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Simplifier of 3D structures of molecules

Project description

# KnotPull - a simplifier for 3D structures

KnotPull reduces a user provided 3D structure, to simplify it,
while preserving the topology of the chain. It has been successfully
used for knot detection in proteins and chromatine chains.

It can return either a final, simplified structure, or a .pdb formatted
trajectory of consecutive simplifications performed.

## Install
`pip install knot_pull `

(older versions) `pip install --index-url knot_pull`

If installing with `pip --user` knot_pull_check and knot_pull_show
will be installed in your user base
(`python -c "import site; print(site.USER_BASE)"`), e.g.

## Running

To run on a specific chain of a local pdb file:
knot_pull_check -o -k -c A 3ris.pdb
To run on a local xyz file (with format id<whitespace>x<whitespace>y<whitespace>z; chains separated by a line with "END"):
knot_pull_check -o from_xyz.pdb -k
To run on by structure id from RCSB PDB:
knot_pull_check -k 4mcb

To show coloured trajectory in PyMOL (if installed):
knot_pull_shown my_output_file.pdb
If PyMOL is nto available in system path it can be specified as the second argument

### Help:
usage: knot_pull_check [-h] [-p] [-t] [-f {pdb,xyz,guess}] [-k] [-c CHAIN]
[-o [OUTPUT]] [-s [SAVE]]

Simplify the 3D structure while preserving the topology

positional arguments:
infile Structure file which will be used

optional arguments:
-h, --help show this help message and exit
-p, --preserve_resnums
Keep original numbering
-t, --trajectory Write out all steps of the simplification [default is
-f {pdb,xyz,guess}, --format {pdb,xyz,guess}
Input file format: xyz or pdb [default is guess]
-k, --detect_knot Calculate the knot Dowker notation and assign the knot
-c CHAIN, --chain CHAIN
Specify which chain you want to simplify.
-o [OUTPUT], --output [OUTPUT]
Specify the output file. Format is guessed based on
extension [default pdb]. Default is stdout
-s [SAVE], --save [SAVE]
Write out a savefile. If any argument is given here -
run from a savefile (knot detection only).


### Copyright (c) Aleksandra Jarmolińska

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