Biomolecular Visualization with PyMOL

Usage

pymol(...)
"pymol"(pdbs, col=NULL, as="ribbon", file=NULL, type="script", exefile=NULL, ...)
"pymol"(...)
"pymol"(...)
"pymol"(modes, mode=NULL, file=NULL, scale=5, dual=FALSE, type="script", exefile=NULL, ...)
"pymol"(dccm, pdb, file=NULL, step=0.2, omit=0.2, radius = 0.15, type="script", exefile=NULL, ...)

Arguments

pdbs
aligned C-alpha Cartesian coordinates as obtained with read.fasta.pdb or pdbaln.
col
a single element character vector specifying the coloring of the structures. Options are: ‘index’, ‘index2’, ‘gaps’, ‘rmsf’. Special cases: Provide a ‘core’ object as obtained by core.find to color on the invariant core. Alternatively, provide a vector containing the color code for each structure in the ‘pdbs’ object.
as
show as ‘ribbon’, ‘cartoon’, ‘lines’, ‘putty’.
file
a single element character vector specifying the file name of the PyMOL session/script file.
type
a single element character vector specifying the output type: ‘script’ generates a .pml script; ‘session’ generates a .pse session file; ‘launch’ launches pymol.
exefile
file path to the ‘PYMOL’ program on your system (i.e. how is ‘PYMOL’ invoked). If NULL, use OS-dependent default path to the program.
modes
an object of class nma or pca as obtained from functions nma or pca.xyz.
mode
the mode number for which the vector field should be made.
scale
global scaling factor.
dual
logical, if TRUE mode vectors are also drawn in both direction.
dccm
an object of class dccm as obtained from function dccm.
pdb
an object of class pdb as obtained from function read.pdb or a numerical vector of Cartesian coordinates.
step
binning interval of cross-correlation coefficents.
omit
correlation coefficents with values (0-omit, 0+omit) will be omitted from visualization.
radius
numeric, radius of visualized correlation cylinders in PyMol. Alternatively, a matrix with the same dimesions as dccm can be provided, e.g. to draw cylinders with radii associated to the pairwise correlation value.
...
arguments passed to function pymol.modes for ‘nma’ and ‘pca’ objects.

Description

Visualize Bio3D structure objects in PyMOL

Details

These functions provides a convenient approach for the visualization of Bio3D objects in PyMOL. See examples for more details.

DCCM PyMOL visualization: This function generates a PyMOL (python) script that will draw colored lines between (anti)correlated residues. The PyMOL script file is stored in the working directory with filename “R.py”. PyMOL will only be launched (and opened) when using argument ‘type='launch'’. Alternatively a PDB file with CONECT records will be generated (when argument type='pdb').

For the PyMOL version, PyMOL CGO objects are generated - each object representing a range of correlation values (corresponding to the actual correlation values as found in the correlation matrix). E.g. the PyMOL object with name “cor_-1_-08” would display all pairs of correlations with values between -1 and -0.8.

NMA / PCA PyMOL vector field visualization: This function generates a PyMOL (python) script for drawing mode vectors on a PDB structure. The PyMOL script file is stored in the working directory with filename “R.py”.

Value

Called for its action

References

Skjaerven, L. et al. (2014) BMC Bioinformatics 15, 399. Grant, B.J. et al. (2006) Bioinformatics 22, 2695--2696.

Examples

##- pymol with a 'pdbs' object attach(transducin)
The following objects are masked from transducin (pos = 3): annotation, core, pdbs
# build a pymol session containing all structures in the PDBs object pymol(pdbs)
PyMOL script written to file R.pml
# color by invariant core ( # core <- core.find(pdbs) pymol(pdbs, col=core)
PyMOL script written to file R.pml
# color by RMSF pymol(pdbs, col="rmsf")
PyMOL script written to file R.pml
# color by clustering rd <- rmsd(pdbs$xyz)
Warning message: No indices provided, using the 305 non NA positions
hc <- hclust(as.dist(rd)) grps <- cutree(hc, k=3) pymol(pdbs, col=grps)
PyMOL script written to file R.pml
##- pymol with a 'dccm' object ## Fetch stucture pdb <- read.pdb( system.file("examples/1hel.pdb", package="bio3d") ) ## Calculate normal modes modes <- nma(pdb)
Building Hessian... Done in 0.075 seconds. Diagonalizing Hessian... Done in 0.131 seconds.
## Calculate correlation matrix cm <- dccm.nma(modes)
|======================================================================| 100%
pymol(cm, modes$xyz)
PyMOL script written to file R.py
##- pymol with a 'nma' or 'pca' object pymol(modes, mode=7)
PyMOL script written to file R.py
detach(transducin)

See also

view

Author

Lars Skjaerven