mktrj.pca {bio3d} | R Documentation |
Make a trajectory of atomic displacments along a given principal component.
mktrj.pca(pca = NULL, pc = 1, mag = 1, step = 0.125, file = NULL, resno = NULL, resid = NULL, ...)
pca |
a list object of class "pca" (obtained with
pca.xyz ). |
pc |
the PC number along which displacements should be made. |
mag |
a magnification factor for scaling the displacements. |
step |
the step size by which to increment along the pc . |
file |
a character vector giving the output PDB file name. |
resno |
a vector of residue numbers for the output PDB file. |
resid |
a 3-letter residue sequence for the output PDB file. |
... |
extra arguments to be passed to the function write.pdb. |
Trajectory frames are built from reconstructed Cartesian coordinates
produced by interpolating from the mean structure along a given
pc
, in increments of step
.
An optional magnification factor can be used to amplify
displacements. This involves scaling by mag
-times the standard
deviation of the conformer distribution along the given pc
(i.e. the square root of the associated eigenvalue).
Returns a numeric matrix of interpolated coordinates with a row per structure.
The molecular graphics software VMD is useful for viewing
trajectories see:
http://www.ks.uiuc.edu/Research/vmd/.
Barry Grant
Grant, B.J. et al. (2006) Bioinformatics 22, 2695–2696.
data(kinesin) # see pca.xyz for details attach(kinesin) # Ignore gap containing positions cut.seqs <- which(pdbs$id %in% c("d1n6mb_","d1ry6a_")) gaps <- gap.inspect(pdbs$ali[-cut.seqs,]) # Write PC trajectory a <- mktrj.pca(pc.xray, pc=1, file="pc1.pdb", resno = pdbs$resno[1, gaps$f.inds], resid = aa123(pdbs$ali[1, gaps$f.inds]) ) b <- mktrj.pca(pc.xray, pc=2, file="pc2.pdb", resno = pdbs$resno[1, gaps$f.inds], resid = aa123(pdbs$ali[1, gaps$f.inds]) ) c <- mktrj.pca(pc.xray, pc=3, file="pc3.pdb", resno = pdbs$resno[1, gaps$f.inds], resid = aa123(pdbs$ali[1, gaps$f.inds]) )