protein {CHNOSZ} | R Documentation |
Retrieve the amino acid compositions or thermodynamic properties and equations of state parameters of proteins.
protein(protein,organism=NULL,online=thermo$opt$online) protein.residue(proteins) protein.info()
protein |
character, protein identifiers, or numeric, indices of protein (rownumbers of thermo$protein ), or dataframe, protein compositions to sum into new protein. |
organism |
character, organism identifiers (required if protein is character), or physical state (optional if protein is numeric). |
proteins |
character, names of proteins. |
online |
logical, try an online search if the specified protein(s) are not found locally? |
protein
is a function to query the protein database and to perform group additivity calculations of the standard molal thermodynamic properties and equations of state parameters of proteins.
The user will generally specify a protein by submitting the name of one in the argument to a function like species
or subcrt
. To distinguish names of proteins from those of other species, protein names in CHNOSZ have an underscore ("_") somewhere in their name, as in LYSC_CHICK.
If two character arguments are provided and neither one contains an underscore, a search in local and perhaps online data sources is initiated. For each protein
–organism
pair (the arguments should be the same length), the contents of thermo$proteins
are searched for completely matching (both protein
and organism
) entries.
If no match is found in thermo$proteins
, an online search is invoked, unless online
is FALSE. (If online
is NA, i.e., the default setting in thermo$opt$online
, the user is prompted whether she or he wishes the search to be performed, and this response is stored in thermo$opt$online
.) The function attempts a search of the SWISS-Prot database (Boeckmann et al., 2003). The search string in this case is formed by joining the corresponding elements of the two arguments with an intervening underscore character to make a name such as LYSC_CHICK. If the amino acid composition of the protein is successfully retrieved by the online searche, that composition is stored in thermo$proteins
. For either local or online matches, the values returned by protein
are the row numbers of the protein composition in thermo$proteins
.
If protein
is numeric, the compositional information found in that row(s) of thermo$proteins
is combined with sidechain and backbone group contributions to generate the standard molal thermodynamic properties and equations of state parameters of the proteins at 25 degree C and 1 bar (Dick et al., 2006), and a dataframe of these values returned. The physical state of the proteins in this calculation is controlled by the value of organism
(aq or cr; NULL
defaults to aq). Note that the properties of aqueous (and crystalline) proteins calculated in this step refer to hypothetically completely nonionized proteins; the contributions by ionization to the chemical affinities of formation reactions of aqueous proteins can be calculated during execution of affinity
if the basis species contain H+ (see ionize
).
If protein
is character but organism
is NULL, the function assumes that protein
refers to the name of protein, that is searched for in thermo$proteins
; if matches are found, the selected rows are returned. If organism
looks like the name of a protein (it contains an underscore), the function assumes that protein
contains the amino acid sequence and of a new protein, and the corresponding amino acid composition is added to thermo$protein
, with the name given by organism
. This allows for entry of protein compositions at the command line.
If protein
is a data.frame
, it is taken to be representative of the compositions of one or more proteins that are summed to make a new protein. In this case, the argument organism
should contain the name of the new protein, e.g. PROTEIN_NEW.
protein.residue
generates average residue compositions of proteins. It takes the name(s) of one or more proteins (e.g. LYSC_CHICK), retrieves their amino acid compositions from thermo$protein
, and divides by the total number of amino acids in each protein.
protein.info
is a utility to tabulate some properties of proteins. A dataframe is returned containing for each protein that is among the species
of interest, the name of the protein, its length, formula, and values of the standard molal Gibbs energy of the neutral protein, net charge, standard molal Gibbs energy of the ionized protein, and nominal carbon oxidation state.
If protein
or organism
contains an underscore, a row of the protein composition dataframe. Otherwise, if protein
is numeric, a dataframe with calculated thermodynamic properties and parameters of the neutral protein, or if protein
is character, an invisible
return of numeric values (or NA for no match) representing rownumbers of thermo$protein
that were matched to protein
–organism
identifiers.
Boeckmann, B., Bairoch, A., Apweiler, R., Blatter, M.-C., Estreicher, A., Gasteiger, E., Martin, M. J., Michoud, K., Donovan, C., Phan, I., Pilbout, S. and Schneider, M., 2003. The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003. Nucleic Acids Res., 31, 365-370. http://www.expasy.org, accessed on 2007-12-19.
Dick, J. M., LaRowe, D. E. and Helgeson, H. C., 2006. Temperature, pressure and electrochemical constraints on protein speciation: Group additivity calculation of the standard molal thermodynamic properties of ionized unfolded proteins. Biogeosciences, 3, 311-336.
get.protein
for retrieving compositions of proteins in yeast and E. coli, including those identified in stress response experiments. add.protein
for adding these compositions to the dataframe that is accessed by protein
.
### Interaction with the 'protein'function ## Thermodynamic properties of proteins # get the composition of a protein protein('BPT1_BOVIN') # retrieve the rownumber of a protein in thermo$protein iprotein <- protein('LYSC','CHICK') # calculate properties and parameters from group additivity protein(iprotein) # a call to info() causes the protein properties to # be appended to thermo$obigt info('LYSC_CHICK') # the second time it is faster info('LYSC_CHICK') # thermodynamic properties can be calculated with subcrt() subcrt('LYSC_CHICK') ### Table of properties of some proteins basis('CHNOS+') species(c('LYSC_CHICK','CYC_BOVIN','MYG_HORSE','RNAS1_BOVIN')) # here, G in the Gibbs energy of a neutral protein, Z is the # charge of an ionized protein, G.Z is the Gibbs energy of the # ionized protein, and Z.C is the nominal carbon oxidation state protein.info() ## Protein Data from Online Sources ## Not run: ## marked dontrun because it requires internet # this asks to search SWISS-Prot info('PRND_HUMAN') # an online search can also be started from the # 'subcrt' function subcrt('SPRN_HUMAN') ## End(Not run) ## end dontrun ## Inputting protein compositions # make a new protein protein('GGSGG','PROTEIN_TEST') # a sequence can be pasted into the command line: # type this protein(' # then paste the sequence # and end the command by typing ','PROTEIN_NEW') # or use whatever name you want (with an underscore). ## Standard molal entropy of a protein reaction basis('CHNOS') # here we provide the reaction coefficients of the # proteins (per protein backbone); 'subcrt' function calculates # the coefficients of the basis species in the reaction t <- subcrt(c('CSG_METTL','CSG_METJA'),c(-1/558,1/530), T=seq(0,350,length.out=15)) thermo.plot.new(xlim=range(t$out$T),ylim=range(t$out$S), xlab=axis.label('T'),ylab=axis.label('DS0r')) lines(t$out$T,t$out$S) # do it at high pressure as well t <- subcrt(c('CSG_METTL','CSG_METJA'),c(-1/558,1/530), T=seq(0,350,length.out=15),P=3000) lines(t$out$T,t$out$S,lty=2) # label the plot title(main=paste('Standard molal entropy\n', 'P = Psat (solid), P = 3000 bar (dashed)')) t$reaction$coeff <- round(t$reaction$coeff,3) d <- describe(t$reaction, use.name=c(TRUE,TRUE,FALSE,FALSE,FALSE,FALSE,FALSE)) text(160,-8,c2s(s2c(d,sep='=',move.sep=TRUE),sep='\n'),cex=0.8) ### Metastability calculations ## sigma factors of E. coli as a function ## of logfO2 - logaNH3 basis('CHNOS') species(c('RPOE','RP32','RP54','RPOD'),'ECOLI') t <- affinity(NH3=c(-10,0),O2=c(-80,-75)) diagram(t,balance='PBB',cex.axis=1.5) title(main=paste('Sigma factors of E. coli\n', describe(thermo$basis[-c(3,5),]))) ## subcellular homologs of yeast glutaredoxin ## as a function of logfO2 - logaH2O basis('CHNOS') protein <- c('GLRX1','GLRX2','GLRX3','GLRX4','GLRX5') loc <- c('(C)','(M)','(N)','(N)','(M)') species(protein,'YEAST') t <- affinity(H2O=c(-10,0),O2=c(-85,-60)) diagram(t,names=paste(protein,loc),cex.axis=1.5) title(main=paste('Subcellular homologs of yeast glutaredoxin\n', describe(thermo$basis[-c(2,5),]))) ## surface-layer proteins from Methanococcus spp.: ## METVO (mesophile) ## METTL (thermophile) ## METJA (hyperthermophile) # a speciation diagram for surface layer proteins # as a function of oxygen fugacity # after Dick, 2008 # make our protein list organisms <- c("METSC","METJA","METFE","HALJP","METVO", "METBU","ACEKI","BACST","BACLI","AERSA") proteins <- c(rep("CSG",6),rep("SLAP",4)) proteins <- paste(proteins,organisms,sep="_") # set some graphical parameters lwd <- c(rep(3,6),rep(1,4)) lty <- c(1:6,1:4) # load the basis species and proteins basis("CHNOS+") species(proteins) # calculate affinities a <- affinity(O2=c(-100,-65)) # make diagram d <- diagram(a,ylim=c(-5,-1),residue=TRUE,legend.x=NULL,lwd=lwd, ylab=as.expression(quote(log~italic(a[j]))),yline=1.7) # label diagram text(-80,-1.9,"METJA") text(-74.5,-1.9,"METVO") text(-69,-1.9,"HALJP") text(-78,-2.85,"METBU",cex=0.8,srt=-22) text(-79,-3.15,"ACEKI",cex=0.8,srt=-25) text(-81,-3.3,"METSC",cex=0.8,srt=-25) text(-87,-3.1,"METFE",cex=0.8,srt=-17) text(-79,-4.3,"BACST",cex=0.8) text(-85.5,-4.7,"AERSA",cex=0.8,srt=38) text(-87,-4.25,"BACLI",cex=0.8,srt=30) # add water line abline(v=-83.1,lty=2) title(main=paste("Surface-layer proteins","After Dick, 2008",sep="\n")) ## now, show the species richness draw.diversity(d,"richness",logactmin=-4) title(main=paste("Surface-layer protein richness"))