metrics: Calculate Compositional Metrics for Proteins

Description

These functions calculate compositional metrics of proteins given a data frame of amino acid compositions.

Usage

ZCAA(AAcomp, nothing = NULL)
  H2OAA(AAcomp, basis = getOption("basis"))
  O2AA(AAcomp, basis = getOption("basis"))
  GRAVY(AAcomp)
  pI(AAcomp)
  MWAA(AAcomp)
  basis.text(basis)

Arguments

AAcomp

data frame, amino acid compositions

nothing

dummy argument

basis

character, basis species

Details

Columns in AAcomp should be named with the three-letter abbreviations for the amino acids (e.g. Ala). The metrics are described below:

ZCAA

Average oxidation state of carbon () (Dick, 2014). nothing is an extra argument that does nothing. It is provided so that do.call can be used to run ZCAA or H2OAA with the same number of arguments.

This metric is independent of the choice of basis species.

H2OAA

Stoichiometric hydration state () per residue. The available basis species are:

QEC - glutamine, glutamic acid, cysteine, , (Dick et al., 2020) (this is the default for getOption("basis"))
QCa - glutamine, cysteine, acetic acid, ,
Any other valid basis specification for basis, such as CHNOS for , , , , and

O2AA

Stoichiometric oxidation state () per residue. The basis species also affect this calculation.

GRAVY

Grand average of hydropathicity. Values of the hydropathy index for individual amino acids are from Kyte and Doolittle (1982).

pI

Isoelectric point. The net charge for each ionizable group was pre-calculated from pH 0 to 14 at intervals of 0.01. The isoelectric point is found as the pH where the sum of charges of all groups in the protein is closest to zero. The values for the terminal groups and sidechains are taken from Bjellqvist et al. (1993) and Bjellqvist et al. (1994); note that the calculation does not implement position-specific adjustments described in the latter paper. The number of N- and C-terminal groups is taken to be one, unless a value for chains (number of polypeptide chains) is given in AAcomp.

MWAA

Molecular weight per residue.

Note that is a per-carbon average, but is a per-residue average. The contribution of from the terminal groups of proteins is counted, so shorter proteins have slightly greater .

Tests for a few proteins (see examples) indicate that GRAVY and pI are equal those calculated with the ProtParam tool (https://web.expasy.org/protparam/; Gasteiger et al., 2005).

basis.text is used in the vignettes to generate a textual description of the names of the basis species, except and , for one of the keywords QEC or QCa.

References

Bjellqvist, B., Hughes, G. J., Pasquali, C., Paquet, N., Ravier, F., Sanchez, J.-C., Frutiger, S. and Hochstrasser, D. (1993) The focusing positions of polypeptides in immobilized pH gradients can be predicted from their amino acid sequences. Electrophoresis 14, 1023--1031. 10.1002/elps.11501401163

Bjellqvist, B. and Basse, B. and Olsen, E. and Celis, J. E. (1994) Reference points for comparisons of two-dimensional maps of proteins from different human cell types defined in a pH scale where isoelectric points correlate with polypeptide compositions. Electrophoresis 15, 529--539. 10.1002/elps.1150150171

Dick, J. M. (2014) Average oxidation state of carbon in proteins. J. R. Soc. Interface 11, 20131095. 10.1098/rsif.2013.1095

Dick, J. M., Yu, M. and Tan, J. (2020) Uncovering chemical signatures of salinity gradients through compositional analysis of protein sequences. Biogeosciences Discussions. 10.5194/bg-2020-146

Gasteiger, E., Hoogland, C., Gattiker, A., Duvaud, S., Wilkins, M. R., Appel, R. D. and Bairoch, A. (2005) Protein identification and analysis tools on the ExPASy server. In J. M. Walker (Ed.), The Proteomics Protocols Handbook (pp. 571--607). Totowa, NJ: Humana Press Inc. 10.1385/1-59259-890-0:571

Kyte, J. and Doolittle, R. F. (1982) A simple method for displaying the hydropathic character of a protein. J. Mol. Biol. 157, 105--132. 10.1016/0022-2836(82)90515-0

Examples

Run this code

# NOT RUN {
# we need CHNOSZ for these examples
require(CHNOSZ)

# for reference, compute ZC of alanine and glycine "by hand"
ZC.Gly <- ZC("C2H5NO2")
ZC.Ala <- ZC("C3H7NO2")
# define the composition of a Gly-Ala-Gly tripeptide
AAcomp <- data.frame(Gly = 2, Ala = 1)
# calculate the ZC of the tripeptide (value: 0.571)
ZC.GAG <- ZCAA(AAcomp)
# this is equal to the carbon-number-weighted average of the amino acids
nC.Gly <- 2 * 2
nC.Ala <- 1 * 3
ZC.average <- (nC.Gly * ZC.Gly + nC.Ala * ZC.Ala) / (nC.Ala + nC.Gly)
stopifnot(all.equal(ZC.GAG, ZC.average))

# compute the per-residue nH2O of Gly-Ala-Gly
basis("QEC")
nH2O.GAG <- species("Gly-Ala-Gly")$H2O
# divide by the length to get residue average (we keep the terminal H-OH)
nH2O.residue <- nH2O.GAG / 3
# compare with the value calculated by H2OAA() (-0.2)
nH2O.H2OAA <- H2OAA(AAcomp, "QEC")
stopifnot(all.equal(nH2O.residue, nH2O.H2OAA))

# calculate GRAVY for a few proteins
# first get the protein index in CHNOSZ's list of proteins
iprotein <- pinfo(c("LYSC_CHICK", "RNAS1_BOVIN", "AMYA_PYRFU"))
# then get the amino acid compositions
AAcomp <- pinfo(iprotein)
# then calculate GRAVY
Gcalc <- as.numeric(GRAVY(AAcomp))
# these are equal to values obtained with ProtParam on uniprot.org
# https://web.expasy.org/cgi-bin/protparam/protparam1?P00698@19-147@
# https://web.expasy.org/cgi-bin/protparam/protparam1?P61823@27-150@
# https://web.expasy.org/cgi-bin/protparam/protparam1?P49067@2-649@
Gref <- c(-0.472, -0.663, -0.325)
stopifnot(all.equal(round(Gcalc, 3), Gref))
# also calculate molecular weight of the proteins
MWcalc <- as.numeric(MWAA(AAcomp)) * protein.length(iprotein)
MWref <- c(14313.14, 13690.29, 76178.25)
stopifnot(all.equal(round(MWcalc, 2), MWref))

# calculate pI for a few proteins
iprotein <- pinfo(c("LYSC_CHICK", "RNAS1_BOVIN", "AMYA_PYRFU", "CSG_HALJP"))
AAcomp <- pinfo(iprotein)
pI_calc <- pI(AAcomp)
# reference values calculated with ProtParam on uniprot.org
# LYSC_CHICK: residues 19-147 (sequence v1)
# RNAS1_BOVIN: residues 27-150 (sequence v1)
# AMYA_PYRFU: residues 2-649 (sequence v2)
# CSG_HALJP: residues 35-862 (sequence v1)
pI_ref <- c(9.32, 8.64, 5.46, 3.37)
stopifnot(all.equal(as.numeric(pI_calc), pI_ref))
# }