As of DSSR v1.3.0-2015aug27, the --json option is available for producing analysis results that is strictly compliant with the JSON data exchange format. The JSON file contains numerous DSSR-derived structural features, including those in the default main output, backbone torsions in dssr-torsions.txt, and a detailed list of hydrogen bonds.

According to the official JSON website:

JSON (JavaScript Object Notation) is a lightweight data-interchange format. It is easy for humans to read and write. It is easy for machines to parse and generate. It is based on a subset of the JavaScript Programming Language… JSON is a text format that is completely language independent… These properties make JSON an ideal data-interchange language.

Indeed, the JSON output file makes DSSR readily accessible for integration with other bioinformatics tools or normal usages from the command line. Using the classic yeast phenylalanine tRNA 1ehz as an example (1ehz.pdb), let’s go over some simple use-cases. Note that the following examples take advantage of jq, a lightweight and flexible command-line JSON processor.

x3dna-dssr -i=1ehz.pdb --json -o=1ehz-dssr.json
jq . 1ehz-dssr.json  # reformatted for pretty output
x3dna-dssr -i=1ehz.pdb --json | jq .  # the above 2 steps combined

With 1ehz-dssr.json in hand, we can easily extract DSSR-derived structural features of interest:

jq .pairs 1ehz-dssr.json   # list of 34 pairs
jq .multiplets 1ehz-dssr.json  # list of 4 base triplets
jq .hbonds 1ehz-dssr.json  # list of hydrogen bonds
jq .helices 1ehz-dssr.json
jq .stems 1ehz-dssr.json
  # list of nucleotide parameters, including torsion angles and suites
jq .ntParams 1ehz-dssr.json
  # list of 14 modified nucleotides
jq '.ntParams[] | select(.is_modified)' 1ehz-dssr.json
  # select nucleotide id, delta torsion, sugar puckering and cluster of suite name
jq '.ntParams[] | {nt_id, delta, puckering, cluster}' 1ehz-dssr.json
  # same selection as above, but in 'Comma Separated Values' format
jq -r '.ntParams[] | [.nt_id, .delta, .puckering, .cluster] | @csv' 1ehz-dssr.json

Here is the result of running jq (v1.5) to select multiplets:

# jq .multiplets 1ehz-dssr.json
[
  {
    "index": 1,
    "num_nts": 3,
    "nts_short": "UAA",
    "nts_long": "A.U8,A.A14,A.A21"
  },
  {
    "index": 2,
    "num_nts": 3,
    "nts_short": "AUA",
    "nts_long": "A.A9,A.U12,A.A23"
  },
  {
    "index": 3,
    "num_nts": 3,
    "nts_short": "gCG",
    "nts_long": "A.2MG10,A.C25,A.G45"
  },
  {
    "index": 4,
    "num_nts": 3,
    "nts_short": "CGg",
    "nts_long": "A.C13,A.G22,A.7MG46"
  }
]

With the JSON file, DSSR can now be connected with the bioinformatics community in a ‘structured’ way, with a clearly delineated boundary. Now I can enjoy the freedom of refining the default main output format, without worrying too much about breaking third-party parsers. Moreover, I no longer need to write an adapter for each integration of DSSR with other tools. So nice!

For your reference, here is the output file 1ehz-dssr.json. It may be possible that the identifiers (names) of the JSON output will be refined in the next few iterations. I welcome your comments to make the DSSR-derived JSON better suite your needs.