load_sipes2017: Load CLint and Fup QSPR predictions from Sipes et al 2017.

In httk: High-Throughput Toxicokinetics

Load CLint and Fup QSPR predictions from Sipes et al 2017.

Description

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.

Usage

load_sipes2017(overwrite = FALSE, 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.
target.env	The environment where the new chem.physical_and_invitro.data is loaded. Defaults to global environment.

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).

Value

data.frame

An updated version of chem.physical_and_invitro.data.

Author(s)

Robert Pearce and John Wambaugh

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

Examples

# 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())
                        

httk documentation built on Sept. 11, 2024, 9:32 p.m.