# Michaelis-Menten type enzyme kinetics fitting (S-v plot)
# Multiple curves version
# Written by S. Fushinobu (2019.10.22)
# Thanks to Carly Huitema & Geoff P Horsman
# Edit the parameters below
MM.df <- read.csv("/Users/fushi/Documents/R/Michaelis-multi.csv")
Mtitle <- "Michaelis-Menten plot"  # main title of the plot
Substname <- "Substrate"
Substunit <- " (mM)"
Vunit <- " (units/mg)"
Kminit <- 4               # initial values for fitting
Vmaxinit <- 35
mono <- FALSE              # FALSE for color, TRUE for monochrome

ncurve <- ncol(MM.df) -1
if (mono) {
plot.color <- rep(1,ncurve)
} else {
plot.color <- rainbow(ncurve)
}

#plot blank
plot(0,0, pch="", xlim=c(0,max(MM.df[,1], na.rm=TRUE)),ylim=c(0,max(MM.df[,-1], na.rm=TRUE)), main=Mtitle,xlab=paste(Substname,Substunit),ylab=paste("v",Vunit))

# write legends
labels <- colnames(MM.df)[-1]
legend("topleft", legend = labels, pch=c(1:length(labels)), lty=c(1:length(labels)), col=plot.color[1:length(labels)], bg="white")

for (i in 1:ncurve){
ithdata.df <- MM.df[,1]
ithdata.df <- cbind(ithdata.df,MM.df[i+1])
colnames(ithdata.df) <- c("conc","rate")
ithdata.df <- subset(ithdata.df, rate != "NA")
points(ithdata.df$conc,ithdata.df$rate, col=plot.color[i], pch=i)
MM.nls <- nls(rate ~ (Vmax * conc / (Km + conc)), data=ithdata.df, start=list(Km=Kminit, Vmax=Vmaxinit))
summary(MM.nls)$parameters
Km <- unname(coef(MM.nls)["Km"])
Vmax <- unname(coef(MM.nls)["Vmax"])
curve(Vmax*x/(Km+x),0,max(ithdata.df$conc),add=TRUE,col=plot.color[i],lty=i)

mtext(paste(colnames(MM.df)[i+1],": Km = ",signif(Km,digits=3),"±",signif(summary(MM.nls)$parameters[1,2],digits=3),Substunit,"; Vmax = ",signif(Vmax,digits=3),"±",signif(summary(MM.nls)$parameters[2,2],digits=3),Vunit),side=1,line=-i,adj=0)
}