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Calculate the cross-correlation matrix from Normal Modes Analysis.
# S3 method for nma
dccm(x, nmodes = NULL, ncore = NULL, …)
an object of class nma
as obtained from
function nma
.
numerical, number of modes to consider.
number of CPU cores used to do the calculation.
ncore>1
requires package ‘parallel’ installed.
additional arguments ?
Returns a cross-correlation matrix.
This function calculates the cross-correlation matrix from Normal
Modes Analysis (NMA) obtained from nma
of a protein
structure. It returns a matrix of residue-wise cross-correlations
whose elements, Cij, may be displayed in a graphical
representation frequently termed a dynamical cross-correlation
map, or DCCM.
If Cij = 1 the fluctuations of residues i and j are completely correlated (same period and same phase), if Cij = -1 the fluctuations of residues i and j are completely anticorrelated (same period and opposite phase), and if Cij = 0 the fluctuations of i and j are not correlated.
Wynsberghe. A.W.V, Cui, Q. Structure 14, 1647--1653. Grant, B.J. et al. (2006) Bioinformatics 22, 2695--2696.
# NOT RUN {
## Fetch stucture
pdb <- read.pdb( system.file("examples/1hel.pdb", package="bio3d") )
## Calculate normal modes
modes <- nma(pdb)
## Calculate correlation matrix
cm <- dccm.nma(modes)
## Plot correlation map
plot(cm, sse = pdb, contour = FALSE, col.regions = bwr.colors(20),
at = seq(-1, 1, 0.1))
# }
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