ADMET Predictor: Import 21 structure to a new project

library(tidyverse)
library(kableExtra)
library(DT)
library(gastroPlusAPI)
library(gastroPlusRModuLens)

if (rstudioapi::isAvailable()){
  current_working_directory <- dirname(rstudioapi::getSourceEditorContext()$path)
  setwd(current_working_directory)
}

gpx_service <- start_service(verbose=FALSE)

✔ Configured the GastroPlus Service

gpx_service$is_alive()

[1] TRUE

project_path = "../../ProjectFiles/ADMET Predictor.gpproject"
structure_file = "../../ProjectFiles/ap_import_files/21-Comps-w-ExperData-3D.sdf"
open_project(project_path)
current_compounds <- unlist(get_project_assets(AssetType$Compound)$assets)

load_structure(structure_file)

#Get import configuration
import_configuration <- get_admet_predictor_import_configuration()

#View the contents of the import configuration
#str(import_configuration$toJSON()) 

#Make changes to the configuration
import_configuration$dose_regimen_name <- 'PO capsule 100mg'
import_configuration$physiology_schedule_name <-'Human 30y 85.53kg schedule'
set_admet_predictor_import_configuration(import_configuration)


#Now import the structure with the updated configuration
import_structure()

# get the runs of the project after the import
get_runs()

# A tibble: 1 × 1
  run_name
  <chr>   
1 Run     

# set the run_name for the ADMET predictor import run to a variable
run_name= "Run"

# get the simulations in the run from the import. name of the run created with the import: "Run"
get_simulations_in_run("Run")

[[1]]
[1] "Simulation for Amiloride"

[[2]]
[1] "Simulation for Amoxicillin"

[[3]]
[1] "Simulation for Desipramine"

[[4]]
[1] "Simulation for Antipyrine"

[[5]]
[1] "Simulation for Atenolol"

[[6]]
[1] "Simulation for Carbamazepine"

[[7]]
[1] "Simulation for Enalaprilat"

[[8]]
[1] "Simulation for Furosemide"

[[9]]
[1] "Simulation for Fluvastatin"

[[10]]
[1] "Simulation for Hydrochlorothiazide"

[[11]]
[1] "Simulation for Methyldopa"

[[12]]
[1] "Simulation for Ketoprofen"

[[13]]
[1] "Simulation for Levodopa"

[[14]]
[1] "Simulation for Lisinopril"

[[15]]
[1] "Simulation for Mannitol"

[[16]]
[1] "Simulation for Metoprolol"

[[17]]
[1] "Simulation for Naproxen"

[[18]]
[1] "Simulation for Verapamil"

[[19]]
[1] "Simulation for Propranolol"

[[20]]
[1] "Simulation for Ranitidine"

[[21]]
[1] "Simulation for Terbutaline"

# execute the run with the ADMET predictor import simulations
execute_run(run_name)

all_compounds <- unlist(get_project_assets(AssetType$Compound)$assets)

admet_import_compounds <- setdiff(all_compounds,current_compounds)

# gastroPlusRModuLens function: build the series for the ADMET Predictor import
series_descriptors <- build_series_descriptors(
  compound = admet_import_compounds,
  c(CompartmentType[["SystemicCirculation"]], StateType[["ConcentrationPlasma"]])
)

series_descriptors

 [1] "Levodopa - Systemic Circulation - Concentration Plasma"           
 [2] "Carbamazepine - Systemic Circulation - Concentration Plasma"      
 [3] "Mannitol - Systemic Circulation - Concentration Plasma"           
 [4] "Atenolol - Systemic Circulation - Concentration Plasma"           
 [5] "Fluvastatin - Systemic Circulation - Concentration Plasma"        
 [6] "Hydrochlorothiazide - Systemic Circulation - Concentration Plasma"
 [7] "Methyldopa - Systemic Circulation - Concentration Plasma"         
 [8] "Antipyrine - Systemic Circulation - Concentration Plasma"         
 [9] "Propranolol - Systemic Circulation - Concentration Plasma"        
[10] "Lisinopril - Systemic Circulation - Concentration Plasma"         
[11] "Ketoprofen - Systemic Circulation - Concentration Plasma"         
[12] "Furosemide - Systemic Circulation - Concentration Plasma"         
[13] "Enalaprilat - Systemic Circulation - Concentration Plasma"        
[14] "Ranitidine - Systemic Circulation - Concentration Plasma"         
[15] "Amiloride - Systemic Circulation - Concentration Plasma"          
[16] "Desipramine - Systemic Circulation - Concentration Plasma"        
[17] "Amoxicillin - Systemic Circulation - Concentration Plasma"        
[18] "Metoprolol - Systemic Circulation - Concentration Plasma"         
[19] "Naproxen - Systemic Circulation - Concentration Plasma"           
[20] "Verapamil - Systemic Circulation - Concentration Plasma"          
[21] "Terbutaline - Systemic Circulation - Concentration Plasma"        

# gastroPlusRModuLens function: get the series in the ADMET Predictor run

series_data_APimport <- get_series_data_run(run_name=run_name,series_descriptor = series_descriptors)
series_data_APimport <- series_data_APimport %>% mutate(compound=str_extract(series_name, "^[^-]+") %>% trimws())

# Getting the plotting environment ready
# set default ggplot2 theme
theme_set(
  theme_gastroPlus_grid()
)
set_default_ggplot_options()

#plot the simulations faceted
plot_series_data(series_data_APimport,
                 x_label = "Time (h)",
                 y_label = "Concentration (ng/mL)",
) +
  scale_y_continuous()+
  facet_wrap(~compound,scales = "free_y")+
  labs(color=NULL)

Scale for y is already present.
Adding another scale for y, which will replace the existing scale.

#Plot the simulations in one plot
plot_series_data(series_data_APimport,
                 color= compound,
                 x_label = "Time (h)",
                 y_label = "Concentration (ng/mL)",
) 

#get all the summary outputs
summary_output_APimport <- get_summary_output_tidy(run_name) %>% 
  filter(!name %in% c("total_dose"))

ggplot(summary_output_APimport, aes(x = compound, y = value)) +
    geom_col(position = "dodge") + # geom_col for bar charts with a pre-calculated y-value
    facet_wrap(~ label, scales = "free_y", ncol = 3) + 
    labs(
        title = "ADMET PK parameters by Compound, Faceted by key Summary output PK parameters",
        x = "Compound",
        y = "Value",
        fill = "Summary Parameter Name"
    )+theme(
    axis.text.x = element_text(angle = 45, hjust = 1), 
    legend.position = "right"
  )

#change this variable to get the top ranking molecules
topn <- 3
#get the table of the ranking
summary_output_ranking <- summary_output_APimport %>% 
  arrange(name,value)  %>% 
  group_by(name) %>%
  mutate(
    rank = dense_rank(value),
    label = str_squish(label)
  ) %>%
  filter(rank %in% c(1:topn,(n()-(topn-1)):(n()))) %>% 
  ungroup() %>% 
  select(label, compound, value, rank)

 # View(summary_output_ranking)
kable(summary_output_ranking, format = "simple",
      caption = "Compound Rankings by ADMET Parameters",
      digits = 2)

gpx_service$kill()

[1] TRUE