# Load CLint and Fup QSPR predictions from Sipes et al 2017. This function returns an updated version of `chem.physical_and_invitro.data` that includes quantitative structure-property relationship (QSPR) predictions from Simulations Plus' ADMET predictor as used in Sipes et al. 2017, included in `sipes2017`. ```r load_sipes2017(overwrite = FALSE, chem_include = NULL, target.env = .GlobalEnv) ``` ## Arguments - `overwrite`: Only matters if load.image=FALSE. If overwrite=TRUE then existing data in chem.physical_and_invitro.data will be replaced by any predictions in Sipes et al. (2017) that is for the same chemical and property. If overwrite=FALSE (DEFAULT) then new data for the same chemical and property are ignored. Funbound.plasma values of 0 (below limit of detection) are overwritten either way. - `chem_include`: A vector of CAS numbers indicating only the chemicals to be included in the loading process. If set to `NULL` all applicable chemicals are loaded. (Default is `NULL`.) - `target.env`: The environment where the new `chem.physical_and_invitro.data` is loaded. Defaults to global environment. ## Returns - **data.frame**: An updated version of `chem.physical_and_invitro.data`. ## Details Because Clint and Fup are the only measurements required for many HTTK models, changing the number of chemicals for which a value is available will change the number of chemicals which are listed with the `get_cheminfo` command. Use the command `reset_httk` to return to the initial (measured only) `chem.physical_and_invitro.data` (for all parameters). ## Examples ```r # Count how many chemicals for which HTTK is available without the QSPR: num.chems <- length(get_cheminfo()) print(num.chems) # For chemicals with Sipes et al. (2017) Clint and Fup QSPR predictions, # add them to our chemical information wherever measured values are # unavailable: load_sipes2017() # Here's a chemical we didn't have before (this one is a good test since the # logP is nearly 10 and it probably wouldn't work in vitro): calc_css(chem.cas="26040-51-7") # Let's see how many chemicals we have now with the Sipes et al. (2017) # predictions data loaded: length(get_cheminfo()) # Now let us reset the chemical data to the initial version: reset_httk() # We should be back to our original number: num.chems == length(get_cheminfo()) # Demonstrate loading data for specific chemicals: # # Find chemicals with a clint and no fup: subset(chem.physical_and_invitro.data,!is.na(Human.Clint) & Human.Funbound.plasma==0)$CAS chem1 <- "101-05-3" chem2 <- "2971-36-0" # Take a look at what parameterize_steadystate gives (working from a default fup of 0.005): a1 <- parameterize_steadystate(chem.cas=chem1) a2 <- parameterize_steadystate(chem.cas=chem2) # load Sipes for this chemical: load_sipes2017(chem_include=chem1) # Check values, only fup for the first chemical should change: a3 <- parameterize_steadystate(chem.cas=chem1) a4 <- parameterize_steadystate(chem.cas=chem2) # All tests should be true: a1[["Clint"]] == a3[["Clint"]] a1[["Funbound.plasma"]] != a3[["Funbound.plasma"]] a2[["Clint"]] == a4[["Clint"]] a2[["Funbound.plasma"]] == a4[["Funbound.plasma"]] # load Sipes for this chemical, but allow it to overwrite the clint: load_sipes2017(chem_include=chem1, overwrite=TRUE) # Check values, both clint and fup for the first chemical should change: a5 <- parameterize_steadystate(chem.cas=chem1) a6 <- parameterize_steadystate(chem.cas=chem2) # All tests should be true: a1[["Clint"]] != a5[["Clint"]] a1[["Funbound.plasma"]] != a5[["Funbound.plasma"]] a2[["Clint"]] == a6[["Clint"]] a2[["Funbound.plasma"]] == a6[["Funbound.plasma"]] # Load Sipes for all chemicals, fup should change for second chemical: load_sipes2017() a7 <- parameterize_steadystate(chem.cas=chem1) a8 <- parameterize_steadystate(chem.cas=chem2) # All tests should be true: a1[["Clint"]] != a7[["Clint"]] a1[["Funbound.plasma"]] != a7[["Funbound.plasma"]] a2[["Clint"]] == a8[["Clint"]] a2[["Funbound.plasma"]] != a8[["Funbound.plasma"]] # load Sipes for this chemical, but allow it to overwrite all clints: load_sipes2017(overwrite=TRUE) # Both clint and fup should now be changed for second chemical: a9 <- parameterize_steadystate(chem.cas=chem1) a10 <- parameterize_steadystate(chem.cas=chem2) # All tests should be true: a1[["Clint"]] != a9[["Clint"]] a1[["Funbound.plasma"]] != a9[["Funbound.plasma"]] a2[["Clint"]] != a10[["Clint"]] a2[["Funbound.plasma"]] != a10[["Funbound.plasma"]] ``` ## References Sipes, Nisha S., et al. "An intuitive approach for predicting potential human health risk with the Tox21 10k library." Environmental Science & Technology 51.18 (2017): 10786-10796. ## See Also `reset_httk` `get_cheminfo` ## Author(s) Robert Pearce and John Wambaugh

load_sipes2017 function