# chents [](https://pkgdown.jrwb.de/chents/) [](https://jranke.r-universe.dev/chents) [](https://pkgdown.jrwb.de/chents/coverage/coverage.html) The R package **chents** provides some utilities for working with chemical entities in R. When first defining a chemical entity, some chemical information is retrieved from the [PubChem](https://pubchem.ncbi.nlm.nih.gov/) website using the [webchem](https://docs.ropensci.org/webchem/) package. ``` r library(chents) caffeine <- chent$new("caffeine") #> Querying PubChem ... #> Trying to get chemical information from RDKit using PubChem SMILES #> CN1C=NC2=C1C(=O)N(C(=O)N2C)C ``` If Python and [RDKit](https://rdkit.org) (\> 2015.03) are installed and configured for use with the [reticulate](https://rstudio.github.io/reticulate/) package, some additional chemical information including a 2D graph are computed. The print method gives an overview of the information that was collected. ``` r print(caffeine) #> #> Identifier $identifier caffeine #> InChI Key $inchikey RYYVLZVUVIJVGH-UHFFFAOYSA-N #> SMILES string $smiles: #> PubChem #> "CN1C=NC2=C1C(=O)N(C(=O)N2C)C" #> Molecular weight $mw: 194.2 #> PubChem synonyms (up to 10): #> [1] "caffeine" "58-08-2" #> [3] "Guaranine" "1,3,7-Trimethylxanthine" #> [5] "Methyltheobromine" "Theine" #> [7] "Thein" "Cafeina" #> [9] "Koffein" "Mateina" ``` There is a very simple plotting method for the chemical structure. ``` r plot(caffeine) ```  Additional information can be (but is rarely ever) read from a local .yaml file. This information can be leveraged e.g. by the [PEC_soil](https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html) function of the ‘pfm’ package. If you have a so-called ISO common name of a pesticide active ingredient, you can use the ‘pai’ class derived from the ‘chent’ class, which starts with querying the [BCPC compendium](http://www.bcpcpesticidecompendium.org/) first. ``` r lambda <- pai$new("lambda-cyhalothrin") #> Querying BCPC for lambda-cyhalothrin ... #> Querying PubChem ... #> Trying to get chemical information from RDKit using PubChem SMILES #> CC1([C@@H]([C@@H]1C(=O)O[C@@H](C#N)C2=CC(=CC=C2)OC3=CC=CC=C3)/C=C(/C(F)(F)F)\Cl)C #> RDKit mw is 449.856 #> mw is 449.8 plot(lambda) ```  ## Installation You can conveniently install chents from the repository kindly made available by the R-Universe project: install.packages("chents", repos = c("https://jranke.r-universe.dev", "https://cran.r-project.org")) In order to profit from the chemoinformatics, you need to install RDKit and its python bindings. On a Debian type Linux distribution, just use sudo apt install python3-rdkit If you use this package on Windows or MacOS, I would be happy to include installation instructions here if you share them with me, e.g. via a Pull Request. ## Configuration of the Python version to use On Debian type Linux distributions, you can use the following line in your global or project specific `.Rprofile` file to tell the `reticulate` package to use the system Python version that will find the RDKit installed in the system location. Sys.setenv(RETICULATE_PYTHON="/usr/bin/python3")