core.cmap | R Documentation |
Find core positions that have the largest number of contact with neighboring residues.
core.cmap(pdbs, write.pdb = FALSE, outfile="core.pdb",
cutoff = NULL, refine = FALSE, ncore = NULL, ...)
pdbs |
an alignment data structure of class ‘pdbs’
as obtained with |
write.pdb |
logical, if TRUE core coordinate files, containing
only core positions for each iteration, are written to a location
specified by |
outfile |
character string specifying the output directory when
|
cutoff |
numeric value speciyfing the inclusion criteria for core positions. |
refine |
logical, if TRUE explore core positions determined by multiple eigenvectors. By default only the eigenvector describing the largest variation is used. |
ncore |
number of CPU cores used to do the calculation.
By default ( |
... |
arguments passed to and from functions. |
This function calculates eigenvector centrality of the weighted contact network built based on input structure data and uses it to determine the core positions.
In this context, core positions correspond to the most invariant
C-alpha atom positions across an aligned set of protein
structures. Traditionally one would use the core.find
function to for their identification and then use these positions as
the basis for improved structural superposition. This more recent
function utilizes a much faster approach and is thus preferred in
time sensitive applications such as shiny apps.
Returns a list of class "select"
containing ‘atom’ and
‘xyz’ indices.
Xin-Qiu Yao
Grant, B.J. et al. (2006) Bioinformatics 22, 2695–2696.
core.find
,
read.fasta.pdb
,
fit.xyz
## Not run:
##-- Generate a small kinesin alignment and read corresponding structures
pdbfiles <- get.pdb(c("1bg2","2ncd","1i6i","1i5s"), URLonly=TRUE)
pdbs <- pdbaln(pdbfiles)
##-- Find 'core' positions
core <- core.cmap(pdbs)
xyz <- pdbfit(pdbs, core, outpath="corefit_structures")
## End(Not run)
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