn=--- nts=3 GGG C.DG14,C.DG15,C.DG16
loop#1 type=propeller strands=[#1,#2] nts=1 T C.DT4
loop#2 type=propeller strands=[#2,#3] nts=1 T C.DT8
loop#3 type=propeller strands=[#3,#4] nts=2 TT C.DT12,C.DT13
In addition to base pairs, DSSR also automatically detects higher-order base associations. They are generally termed multiplets, consisting of three or more co-planar bases arranged together via H-bonding interactions. The simplest multiplets are base triplets. For example, the yeast phenylalanine tRNA (PDB entry 1ehz) contains four base triplets, as shown below:
The well-known (types I and II) A-minor motifs are also multiplets of three bases. Similarly, the G-tetrad where four guanine bases associate via Hoogsteen H-bonding to form a square planar structure is also a special multiplet. The G-tetrad is the building block of the G-quadruplexes. As of v1.7.0-2017oct19, DSSR can automatically identify and characterize G-quadruplexes (see the DSSR User Manual).
The DSSR algorithm for detecting multiplets is generally applicable. It can identify as many co-planar bases as available in a given structure. Shown below is an octad, consisting of a G-tetrad in the middle and four Us on the peripheries. The octad is derived from PDB entry 1j8g using atomic coordinates from biological assembly 1 and 3.
The DSSR-Jmol paper, titled "DSSR-enhanced visualization of nucleic acid structures in Jmol", has been officially published in the 2017 web-server issue of Nucleic Acids Research (NAR). Notably, the work has been featured in the cover image, as shown below:
Caption: 3D interactive visualization of selected RNA structural features enabled by the DSSR-Jmol integration (http://jmol.x3dna.org). Clockwise from upper left: Structure of the xpt-pbuX guanine riboswitch in complex with hypoxanthine (PDB id: 4fe5) in ‘base blocks’ representation. The three-way junction loop encompassing the metabolite (in space-filling representation) is color-coded by base identity: A, red; C, yellow; G, green; U, cyan. The loop-loop interaction (a kissing-loop motif) at the top is highlighted in red (upper left corner). Structure of the Thermus thermophilus 30S ribosomal subunit in complex with antibiotics (PDB id: 1fjg) in step diagram. The 16S ribosomal RNA is color-coded in spectrum with the 5′-end in blue and the 3′-end in red (upper middle). Structure of the classic L-shaped yeast phenylalanine tRNA (PDB id: 1ehz) in step diagram, with the three hairpin loops highlighted in red and the [2,1,5,0] four-way junction loop in blue (upper right corner). Structure of the Pistol self-cleaving ribozyme (PDB id: 5ktj), showcasing (in red) the horizontal helix in space-filling representation. The helix is composed of six short stems stabilized via coaxial stacking interactions (bottom).
The DSSR-Jmol integration bridges the DSSR command-line analyzing tool and the Jmol molecular viewer seamlessly together via the standard JSON interface. Now users can select DSSR-derived RNA structural features (such as base pairs, double helices, various loops, etc.) and visualize them in novel representations in Jmol interactively. Moreover, fine-grained characteristics of these features can be queried via the Jmol SQL for DSSR. The DSSR-Jmol integration fills a gap in RNA structural bioinformatics, and brings RNA visualization to an entirely new level. The web interface (http://jmol.x3dna.org) is fully functional and easy to use, serving a huge user base of researchers, educators, and students alike.
Featured as the cover image of the 2017 NAR web-server issue, DSSR's publicity would surely increase through the DSSR-Jmol integration. Additionally, I've written a new post (on the 3DNA Forum) that provides the scripts and datafiles used to create the cover image.
I am pleased to announce the (advance online, May 3, 2017) publication of a new paper titled "DSSR-enhanced visualization of nucleic acid structures in Jmol" in Nucleic Acids Research (NAR). Co-authored by Robert Hanson (Jmol) and me (DSSR), the article will appear in the July 2017 web-server issue of NAR. Here are the key links related to the paper:
The DSSR-Jmol integration project was initiated in October 2013 when I approached Bob at a meeting organized by RCSB PDB at Rutgers. Thereafter, we met only once in July 2014 in Paris. Over the years, we have mostly communicated via email, occasionally facilitated by Skype. Our work bridges the DSSR command-line analyzing tool and the Jmol molecular viewer together via a simple JSON interface and a powerful query language. Users can now select DSSR-derived RNA structural features (such as base pairs, double helices, and various loops) as easily as they can select protein alpha-helices and beta-strands. Moreover, fine-grained characteristics of these features can be queried via Jmol SQL for DSSR (see examples below). Notably, the novel representation styles (step diagram and base blocks) and coloring schemes bring RNA visualization to an entirely new level (see Figure 3 of the paper).
load =1ehz/dssr # load yeast phenylalanine tRNA to Jmol with DSSR annotation
SELECT hairpins # select the three hairpin loops
SELECT junctions # select the four-way junction loop
select within(dssr, "nts WHERE is_modified") # select modified nucleotides (14 total)
SELECT within(dssr, "pairs WHERE name != 'WC'") # select non-Watson-Crick pairs
SELECT within(dssr, "pairs WHERE name = 'WC' OR name = 'Wobble'") # select canonical pairs
Select within(dssr, "pairs WHERE name != 'WC' AND name != 'Wobble'") # select non-canonical pairs
SELECT within(dssr, "pairs WHERE LW = 'tSW'") # select pairs of type tSW per Leontis-Westhof
The DSSR-Jmol integration fills a gap in RNA structural bioinformatics, serving a huge user base of researchers, educators, and students alike. Its functionality is freely accessible either via the Jmol application, or the JSmol-based website (http://jmol.x3dna.org). By adhering to web standards, the website is fully functional in all modern browsers on various computer/operating systems (including handheld devices, such as tablets and smart phones). The web interface is simple and intuitive, and new users can get started easily. It also allows power users to take full advantage of Jmol scripting via a command-line console.
This work also provides an example for integrating DSSR-derived features into other molecular graphics programs or bioinformatics pipelines involving nucleic acid structures. By design, DSSR is a stand-alone, command-line program written in ANSI C. The binary executables are only ~1MB in size, and self-contained. With zero dependencies, no setup or configuration, it is trivial to get DSSR up and running. DSSR uncovers a wide range of RNA/DNA structural features in a consistent, easily accessible framework. It possesses a much richer set of functionalities for nucleic acid structural analysis (see the DSSR User Manual) than any other existing tools I am aware of. Moreover, the program is efficient and robust, making it an ideal component to be integrated into other pipelines, especially via the standard and structured JSON interface.
Collaborating with Bob has been a truly exciting experience. The NAR-web publication represents a gratifying intermediate result along an on-going journey. Hopefully, others (may be some of you) can join us in pushing forward the field of RNA structural bioinformatics.
Dear 3DNA Forum subscribers,
Here are some highlights of recent developments of 3DNA/DSSR:
Note: If you’ve difficulty in accessing the 3DNA homepage, possibly the case from mainland China (as I know it), please visit its duplicate at http://home.x3dna.org. This newsletter is written in Markdown, with a translated HTML version posted on the 3DNA homepage.
3DNA v2.3
The C source code is now available. Since the programs are written in strict ANSI C, 3DNA can be compiled (as is) on any computers/operating systems with a C (or C++) compiler. For user convenience, three binary distributions (with source code under the src/ subdirectory) are provided for Windows, Linux, and Mac OS X. The distributed Windows version works in native Windows (7 and up, via the cmd command-line interface, or ConEMU), MinGW/Msys (Msys2), and Cygwin, in either 32 or 64-bit.
A new set of ‘simple’ base-pair and step parameters was introduced to give ‘intuitive’ numerical values for non-Watson-Crick base pairs and associated steps. See the short communication titled Characterization of base pair geometry in the January 2016 issue of Computational Crystallography Newsletter (CCN).
The fiber program includes a new option, --pauling, for easy generation of Pauling & Corey triplex models of DNA/RNA with arbitrary base sequence. See my blogpost titled Pauling’s triplex model of nucleic acids is available in 3DNA.
Thomas Holder (PyMOL Principal Developer at Schrödinger, Inc.) has built a PyMOL wrapper to 3DNA fiber models. Now generating standard, regular DNA/RNA models in PyMOL is straightforward — thanks, Thomas!
DSSR (Dissecting the Spatial Structure of RNA)
Selected features of DSSR have been incorporated into Jmol (in collaboration with Robert Hanson, Jmol Principal Developer), and PyMOL (in collaboration with Thomas Holder). In Jmol application (via the Console window), one can now, for example, load =1ehz/dssr and then select hairpins; color red to see where the three hairpin loops are in 3D. The Jmol-DSSR web interface makes DSSR-enhanced visualization of nucleic acid structures in Jmol readily accessible to a broad user base, and has been employed in classes for educational purpose. A sample image of DSSR-derived cartoon-block representation via PyMOL is available for PDB entry 5dww, which has a G-quadruplex-duplex interface.
Since the publication of the Nucleic Acids Research paper in 2015, DSSR has been continuously refined and expanded, with a total of 36 new releases (from v1.2.8 to v1.6.4) as of this writing. Notably, the --json option provides DSSR-derived parameters in the simple, structured, and standard JSON format that can be easily parsed. This JSON output format is the (preferred) way for the outside world to interface with DSSR, and the Jmol-DSSR integration is built upon it. The --nmr option allows for batch processing of MODEL/ENDMDL-delineated NMR ensembles or trajectories of molecular dynamics (MD) simulations. Did you know that scripts and data files for reproducing the reported results are available in the DSSR-NAR paper section on the 3DNA Forum?
The User Manual is now 88-page long, covering nevertheless only the most common use cases of what DSSR has to offer. Miss a feature that you would like to have? Maybe it is already there or can be easily implemented in DSSR. Simply ask (on the 3DNA Forum), and I’ll try my best to help.
SNAP (Structures of Nucleic Acid-Protein complexes)
- SNAP aims to consolidate, refine, and significantly extend commonly used functionalities for DNA/RNA-protein structural analysis in one easy-to-use program. Currently in beta testing, SNAP is already fully functional, with features for characterizing the protein-nucleic acid interface and identifying amino acid-base pairing and stacking interactions.
A note for 3DNA/DSSR users in mainland China: It’s a pleasure to see the ~100 registrations on the 3DNA Forum with emails ending in .cn, 163.com, or qq.com etc., mostly from recent years. I’m planning a trip to China in 2017, and I’d be happy to meet some of you for academic exchanges and possible collaborations (学术交流、合作). If you’re interested, let’s get in touch!
Best regards,
Xiang-Jun
—
Dr. Xiang-Jun Lu (律祥俊)
Email: xiangjun@x3dna.org
Web: http://home.x3dna.org/
Forum: http://forum.x3dna.org/
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.
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.
- 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
- 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.
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),
1213-1227.
THE 3DNA SOFTWARE IS PROVIDED "AS IS", WITHOUT EXPRESSED OR
IMPLIED WARRANTY OF ANY KIND.
Any 3DNA-related questions, comments, and suggestions are
welcome and should be directed to the open 3DNA Forum
(http://forum.x3dna.org/).
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.
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
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.
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.
DSSR and PyMOL
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.
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.
Notes
- 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.
