pK: pK values for the side chain of charged amino acids from...

In seqinr: Biological Sequences Retrieval and Analysis

pK values for the side chain of charged amino acids from various sources

Description

This compilation of pK values is from Joanna Kiraga (2008).

Usage

data(pK)

Format

A data frame with the seven charged amino-acid in row and six sources in column. The rownames are the one-letter code for amino-acids.

Source

Table 2 in Kiraga (2008).

References

Kiraga, J. (2008) Analysis and computer simulations of variability of isoelectric point of proteins in the proteomes. PhD thesis, University of Wroclaw, Poland.

Bjellqvist, B., Hughes, G.J., Pasquali, Ch., Paquet, N., Ravier, F., Sanchez, J.Ch., Frutige,r S., Hochstrasser D. (1993) The focusing positions of polypeptides in immobilized pH gradients can be predicted from their amino acid sequences. Electrophoresis, 14:1023-1031.

EMBOSS data were from release 5.0 and were still the same in release 6.6 https://emboss.sourceforge.net/apps/release/6.6/emboss/apps/iep.html last visited 2016-06-03.

Murray, R.K., Granner, D.K., Rodwell, V.W. (2006) Harper's illustrated Biochemistry. 27th edition. Published by The McGraw-Hill Companies.

Sillero, A., Maldonado, A. (2006) Isoelectric point determination of proteins and other macromolecules: oscillating method. Comput Biol Med., 36:157-166.

Solomon, T.W.G. (1998) Fundamentals of Organic Chemistry, 5th edition. Published by Wiley.

Stryer L. (1999) Biochemia. czwarta edycja. Wydawnictwo Naukowe PWN.

citation("seqinr")

Examples

data(pK)
data(SEQINR.UTIL) # for N and C terminal pK values
prot <- s2c("ACDEFGHIKLMNPQRSTVWY")
compoAA <- table(factor(prot, levels = LETTERS))
nTermR <- which(LETTERS == prot[1])
cTermR <- which(LETTERS == prot[length(seq)])

computeCharge <- function(pH, compoAA, pK, nTermResidue, cTermResidue){
  cter <- 10^(-SEQINR.UTIL$pk[cTermResidue,1]) /
     (10^(-SEQINR.UTIL$pk[cTermResidue,1]) + 10^(-pH))
  nter <- 10^(-pH) / (10^(-SEQINR.UTIL$pk[nTermResidue,2]) + 10^(-pH))
  carg <- as.vector(compoAA['R'] * 10^(-pH) / (10^(-pK['R']) + 10^(-pH)))
  chis <- as.vector(compoAA['H'] * 10^(-pH) / (10^(-pK['H']) + 10^(-pH)))
  clys <- as.vector(compoAA['K'] * 10^(-pH) / (10^(-pK['K']) + 10^(-pH)))
  casp <- as.vector(compoAA['D'] * 10^(-pK['D']) /(10^(-pK['D']) + 10^(-pH)))
  cglu <- as.vector(compoAA['E'] * 10^(-pK['E']) / (10^(-pK['E']) + 10^(-pH)))
  ccys <- as.vector(compoAA['C'] * 10^(-pK['C']) / (10^(-pK['C']) + 10^(-pH)))
  ctyr <- as.vector(compoAA['Y'] * 10^(-pK['Y']) / (10^(-pK['Y']) + 10^(-pH)))
  charge <- carg + clys + chis + nter - (casp + cglu + ctyr + ccys + cter)
  return(charge)
}

pHseq <- seq(from = 0, to = 14, by = 0.1)
Bje <- pK$Bjellqvist
names(Bje) <- rownames(pK)
res <- computeCharge(pHseq, compoAA, Bje, nTermR, cTermR)
plot(pHseq, res, type = "l", ylab = "Charge", las = 1,
  main = paste("Charge of protein\n",c2s(prot)),
  xlab = "pH")
for(j in 2:ncol(pK)){
  src <- pK[,j]
  names(src) <- rownames(pK)
  res <- computeCharge(pHseq, compoAA, src, nTermR, cTermR)
  lines(pHseq, res, lty = j, col = rainbow(5)[j])
}

abline(h=0)
abline(v=computePI(prot))
legend("bottomleft", inset = 0.01, colnames(pK), lty = 1:6, col = c("black", rainbow(5)))

seqinr documentation built on May 29, 2024, 6:36 a.m.