It gives me great pleasure to announce that the 3DNA/DSSR project is now funded by the NIH R24GM153869 grant, titled "X3DNA-DSSR: a resource for structural bioinformatics of nucleic acids". I am deeply grateful for the opportunity to continue working on a project that has basically defined who I am. It was a tough time during the funding gap over the past few years. Nevertheless, I have experienced and learned a lot, and witnessed miracles enabled by enthusiastic users.

Since late 2020 when I lost my R01 grant, DSSR has been licensed by the Columbia Technology Ventures (CTV). I appreciate the numerous users (including big pharma) who purchased a DSSR Pro License or a DSSR Basic paid License. Thanks to the NIH R24GM153869 grant, we are pleased to provide DSSR Basic free of charge to the academic community. Academic Users may submit a license request for DSSR Basic or DSSR Pro by clicking "Express Licensing" on the CTV landing page. Commercial users may inquire about pricing and licensing terms by emailing techtransfer@columbia.edu, copying xiangjun@x3dna.org.

The current version of DSSR is v2.4.5-2024sep24 which contains miscellaneous bug fixes (e.g., chain id with > 4 chars) and minor improvements. This release synchronizes with the new R24 funding, which will bring the project to the next level. All existing users are encouraged to upgrade their installation.

Lots of exciting things will happen for the project. The first thing is to make DSSR freely accessible to the academic community. In the past couple of weeks, CTV have already issued quite a few DSSR Basic Academic licenses to users from all over the world. So the demand is high, and it will become stronger as more academic users become aware of DSSR. I'm closely monitoring the 3DNA Forum, and is always ready to answer users questions.

I am committed to making DSSR a brand that stands for quality and value. By virtue of its unmatched functionality, usability, and support, DSSR saves users a substantial amount of time and effort when compared to other options. My track record throughout the years has unambiguously demonstrated my dedication to this solid software product.


DSSR Basic contains all features described in the three DSSR-related papers, and includes the originally separate SNAP program (still unpublished) for analyzing DNA/RNA-protein complexes. The Pro version integrates the classic 3DNA functionality, plus advanced modeling routines, with email/Zoom/phone support.

---

List of modified nucleotides in DSSR output

From early on, 3DNA and DSSR have native support of modified nucleotides. The currently distributed baselist.dat file with 3DNA contains over 700 entries. As of v1.1.4-2014aug09, a new section has been added to DSSR to list explicitly the modified nucleotides in an analyzed structure.

Using the 76-nucleotide long yeast phenylalanine tRNA (1ehz) as an example, the pertinent section in DSSR output is as below.

List of 11 types of 14 modified nucleotides
      nt    count  list
   1 1MA-a    1    A.1MA58
   2 2MG-g    1    A.2MG10
   3 5MC-c    2    A.5MC40,A.5MC49
   4 5MU-t    1    A.5MU54
   5 7MG-g    1    A.7MG46
   6 H2U-u    2    A.H2U16,A.H2U17
   7 M2G-g    1    A.M2G26
   8 OMC-c    1    A.OMC32
   9 OMG-g    1    A.OMG34
  10 PSU-P    2    A.PSU39,A.PSU55
  11 YYG-g    1    A.YYG37

So 1ehz has 14 modified nucleotides of 11 different type, as listed in the following rows after the header line. The meaning of each column should be obvious. For example, the third row means that 5MC (5-methylcytidine, abbreviated as 'c' in 1-letter code) occurs twice, identified as A.5MC40 and A.5MC49, respectively.

With the 3-letter id, one can search the RCSB ligand database for more information about a specified modified nucleotide. The URL would be like this, using pseudouridine (PSU) as an example, http://www.rcsb.org/pdb/ligand/ligandsummary.do?hetId=PSU.

It is hoped that the newly added section, put at the very top of DSSR output, will draw more attention to modified nucleotides.

Comment

---

DSSR-derived secondary structure in BPSEQ format

From v1.1.3-2014jun18, DSSR has an additional output of RNA secondary structures in BPSEQ format. A sample file for PDB entry 1msy is shown below.

1msy [GUAA tetra loop] in 3d and 2d representations

Filename: dssr-2ndstrs.bpseq
Organism: DSSR-derived secondary structure [1msy]
Accession Number: DSSR v1.1.4-2014aug09 (xiangjun@x3dna.org)
Citation: Please cite 3DNA/DSSR (see http://home.x3dna.org)
    1 U     0 # name=A.U2647
    2 G    26 # name=A.G2648, pairedNt=A.U2672
    3 C    25 # name=A.C2649, pairedNt=A.G2671
    4 U    24 # name=A.U2650, pairedNt=A.A2670
    5 C    23 # name=A.C2651, pairedNt=A.G2669
    6 C    22 # name=A.C2652, pairedNt=A.G2668
    7 U     0 # name=A.U2653
    8 A     0 # name=A.A2654
    9 G     0 # name=A.G2655
   10 U     0 # name=A.U2656
   11 A     0 # name=A.A2657
   12 C    17 # name=A.C2658, pairedNt=A.G2663
   13 G     0 # name=A.G2659
   14 U     0 # name=A.U2660
   15 A     0 # name=A.A2661
   16 A     0 # name=A.A2662
   17 G    12 # name=A.G2663, pairedNt=A.C2658
   18 G     0 # name=A.G2664
   19 A     0 # name=A.A2665
   20 C     0 # name=A.C2666
   21 C     0 # name=A.C2667
   22 G     6 # name=A.G2668, pairedNt=A.C2652
   23 G     5 # name=A.G2669, pairedNt=A.C2651
   24 A     4 # name=A.A2670, pairedNt=A.U2650
   25 G     3 # name=A.G2671, pairedNt=A.C2649
   26 U     2 # name=A.U2672, pairedNt=A.G2648
   27 G     0 # name=A.G2673

Based on online sources, BPSEQ has originated from the Comparative RNA Web site developed by the Gutell lab. CRW files contain four header lines, describing the file name, organism, accession number, and a general remark. Thereafter, there is one line per base in the molecule, listing the position of the base (starting from 1), the one-letter base name (A,C,G,U etc), and the position number of the base to which it is paired. If the base is unpaired, zero (0) is put in the third column. In the above sample BPSEQ file derived from DSSR, detailed information about the base and its paired base (if any) comes after the # symbol.

Compared to dot-bracket notation (dbn) and connect-table (.ct) format, BPSEQ is simpler but less expressive. Nevertheless, the format is well-supported in bioinformatic tools on RNA secondary structures. It only seems fitting that DSSR now produces secondary structures in .bpseq (with default file name dssr-2ndstrs.bpseq), in addition to .dbn and .ct. Technically, adding the BPSEQ output to DSSR is trivial given the infrastructure already in place.

Comment

---

RNA pseudoknot detection and removal with DSSR

From early on, DSSR-derived RNA secondary structures in dot-bracket notation (dbn) have taken pseudoknots into consideration. Nevertheless, in DSSR releases prior to v1.1.3-2014jun18, the dbn output had been simplified to the first level only, with matched []s, even for RNA structures with high-order pseudoknots. RNA pseudoknot is a (relatively) complicated issue, and I’d planned to put off the topic until DSSR is well-established.

In early May, I noticed the Antczak et al. article RNApdbee—a webserver to derive secondary structures from pdb files of knotted and unknotted RNAs. I was delighted to read the following citation:

In order to facilitate a more comprehensive study, the webserver integrates the functionality of RNAView, MC-Annotate and 3DNA/DSSR, being the most common tools used for automated identification and classification of RNA base pairs.

Even before any paper on DSSR has been published, the software has already be ranked in the top three for the identification and classification of RNA base pairs! Well familiar with RNAView and MC-Annotate, I am glad to see DSSR is now listed on a par with them. Note that DSSR has far more functionality than just identifying and classifying RNA base pairs.

Further down the RNApdbee paper, especially in Figure 2, I found the following remarks regarding DSSR’s capability on RNA structures with high-order pseudoknot.

An arc diagram to represent the secondary structure of 1DDY (chain A)

An arc diagram to represent the secondary structure of 1DDY (chain A) generated by R-CHIE upon the dot-bracket notation. Arcs of the same colour define a paired region. Crossing arcs reflect a conflict observed between the corresponding regions. (a) RNApdbee recognizes pseudoknots of the first (dark green) and second (navy blue) order. (b) 3DNA/DSSR improperly classifies base pairs (within residues in red) and the structure is recognized as the first-order pseudoknot.

The above citation and the question Higher-order pseudoknots in DP output (from Jan Hajic, Charles University in Prague) on the 3DNA Forum prompted me to further refine DSSR’s algorithm for deriving secondary structures of RNA with high-order pseudoknots. The DSSR v1.1.3-2014jun18 release made this revised functionality explicit. For the above cited PDB entry 1ddy, the relevant output of running DSSR on it would be:

Running command: "x3dna-dssr -i=1ddy.pdb"

****************************************************************************
This structure contains 2-order pseudoknot(s)

****************************************************************************
Secondary structures in dot-bracket notation (dbn) as a whole and per chain
>1ddy nts=140 [whole]
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA&GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA&GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA&GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((.{[[....[[)))...].].}.]]..&......(((.{[[....[[)))...].].}.]]..&......(((.{[[....[[)))...].].}.]]..&......(((.{[[....[[)))...].].}.]]..
>1ddy-A #1 nts=35 [chain] RNA
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((.{[[....[[)))...].].}.]]..
>1ddy-C #2 nts=35 [chain] RNA
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((.{[[....[[)))...].].}.]]..
>1ddy-E #3 nts=35 [chain] RNA
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((.{[[....[[)))...].].}.]]..
>1ddy-G #4 nts=35 [chain] RNA
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((.{[[....[[)))...].].}.]]..

Note that the whole 1ddy entry contains four RNA chains (A, C, E, and G), and DSSR can handle each properly. So at least from DSSR v1.1.3-2014jun18, the following statement is no longer valid:

3DNA/DSSR improperly classifies base pairs (within residues in red) and the structure is recognized as the first-order pseudoknot.

A closely related issue is knot removal, a topic nicely summarized by Smit et al. in their publication From knotted to nested RNA structures: A variety of computational methods for pseudoknot removal. While not explicitly documented, the --nested (abbreviated to --nest) option has been available since DSSR v1.1.3-2014jun18. This option was first mentioned in the release note of DSSR v1.1.4-2014aug09. Again, using PDB entry 1ddy as an example, the relevant output of running DSSR with option --nested is as follows:

Running command: "x3dna-dssr -i=1ddy.pdb --nested"

****************************************************************************
This structure contains 2-order pseudoknot(s)
   o You've chosen to remove pseudo-knots, leaving only nested pairs

****************************************************************************
Secondary structures in dot-bracket notation (dbn) as a whole and per chain
>1ddy nts=140 [whole]
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA&GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA&GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA&GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((..........))).............&......(((..........))).............&......(((..........))).............&......(((..........))).............
>1ddy-A #1 nts=35 [chain] RNA
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((..........))).............
>1ddy-C #2 nts=35 [chain] RNA
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((..........))).............
>1ddy-E #3 nts=35 [chain] RNA
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((..........))).............
>1ddy-G #4 nts=35 [chain] RNA
GGAACCGGUGCGCAUAACCACCUCAGUGCGAGCAA
......(((..........))).............

Comment

---

Get hydrogen bonds with DSSR

H-bonding interactions are crucial for defining RNA secondary and tertiary structures. DSSR/3DNA contains a geometrically based algorithm for identifying H-bonds in nucleic-acid or protein structures given in .pdb or .cif format. Over the years, the method has been continuously refined, and it has served its purpose quite well. As of v1.1.1-2014apr11, this functionality is directly available from DSSR thorough the --get-hbonds option.

The output for 1msy, which contains a GUAA tetraloop mutant of Sarcin/Ricin domain from E. Coli 23 S rRNA, is listed below. The first line gives the header (# H-bonds in '1msy.pdb' identified by DSSR ...). The second line provides the total number of H-bonds (40) identified in the structure. Afterwards, each line consists of 8 space-delimited columns used to characterize a specific H-bond. Using the first one (#1) as an example, the meaning of each of the 8 columns is:

  1. The serial number (15), as denoted in the .pdb or .cif file, of the first atom of the H-bond.
  2. The serial number (578) of the second H-bond atom.
  3. The H-bond index (#1), from 1 to the total number of H-bonds.
  4. A one-letter symbol showing the atom-pair type (p) of the H-bond. It is ‘p’ for a donor-acceptor atom pair; ‘o’ for a donor/acceptor (such as the 2′-hydorxyl oxygen) with any other atom; ‘x’ for a donor-donor or acceptor-acceptor pair (as in #17); ‘?’ if the donor/acceptor status is unknown for any H-bond atom.
  5. Distance in Å between donor/acceptor atoms (2.768).
  6. Elemental symbols of the two atoms involved in the H-bond (O/N).
  7. Identifier of the first H-bond atom (O4@A.U2647).
  8. Identifier of the second H-bond atom (N1@A.G2673).
Command: x3dna-dssr -i=1msy.pdb --get-hbonds –o=1msy-hbonds.txt

# H-bonds in '1msy.pdb' identified by 3DNA version 3 (xiangjun@x3dna.org)
40
   15   578  #1     p    2.768 O:N O4@A.U2647 N1@A.G2673
   35   555  #2     p    2.776 O:N O6@A.G2648 N3@A.U2672
   36   554  #3     p    2.826 N:O N1@A.G2648 O2@A.U2672
   55   537  #4     p    2.965 O:N O2@A.C2649 N2@A.G2671
   56   535  #5     p    2.836 N:N N3@A.C2649 N1@A.G2671
   58   534  #6     p    2.769 N:O N4@A.C2649 O6@A.G2671
   76   513  #7     p    2.806 N:N N3@A.U2650 N1@A.A2670
   78   512  #8     p    3.129 O:N O4@A.U2650 N6@A.A2670
   95   492  #9     p    2.703 O:N O2@A.C2651 N2@A.G2669
   96   490  #10    p    2.853 N:N N3@A.C2651 N1@A.G2669
   98   489  #11    p    2.987 N:O N4@A.C2651 O6@A.G2669
  115   466  #12    p    2.817 O:N O2@A.C2652 N2@A.G2668
  116   464  #13    p    2.907 N:N N3@A.C2652 N1@A.G2668
  118   463  #14    p    2.897 N:O N4@A.C2652 O6@A.G2668
  123   151  #15    o    2.622 O:O OP2@A.U2653 O2'@A.A2654
  135   443  #16    p    2.898 O:N O2@A.U2653 N4@A.C2667
  147   192  #17    x    3.054 O:O O4'@A.A2654 O4'@A.U2656
  158   408  #18    p    2.960 N:O N6@A.A2654 OP2@A.C2666
  173   188  #19    o    2.923 O:O O2'@A.G2655 OP2@A.U2656
  173   378  #20    o    3.093 O:O O2'@A.G2655 O6@A.G2664
  173   379  #21    o    3.343 O:N O2'@A.G2655 N1@A.G2664
  181   386  #22    p    2.768 N:O N1@A.G2655 OP2@A.A2665
  183   203  #23    p    2.754 N:O N2@A.G2655 O4@A.U2656
  183   387  #24    p    2.887 N:O N2@A.G2655 O5'@A.A2665
  188   379  #25    p    3.044 O:N OP2@A.U2656 N1@A.G2664
  188   381  #26    p    2.944 O:N OP2@A.U2656 N2@A.G2664
  200   401  #27    p    3.122 O:N O2@A.U2656 N6@A.A2665
  201   398  #28    p    2.759 N:N N3@A.U2656 N7@A.A2665
  220   381  #29    p    3.035 N:N N7@A.A2657 N2@A.G2664
  223   371  #30    o    2.963 N:O N6@A.A2657 O2'@A.G2664
  223   382  #31    p    3.039 N:N N6@A.A2657 N3@A.G2664
  242   358  #32    p    2.821 O:N O2@A.C2658 N2@A.G2663
  243   356  #33    p    2.890 N:N N3@A.C2658 N1@A.G2663
  245   355  #34    p    2.887 N:O N4@A.C2658 O6@A.G2663
  258   305  #35    o    2.604 O:N O2'@A.G2659 N7@A.A2661
  258   308  #36    o    3.264 O:N O2'@A.G2659 N6@A.A2661
  268   315  #37    p    2.973 N:O N2@A.G2659 OP2@A.A2662
  268   327  #38    p    2.864 N:N N2@A.G2659 N7@A.A2662
  371   390  #39    o    2.751 O:O O2'@A.G2664 O4'@A.A2665
  550   566  #40    o    3.372 O:O O2'@A.U2672 O4'@A.G2673

In its default settings, DSSR detects 117 H-bonds for 1ehz (yeast phenylalanine tRNA), and 5,809 for 1jj2 (the H. marismortui large ribosomal subunit). Note that the program can identify H-bonds not only in RNA and DNA, but also in proteins, or their complexes. By default, however, DSSR only reports H-bonds within nucleic acids. As shown above, it is trivial to run DSSR with the --get-hbonds option to get all H-bonds in a given structure, and the plain text output is straightforward to work on.

While there exist dedicated tools for finding H-bonds, such as HBPLUS or HBexplore, DSSR may well be sufficient to fulfill most practical needs. If you notice any weird behaviors with this H-bond finding functionality, please let me know. I strive to address reported issues promptly, to the extent practical. At the very least, I should be able to explain why the program is working the way it does.

Comment [2]

---

DSSR now has a user manual!

As of v1.0.3-2014mar09, DSSR has a decent user manual in PDF! Currently of 45 pages long, the DSSR manual contains everything a typical user needs to know to get started using the program effectively. The contents the manual are listed below.

Table of Contents

List of Figures

Introduction

Download and installation

Usages
  Command-line help
  Default run on PDB entry 1msy – detailed explanations
    Summary section
    List of base pairs
    List of multiplets
    List of helices
    List of stems
    List of lone canonical pairs
    List of various loops
    List of single-stranded fragments
    Secondary structure in dot-bracket notation
    List of backbone torsion angles and suite names
  Default run on PDB entry 1ehz (tRNAPhe) – summary notes
    Brief summary
    Specific features
  Default run on PDB entry 1jj2 – four auto-checked motifs
    Kissing loops
    A-minor (types I and II) motifs
    Ribose zippers
    Kink turns
  The --more option
    Extra parameters for base pairs
    Extra parameters for helices/stems
  The –-non-pair option
  The –-u-turn option
  The --po4 option
  The –-long-idstr option

Frequently asked questions
  How to cite DSSR?
  Does DSSR work for DNA?
  Does DSSR detect RNA tertiary interactions?

Revision history

Acknowledgements

References

With the User Manual available, I feel confident to claim that DSSR is now mature, stable, ready for real world applications. While only time would tell, I have no doubt that DSSR will become an essential tool in RNA structural bioinformatics.

Comment

---

DSSR-derived secondary structure in .ct format

From early on, DSSR-derived nucleic acid secondary structures have been written in the compact dot-bracket notation (.dbn) with pseudo-knot information. To better connect DSSR to the 2D world, I recently looked into the connect (.ct) format, which was first introduced by Zuker’s mfold program. Over time, the .ct format has become one of the most commonly used RNA secondary structure formats, and it is more expressive than the .dbn format (see below).

As of v1.0, for each analyzed structure, DSSR produces two secondary structure files with default names dssr-2ndstrs.dbn and dssr-2ndstrs.ct, in .dbn and .ct formats, respectively. Using the 27-nucleotides (nt) RNA fragment 1msy as an example, the DSSR-derived secondary structure in .dbn and .ct formats are shown below:

1msy [GUAA tetra loop] in 3d and 2d representations

In dot-bracket notation (.dbn) [dssr-2ndstrs.dbn]
------------------------------------------------------
>1msy nts=27 DSSR-derived secondary structure
UGCUCCUAGUACGUAAGGACCGGAGUG
.(((((.....(....)....))))).
------------------------------------------------------

In connect format (.ct) [dssr-2ndstrs.ct]
------------------------------------------------------
   27 DSSR-derived secondary structure in '1msy'
    1 U     0     2     0  2647 # name=A.U2647
    2 G     1     3    26  2648 # name=A.G2648, pairedNt=A.U2672
    3 C     2     4    25  2649 # name=A.C2649, pairedNt=A.G2671
    4 U     3     5    24  2650 # name=A.U2650, pairedNt=A.A2670
    5 C     4     6    23  2651 # name=A.C2651, pairedNt=A.G2669
    6 C     5     7    22  2652 # name=A.C2652, pairedNt=A.G2668
    7 U     6     8     0  2653 # name=A.U2653
    8 A     7     9     0  2654 # name=A.A2654
    9 G     8    10     0  2655 # name=A.G2655
   10 U     9    11     0  2656 # name=A.U2656
   11 A    10    12     0  2657 # name=A.A2657
   12 C    11    13    17  2658 # name=A.C2658, pairedNt=A.G2663
   13 G    12    14     0  2659 # name=A.G2659
   14 U    13    15     0  2660 # name=A.U2660
   15 A    14    16     0  2661 # name=A.A2661
   16 A    15    17     0  2662 # name=A.A2662
   17 G    16    18    12  2663 # name=A.G2663, pairedNt=A.C2658
   18 G    17    19     0  2664 # name=A.G2664
   19 A    18    20     0  2665 # name=A.A2665
   20 C    19    21     0  2666 # name=A.C2666
   21 C    20    22     0  2667 # name=A.C2667
   22 G    21    23     6  2668 # name=A.G2668, pairedNt=A.C2652
   23 G    22    24     5  2669 # name=A.G2669, pairedNt=A.C2651
   24 A    23    25     4  2670 # name=A.A2670, pairedNt=A.U2650
   25 G    24    26     3  2671 # name=A.G2671, pairedNt=A.C2649
   26 U    25    27     2  2672 # name=A.U2672, pairedNt=A.G2648
   27 G    26     0     0  2673 # name=A.G2673
------------------------------------------------------

Presumably, the .ct format is very simple, and examining a sample file as shown above would give one a pretty good sense of what each column is about. While there exist many oversimplified descriptions of the .ct format on the web, the most detailed and accurate explanation is from the mfold manual:

The ``ct’‘ file (connect table) contains the sequence and base pair information, and is meant to be an input file for a structure drawing program. In addition to containing base pair information, it also lists the 5′ and 3′ neighbor of each base, allowing for the representation of circular RNA or multiple molecules. The ct file also lists the historical base numbering in the original sequence, as bases and base pairs are numbered according from 1 to the size of the folded segment. A portion of a ct file is displayed in Figure 12.

Figure 12: The ct file for the second and final folding of S. cerevisiae Phe-tRNA at 37°, with default parameters. The first record displays the fragment size (76), ΔG and sequence name. The ith subsequent record contains, in order, i, ri, the index of the 5′-connecting base, the index of the 3′-connecting base, the index of the paired base and the historical numbering of the ith base in the original sequence. The 5′, 3′ and base pair indices are 0 when there is no connection or base pair.

Specifically, the 3rd, 4th, and 6th columns in the .ct format convey specific information; by design, they are not redundant to information contained in the 1st column. Note that in the above ‘1msy’ example, the 6th column gives the nt sequence numbers (as in the PDB datafile) instead of the serial numbers (as in the 1st column). The DSSR produced .ct files also contain extra information after ‘#’, in the comma separated key=value format.

As an example of the usefulness of the 3rd and 4th columns, have a look of the DSSR-derived .ct file for the Dickerson DNA dodecamer duplex with sequence CGCGAATTCGCG:

   24 DSSR-derived secondary structure in '355d'
    1 C     0     2    24     1 # name=A.DC1, pairedNt=B.DG24
    2 G     1     3    23     2 # name=A.DG2, pairedNt=B.DC23
    3 C     2     4    22     3 # name=A.DC3, pairedNt=B.DG22
    4 G     3     5    21     4 # name=A.DG4, pairedNt=B.DC21
    5 A     4     6    20     5 # name=A.DA5, pairedNt=B.DT20
    6 A     5     7    19     6 # name=A.DA6, pairedNt=B.DT19
    7 T     6     8    18     7 # name=A.DT7, pairedNt=B.DA18
    8 T     7     9    17     8 # name=A.DT8, pairedNt=B.DA17
    9 C     8    10    16     9 # name=A.DC9, pairedNt=B.DG16
   10 G     9    11    15    10 # name=A.DG10, pairedNt=B.DC15
   11 C    10    12    14    11 # name=A.DC11, pairedNt=B.DG14
   12 G    11     0    13    12 # name=A.DG12, pairedNt=B.DC13
   13 C     0    14    12    13 # name=B.DC13, pairedNt=A.DG12
   14 G    13    15    11    14 # name=B.DG14, pairedNt=A.DC11
   15 C    14    16    10    15 # name=B.DC15, pairedNt=A.DG10
   16 G    15    17     9    16 # name=B.DG16, pairedNt=A.DC9
   17 A    16    18     8    17 # name=B.DA17, pairedNt=A.DT8
   18 A    17    19     7    18 # name=B.DA18, pairedNt=A.DT7
   19 T    18    20     6    19 # name=B.DT19, pairedNt=A.DA6
   20 T    19    21     5    20 # name=B.DT20, pairedNt=A.DA5
   21 C    20    22     4    21 # name=B.DC21, pairedNt=A.DG4
   22 G    21    23     3    22 # name=B.DG22, pairedNt=A.DC3
   23 C    22    24     2    23 # name=B.DC23, pairedNt=A.DG2
   24 G    23     0     1    24 # name=B.DG24, pairedNt=A.DC1

Note the 0 at the 4th column for A.DG12 which is at the 3′ end of chain A, and the 0 at 3rd column for B.DC13 which is at the 5′ end of chain B.

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Single- and double-stranded Zp

From early on, 3DNA calculates the Zp parameter to separate A- and B-DNA double helical steps. First introduced in the paper A-form conformational motifs in ligand-bound DNA structures (see figure below), Zp is the mean projection of the two phosphorus atoms onto the z-axis of the dimer ‘middle frame’. Zp is greater than 1.5 Å for A-DNA, and it is less than 0.5 Å for B-DNA. As noted in the 3DNA NAR paper, other parameters such as slide should also be examined to confirm conformational assignments based on Zp.

definition of the Zp parameter for duplex DNA

As of v2.1, 3DNA has introduced the single-stranded variant for the Zp parameter (ssZp) as a more robust substitute for the Richardson phosphorus-glycosidic bond distance parameter (Dp) to characterize sugar puckers. See post Sugar pucker correlates with phosphorus-base distance for more details. In 3DNA/DSSR, ssZp is defined as the z-coordinate of the 3′ phosphorus atom expressed in the standard reference frame of the preceding base; it is positive when phosphorus lies on the +z-axis side (base in anti conformation) and negative if phosphorus is on the –z-axis side (base in syn conformation). Note that by definition, Dp should always be positive.

As in the previous post, here I am using G175 and U176 of PDB entry 1jj2 (the large ribosomal subunit of Haloarcula marismortui) as examples to illustrate how the ssZp parameters are calculated. The GpU forms a dinucleotide platform, where the sugar of G175 adopts a C2′-endo conformation, and that of U176 C3′-endo. For verification, here is the PDB data file for fragment 1jj2-G175-U176-A177.pdb (note A177 is included for its phosphorus atom). Run the following 3DNA commands:

find_pair -s 1jj2-G175-U176-A177.pdb stdout
frame_mol -1 ref_frames.dat 1jj2-G175-U176-A177.pdb ref-G175.pdb
frame_mol -2 ref_frames.dat 1jj2-G175-U176-A177.pdb ref-U176.pdb

File ref-G175.pdb contains the following line:

ATOM     24  P     U 0 176      -5.624   6.937   1.918  1.00 24.19           P 

The z-coordinate of U176 (which is 3′ to G175) is 1.918, which is the ssZp for G175. It is less than 2.9 Å, corresponding to the C2′-endo sugar conformation of G175.

Similarly, file ref-U176.pdb contains the following line:

ATOM     44  P     A 0 177      -3.841   6.592   4.377  1.00 25.91           P

So the ssZp for U176 is 4.377, which is greater than 2.9 Å, corresponding to the C3′-endo sugar conformation of U176.

To sum up, the double-stranded Zp as originally available from 3DNA can be used for discriminating A- and B-DNA double-helical steps: Zp > 1.5 Å for A-DNA, and Zp < 0.5 Å for B-DNA. The newly introduced single-stranded Zp is intended for characterizing sugar puckers: Zp > 2.9 Å for C3′-endo, and Zp < 2.9 Å for C2′-endo. Since A-DNA has predominately C3′-endo sugar conformation and B-DNA has C2′-endo sugar, the ssZp parameter would be helpful in classifying a dinucleotide into A- or B-like conformation. A survey of ssZp in well-defined A- and B-DNA structures (as performed for double-stranded Zp) should prove useful.

Realizing the naming confusions of double-stranded Zp vs single-stranded Zp, I am considering to rename single-stranded Zp as ssZp in future releases of 3DNA and DSSR. Do you have any comments or suggestions? Please let me know by leaving a comment!

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Modified nucleotides in the PDB

In addition to the five canonical bases (A, C, G, T, and U), nucleic acid structures in the PDB contains numerous modified variants (natural or engineered) in the nucleobase, sugar, or the phosphate. For instance, the 76-nt (nucleotide) long yeast phenylalanine tRNA (1ehz) contains 14 modified bases: 2MG10, H2U16, H2U17, M2G26, OMC32, OMG34, YYG37, PSU39, 5MC40, 7MG46, 5MC49, 5MU54, PSU55, and 1MA58. Among which, the most prevalent and best-known example is pseudouridine. Note that in the PDB, each residue (including modified nt) is named with an up to three-letter identifier, e.g., PSU for pseudouridine. For a comprehensive list (with chemical and structural information) of small molecules, including modified nts, please refer to the Ligand Expo website hosted by the RCSB PDB.

Given the widespread occurrences of modified bases in nucleic acid structures, any practical structural bioinformatics software should be able to treat them effectively, as with the canonical bases. In 3DNA, from the very beginning, modified bases are mapped to standard counterparts, e.g. 5‐iodouracil (5IU) to uracil (U) and 1‐methyladenine (1MA) to adenine (A), allowing for easy analysis of unusual DNA and RNA structures (see the NAR03 reference). Specifically, in the 3DNA distribution the file baselist.dat contains the mappings explicitly.

As of v2.1, 3DNA automatically maps a new modified base not available in the file baselist.dat. Yet, I have continuously updated the list in line with new DNA/RNA entries released by the PDB. The process is automated with a Ruby script which calls find_pair -s on each nucleic-acid-containing structure to output unknown bases. As an extreme, the baselist.dat file below comprises only canonical bases:

  A   A
  C   C
  G   G
  T   T
  U   U
 DA   A
 DC   C
 DG   G
 DT   T

With the above minimum mapping list, running the command find_pair -s on 1ehz.pdb identifies all the 14 modified bases. A sample case for 2MG is shown below:

Match '2MG' to 'g' for residue 2MG   10  on chain A [#10]
    check it & consider to add line '2MG     g' to file <baselist.dat>

By parsing the output of a batch run on all DNA/RNA-containing entries in the PDB as of October 18, 2013, I identified a total of 596 modified bases. The top portion is as below:

02I     a
08Q     c
08T     a
0AD     g
 0C     c
0DC     c
0DG     g
0DT     t
 0G     g
0KL     u
0KX     c
0KZ     t

An explicit list of base mapping makes the correspondence transparent, and helps avoid ambiguous cases as to which canonical base a modified nt matches to. DSSR uses the same list internally. Hopefully, the information would also be useful to other related projects.

Comment [2]

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UNR- and GNRA-type U-turns

As of beta-r20-on-20130830, DSSR is able to detect two types of U-turns (see the figure below), the UNR-type (left) originally identified by Quigley and Rich [1976] in yeast phenylalanine tRNA, and the GNRA-type (right) later on established by Jucker and Pardi [1995] in GNRA tetra loops. See the Gutell et al. paper Predicting U-turns in Ribosomal RNA with Comparative Sequence Analysis for a more extensive account of U-turns.

As its name implies, a U-turn is characterized by a reversal of the RNA backbone direction within a few nucleotides. Among other factors, the U-turn is stabilized by two key H-bonding interactions, illustrated in dotted lines in the figure below.

UNR-type U-turn in yeast phenylalanine tRNA (1ehz) GNRA-type U-turn in a GUAA tetraloop (1msy)
UNR-type (1ehz) GNRA-type (1msy)

Applying DSSR to 1jj2 (the crystal structure of the Haloarcula marismortui large ribosomal subunit) led to the identification of over 30 cases. In addition to the well-documented UNR- and GNRA-type U-turns, the program also finds other variants. An example is shown below, where the U-turn is within a GCA triloop instead of a GNRA tetraloop. Here, the N1 (not N2) atom of G1809 forms an H-bond with OP2 of G1812. The G1809 N2 atom is H-bonded to G1812 O5′ to further stabilize the U-turn.

U-turn formed by the GCA-triloop (1jj2)

An examination of the chemical structure of the nitrogenous bases (see figure below) shows clearly other possibilities to connect RNA base donors to the phosphate oxygen acceptors. DSSR allows for the exploration of such variations, and more.

Chemical diagram of RNA bases

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