Calculate the half maximal inhibitory concentration (IC50) for each compound used in a SARS-CoV-2 study

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calculate-the-half-maximal-inhibitory-concentratio
calculate-the-half-maximal-inhibitory-concentratio
calculate-the-half-maximal-inhibitory-concentratio
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This notebook demonstrates how to retrieve metadata associated to the paper A SARS-CoV-2 cytopathicity dataset generated by high-content screening of a large drug repurposing collection and available in IDR at idr0094-ellinger-sarscov2 . Over 300 compounds were used in this investigation. This notebook allows the user to calculate the half maximal inhibitory concentration (IC50) for each compound. IC50 is a measure of the potency of a substance in inhibiting a specific biological or biochemical function. IC50 is a quantitative measure that indicates how much of a particular inhibitory substance (e.g. drug) is needed to inhibit, in vitro, a given biological process or biological component by 50%. User can download the IC50 for each compound used in that study

A shiny app is also available for dynamic plotting of the IC50 curve for each compound. This R shiny app can be launched in My Binder

Inputs

Parameters needed to configure the workflow:

screenId : Identifier of a screen in IDR.

Ouputs

Output file generated:

ic50.csv : Comma separate value file containing the IC50 for each compound.

Code Snippets

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# Parameters:
screenId = 2603
Jupyter Notebook From line 2 of notebooks/idr0094-ic50_loadtable.ipynb 
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# Load the libraries
suppressPackageStartupMessages(library(romero.gateway))
suppressPackageStartupMessages(library(dplyr))
suppressPackageStartupMessages(library(drc))
Jupyter Notebook dplyr From line 7 of notebooks/idr0094-ic50_loadtable.ipynb 
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server <- OMEROServer(host = 'wss://idr.openmicroscopy.org/omero-ws', port = 443L, username='public', password='public')
server <- connect(server)
paste('Successfully logged in as', server@user$getUserName())
Jupyter Notebook OMERO From line 14 of notebooks/idr0094-ic50_loadtable.ipynb 
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tableName <- 'bulk_annotations'
Jupyter Notebook From line 20 of notebooks/idr0094-ic50_loadtable.ipynb 
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screen <- loadObject(server, "ScreenData", screenId)

annos <- getAnnotations(server, 'ScreenData', getOMEROID(screen), nameFilter = tableName)
annotationFileID = as.integer(annos$FileID)

df <- loadDataframe(screen, annotationFileID)
df
Jupyter Notebook From line 24 of notebooks/idr0094-ic50_loadtable.ipynb 
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names(df)[names(df) == 'Compound Name'] <- "CompoundName"
names(df)[names(df) == 'Compound InChIKey'] <- 'InChIKey'
names(df)[names(df) == 'Compound Concentration (microMolar)'] <- "Concentration"
names(df)[names(df) == 'Percentage Inhibition (DPC)'] <- "Inhibition"
Jupyter Notebook From line 34 of notebooks/idr0094-ic50_loadtable.ipynb 
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compoundName <- "Remdesivir"
inChIKey <- "RWWYLEGWBNMMLJ-YSOARWBDSA-N"
Jupyter Notebook InChIKey From line 41 of notebooks/idr0094-ic50_loadtable.ipynb 
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get_id <- function(x) {
    value <- unlist(strsplit(x, split="="))[2]
    id <- unlist(strsplit(value, split=")"))[1]
}

filter_data <- function(df, value) {
    dfcopy <- cbind(df)
    dfcopy <- filter(dfcopy, CompoundName == value)
    df1 <- subset(dfcopy, select=c("Concentration", "Inhibition", "Well"))
    df1 <- cbind(df1[c("Concentration", "Inhibition")], apply(df1[c("Well")], 1, get_id))
    names(df1)[3] <- "Well"
    data <- mutate_all(df1, function(x) as.numeric(as.character(x)))
    data <- data[order(data$Concentration),]
}
Jupyter Notebook From line 46 of notebooks/idr0094-ic50_loadtable.ipynb 
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data <- filter_data(df, compoundName)
nrow(data)
Jupyter Notebook From line 63 of notebooks/idr0094-ic50_loadtable.ipynb 
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cols <- 2
n <- nrow(data)
m <- 4

values <- vector()
par(mfrow = c(m, cols))
par(mar=c(0,0,2,0))
par(oma=c(0,0,10,5))
for(i in 1:n) {
    row <- data[i,]
    if (!is.element(row$Concentration, values)) {
        values <- c(values, row$Concentration)
        well <- loadObject(server, "WellData", row$Well)
        image <- getImages(well, 0)
        thumb <- getThumbnail(image)
        plot(0:1, 0:1, type="n", ann=FALSE, axes=FALSE)
        rasterImage(thumb, 0, 0, 1, 1)
        title(main=paste(row$Concentration, 'uM '), font.main=2, cex.main=2)
    }     
}
mtext(paste("Compound:", compoundName), outer = TRUE, font=2, cex=2, side=3, line=1)
Jupyter Notebook From line 68 of notebooks/idr0094-ic50_loadtable.ipynb 
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disconnect(server)
Jupyter Notebook From line 92 of notebooks/idr0094-ic50_loadtable.ipynb 
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calculate_IC50 <- function(data){
  IC50 <- NA
  data.LL.4 <- NULL
  ctest <- filter(data, Inhibition != "NaN")
  data.LL.4 <- drm(Inhibition ~ Concentration, data = ctest, fct = LL.4(), control = drmc(errorm=FALSE))
  if (is.null(data.LL.4$convergence)) {
      IC50 <- ED(data.LL.4, 50, interval = "delta")[1]
  }
  returned_values <- list("ic50" = IC50, "data" = data.LL.4)
}
Jupyter Notebook From line 96 of notebooks/idr0094-ic50_loadtable.ipynb 
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values <- calculate_IC50(data)
IC50 <- values$ic50
IC50
Jupyter Notebook From line 109 of notebooks/idr0094-ic50_loadtable.ipynb 
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options(repr.plot.width=6, repr.plot.height=5.8)
plot(values$data, broken = TRUE, type = "all",
     main = "Dose Response Curve (DRC)", xlim = c(0, 100),
     xlab = "Log Concentration (uM)",
     ylab = "Percent Inhibition (percent)")
abline(h = 50, col = "cyan")
abline(v = IC50, col = "green")
Jupyter Notebook From line 115 of notebooks/idr0094-ic50_loadtable.ipynb 
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compounds <- unique(as.vector(df["CompoundName"]))
Jupyter Notebook From line 125 of notebooks/idr0094-ic50_loadtable.ipynb 
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ic <- vector()
cn <- vector()
for(i in 1:nrow(compounds)) {
    c <- compounds[i,]
    if (c != "") {
      d <- filter_data(df, c) 
      results <- calculate_IC50(d)
      ic <- c(ic, results$ic50)
      cn <- c(cn, c)
    }
}

result <- data.frame(cn, ic)
x <- c("Compound Name", "IC50 (uM)")
colnames(result) <- x
Jupyter Notebook From line 129 of notebooks/idr0094-ic50_loadtable.ipynb 
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setwd(path.expand('~'))
write.csv(result, "ic50.csv")
Jupyter Notebook From line 147 of notebooks/idr0094-ic50_loadtable.ipynb
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Created: 1yr ago
Updated: 1yr ago
Maitainers: public
URL: https://github.com/IDR/idr0094-ellinger-sarscov2
Name: calculate-the-half-maximal-inhibitory-concentratio
Version: Version 1
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Copyright: Public Domain
License: BSD 2-Clause "Simplified" License
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