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library(webchem)
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, unionThe lc50 dataset provided with webchem
contains acute ecotoxicity of 124 insecticides. We’ll work with a subset
of these to obtain chemical names and octanal/water partitioning
coefficients from PubChem, and gas chromatography retention indices from
the NIST Web Book.
head(lc50)
#> cas value
#> 4 50-29-3 12.415277
#> 12 52-68-6 1.282980
#> 15 55-38-9 12.168138
#> 18 56-23-5 35000.000000
#> 21 56-38-2 1.539119
#> 36 57-74-9 98.400000
lc50_sub <- lc50[1:15, ]Usually a webchem workflow starts with translating and
retrieving chemical identifiers since most chemical information
databases use their own internal identifiers.
First, we will covert CAS numbers to InChIKey identifiers using the Chemical Translation Service. Then, we’ll use these InChiKeys to get Pubchem CompoundID numbers, to use for retrieving chemical properties from PubChem.
lc50_sub$inchikey <- unlist(cts_convert(lc50_sub$cas, from = "CAS", to = "InChIKey", match = "first", verbose = FALSE))
head(lc50_sub)
#> cas value inchikey
#> 4 50-29-3 12.415277 YVGGHNCTFXOJCH-UHFFFAOYSA-N
#> 12 52-68-6 1.282980 NFACJZMKEDPNKN-UHFFFAOYSA-N
#> 15 55-38-9 12.168138 PNVJTZOFSHSLTO-UHFFFAOYSA-N
#> 18 56-23-5 35000.000000 VZGDMQKNWNREIO-UHFFFAOYSA-N
#> 21 56-38-2 1.539119 LCCNCVORNKJIRZ-UHFFFAOYSA-N
#> 36 57-74-9 98.400000 BIWJNBZANLAXMG-UHFFFAOYSA-N
any(is.na(lc50_sub$inchikey))
#> [1] FALSEGreat, now we can retrieve PubChem CIDs. All get_*()
functions return a data frame containing the query and the retrieved
identifier. We can merge this with our dataset with
dplyr::full_join()
x <- get_cid(lc50_sub$inchikey, from = "inchikey", match = "first", verbose = FALSE)
library(dplyr)
lc50_sub2 <- full_join(lc50_sub, x, by = c("inchikey" = "query"))
head(lc50_sub2)
#> cas value inchikey cid
#> 1 50-29-3 12.415277 YVGGHNCTFXOJCH-UHFFFAOYSA-N 3036
#> 2 52-68-6 1.282980 NFACJZMKEDPNKN-UHFFFAOYSA-N 5853
#> 3 55-38-9 12.168138 PNVJTZOFSHSLTO-UHFFFAOYSA-N 3346
#> 4 56-23-5 35000.000000 VZGDMQKNWNREIO-UHFFFAOYSA-N 5943
#> 5 56-38-2 1.539119 LCCNCVORNKJIRZ-UHFFFAOYSA-N 991
#> 6 57-74-9 98.400000 BIWJNBZANLAXMG-UHFFFAOYSA-N 5993Functions that query chemical information databases begin with a
prefix that matches the database. For example, functions to query
PubChem begin with pc_ and functions to query ChemSpider
begin with cs_. In this example, we’ll get the names and
log octanol/water partitioning coefficients for each compound using
PubChem, and the number of aromatic rings within the chemical structure
using ChEMBL.
y <- pc_prop(lc50_sub2$cid, properties = c("IUPACName", "XLogP"))
y$CID <- as.character(y$CID)
lc50_sub3 <- full_join(lc50_sub2, y, by = c("cid" = "CID"))
head(lc50_sub3)
#> cas value inchikey cid
#> 1 50-29-3 12.415277 YVGGHNCTFXOJCH-UHFFFAOYSA-N 3036
#> 2 52-68-6 1.282980 NFACJZMKEDPNKN-UHFFFAOYSA-N 5853
#> 3 55-38-9 12.168138 PNVJTZOFSHSLTO-UHFFFAOYSA-N 3346
#> 4 56-23-5 35000.000000 VZGDMQKNWNREIO-UHFFFAOYSA-N 5943
#> 5 56-38-2 1.539119 LCCNCVORNKJIRZ-UHFFFAOYSA-N 991
#> 6 57-74-9 98.400000 BIWJNBZANLAXMG-UHFFFAOYSA-N 5993
#> IUPACName
#> 1 1-chloro-4-[2,2,2-trichloro-1-(4-chlorophenyl)ethyl]benzene
#> 2 2,2,2-trichloro-1-dimethoxyphosphorylethanol
#> 3 dimethoxy-(3-methyl-4-methylsulfanylphenoxy)-sulfanylidene-lambda5-phosphane
#> 4 tetrachloromethane
#> 5 diethoxy-(4-nitrophenoxy)-sulfanylidene-lambda5-phosphane
#> 6 1,3,4,7,8,9,10,10-octachlorotricyclo[5.2.1.02,6]dec-8-ene
#> XLogP
#> 1 6.9
#> 2 0.5
#> 3 4.1
#> 4 2.8
#> 5 3.8
#> 6 4.9The IUPAC names are long and unwieldy, and one could use
pc_synonyms() to choose better names. Several other
functions return synonyms as well, even though they are not explicitly
translator type functions. We’ll see an example of that next.
Many of the chemical databases webchem can query contain
vast amounts of information in a variety of structures. Therefore, some
webchem functions return nested lists rather than data
frames. chembl_query() is one such function.
To look up entries in ChEMBL we need ChEMBL ID-s. These can be found
on the PubChem page of each compound within the ChEMBL ID section and
can be programmatically retrieved using pc_sect().
lc50_sub3$chembl_id <- pc_sect(x$cid, "ChEMBL ID")$Result
out <- chembl_query(lc50_sub3$chembl_id, verbose = FALSE)out is a nested list which you can inspect with
View(). It has an element for each query, and within each
query, many elements corresponding to different properties in the
database. To extract a single property from all queries, we need to use
a mapping function such as sapply().
lc50_sub3$aromatic_rings <- sapply(out, function(y) {
# return NA if entry cannot be found in ChEMBL
if (length(y) == 1 && is.na(y)) return(NA)
# return the number of aromatic rings
y$molecule_properties$aromatic_rings
})
lc50_sub3$common_name <- sapply(out, function(y) {
# return NA if entry cannot be found in ChEMBL
if (length(y) == 1 && is.na(y)) return(NA)
# return preferred name
ifelse(!is.null(y$pref_name), y$pref_name, NA)
})#tidy up columns
lc50_done <- dplyr::select(lc50_sub3, common_name, cas, inchikey, XLogP, aromatic_rings)
head(lc50_done)
#> common_name cas inchikey XLogP aromatic_rings
#> 1 CHLOROPHENOTHANE 50-29-3 YVGGHNCTFXOJCH-UHFFFAOYSA-N 6.9 2
#> 2 TRICHLORFON 52-68-6 NFACJZMKEDPNKN-UHFFFAOYSA-N 0.5 0
#> 3 FENTHION 55-38-9 PNVJTZOFSHSLTO-UHFFFAOYSA-N 4.1 1
#> 4 CARBON TETRACHLORIDE 56-23-5 VZGDMQKNWNREIO-UHFFFAOYSA-N 2.8 0
#> 5 PARATHION 56-38-2 LCCNCVORNKJIRZ-UHFFFAOYSA-N 3.8 1
#> 6 CHLORDANE 57-74-9 BIWJNBZANLAXMG-UHFFFAOYSA-N 4.9 0These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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