This is a read-only mirror of pymolwiki.org
Difference between revisions of "Load aln"
Jump to navigation
Jump to search
(created) |
m (psico 3.3 drops needle dependency) |
||
Line 7: | Line 7: | ||
== Installation == | == Installation == | ||
− | [[load_aln]] is available from the [[psico]] package and requires [http://biopython.org/ biopython | + | [[load_aln]] is available from the [[psico]] package and requires [http://biopython.org/ biopython]. |
− | + | All dependencies are available from [https://anaconda.org Anaconda Cloud]: | |
conda install -c schrodinger pymol | conda install -c schrodinger pymol | ||
conda install -c schrodinger pymol-psico | conda install -c schrodinger pymol-psico | ||
− | |||
conda install biopython | conda install biopython | ||
Revision as of 10:13, 28 March 2018
Included in psico | |
Module | psico.importing |
---|
load_aln loads a pairwise sequence alignment file as an alignment object into PyMOL.
Installation
load_aln is available from the psico package and requires biopython.
All dependencies are available from Anaconda Cloud:
conda install -c schrodinger pymol conda install -c schrodinger pymol-psico conda install biopython
Usage
load_aln filename [, object [, mobile [, target [, mobile_id [, target_id [, format [, transform ]]]]]]]
Arguments
- filename = str: alignment file
- object = str: name of the object {default: filename prefix}
- mobile, target = str: atom selections {default: ids from alignment file}
- mobile_id, target_id = str: ids from alignment file {default: first two}
- format = str: file format, see http://biopython.org/wiki/AlignIO {default: guess from first line in file}
- transform = 0/1: superpose mobile on target (using fit) {default: 0}
Example
Alignment file (alignment.faa):
>seq1 ACDEFG----HIKLMN >seq2 ACNEYGGGGGHVRLMN
PyMOL script:
# create objects fab ACDEFGHIKLMN, m1 fab ACNEYGGGGGHVRLMN, m2 # load alignment import psico.importing load_aln alignment.faa, mobile=m1, target=m2 # show sequence viewer set seq_view
Use the alignment object to superpose with xfit:
import psico.fitting xfit m1, m2, match=alignment, cycles=100 rebuild