PubChemCrawler

cid = get_cid(name="glucose")
cid = get_cid(smiles="C([C@@H]1[C@H]([C@@H]([C@H](C(O1)O)O)O)O)O")

Return the PubChem compound identification number for the specified compound.

cids = query_substructure_pug(;cid=nothing, smiles=nothing, smarts=nothing,        # specifier for the substructure to search for
                               maxhits=200_000, poll_interval=10)

Retrieve a list of compounds containing a substructure specified via its cid, the SMILES string, or a SMARTS string.

Example

julia> using PubChemCrawler

julia> cids = query_substructure_pug(smarts="[r13]Br")   # query brominated 13-atom rings
66-element Vector{Int64}:
  54533707
 153064026
 152829033
...

PUG searches can take a while to run (they poll for completion), but conversely they allow more complex, long-running searches to succeed. See also query_substructure.

msg = query_substructure(;cid=nothing, smiles=nothing, smarts=nothing,           # specifier for the substructure to search for
                          properties="MolecularFormula,MolecularWeight,XLogP,",  # properties to retrieve
                          output="CSV")                                          # output format

Perform a substructure search of the entire database. You can specify the target via its cid, the SMILES string, or a SMARTS string. Specify the properties you want to retrieve as a comma-separated list from among the choices in http://pubchemdocs.ncbi.nlm.nih.gov/pug-rest, "Compound Property Tables". Requesting more properties takes more time.

The output is a Vector{UInt8}. For output="CSV", a good choice to generate a manipulable result is DataFrame(CSV.File(msg)) from the DataFrames and CSV packages, respectively. Alternatively String(msg) will convert it to a string, which you can write to a file.

Example

julia> using PubChemCrawler, CSV, DataFrames

julia> cid = get_cid(name="estriol")
5756

julia> df = CSV.File(query_substructure(;cid)) |> DataFrame      # on Julia 1.0, use `(;cid=cid)`
11607×4 DataFrame
│ Row  │ CID       │ MolecularFormula │ MolecularWeight │ XLogP    │
│      │ Int64     │ String           │ Float64         │ Float64? │
├──────┼───────────┼──────────────────┼─────────────────┼──────────┤
│ 1    │ 5756      │ C18H24O3         │ 288.4           │ 2.5      │
│ 2    │ 5281904   │ C24H32O9         │ 464.5           │ 1.1      │
│ 3    │ 27125     │ C18H24O4         │ 304.4           │ 1.5      │
...

will query for derivatives of estriol.

msg = get_for_cids(cids; properties|xrefs|cids_type|record_type, output="CSV")

Retrieve the given properties, xrefs, CIDs, or records, respectively, for a list of compounds specified by their cids. The documentation for these traits can be found at http://pubchemdocs.ncbi.nlm.nih.gov/pug-rest; this URL will be referred to as PUGREST below.

• properties include structural features like the molecular formula, number of undefined stereocenters, and so on. Specify these as a comma-separated list from among the choices in PUGREST under "Compound Property Tables".
• xrefs ("cross-references") include identifiers used by other databases, e.g., the CAS (Registry) number, PubMedID, and so on. The supported values for xrefs are available at PUGREST under "XRefs".
• cids_type is used to retrieve CIDs for compounds related to those specified in cids; see PUGREST under "SIDS / CIDS / AIDS".
• record_type is used to retrieve data files and to specify options for these files, e.g., 2d or 3d SDF files. See PUGREST under "Full-record Retrieval".

output specifies the output format. Not all options are applicable to all queries; for example, "CSV" is appropriate for properties queries but "SDF" might be used for a record_type query. See PUGREST, "Output".

Examples

julia> using PubChemCrawler, CSV, DataFrames, JSON3

julia> cids = [get_cid(name="cyclic guanosine monophosphate"), get_cid(name="aspirin")]
2-element Array{Int64,1}:
 135398570
      2244

julia> CSV.File(get_for_cids(cids; properties="MolecularFormula,XLogP", output="CSV")) |> DataFrame
2×3 DataFrame
 Row │ CID        MolecularFormula  XLogP
     │ Int64      String            Float64
─────┼──────────────────────────────────────
   1 │ 135398570  C10H12N5O7P          -3.4
   2 │      2244  C9H8O4                1.2

julia> open("/tmp/aspirin_3d.sdf", "w") do io    # save the 3d SDF file for aspirin (CID 2244)
           write(io, get_for_cids(2244; record_type="3d", output="SDF"))
       end
4055

julia> dct = JSON3.read(get_for_cids(cids; xrefs="RN,", output="JSON"));   # get the Registry Number(s) (CAS)

julia> dct[:InformationList][:Information]
2-element JSON3.Array{JSON3.Object,Array{UInt8,1},SubArray{UInt64,1,Array{UInt64,1},Tuple{UnitRange{Int64}},true}}:
 {
   "CID": 135398570,
    "RN": [
            "40732-48-7",
            "7665-99-8"
          ]
}
 {
   "CID": 2244,
    "RN": [
            "11126-35-5",
            "156865-15-5",
            "50-78-2",
            "52080-78-1",
            "921943-73-9",
            "98201-60-6",
            "99512-66-0"
          ]
}

atomcounts = parse_formula(str::AbstractString)

Parse str as a chemical formula, return a list of atom=>multiplicity pairs.

Example

julia> parse_formula("C2CaH2O6")
4-element Vector{Pair{String, Int64}}:
  "C" => 2
 "Ca" => 1
  "H" => 2
  "O" => 6

rex = atomregex(chemicalsymbol)

Create a regular expression for detecting how many atoms of type chemicalsymbol are in a molecular formula.

Examples

The formula for calcium bicarbonate is Ca(HCO3)2, i.e., C2CaH2O6.

julia> match(atomregex("C"), "C2CaH2O6")
RegexMatch("C2", 1="2")

julia> match(atomregex("Ca"), "C2CaH2O6")
RegexMatch("Ca", 1="")

julia> match(atomregex("H"), "C2CaH2O6")
RegexMatch("H2", 1="2")

julia> match(atomregex("O"), "C2CaH2O6")
RegexMatch("O6", 1="6")

Note that the regex for "C" does not match "Ca".