jamesmkrieger / mnxl

Validating models using restraints from crosslinking mass spectrometry

MNXL - Validate models using restraints from Crosslinking-Mass Spectrometry

 Copyright 2016 MNXL Inventor and Birkbeck College University of London.
                      The MNXL Inventor is: Josh Bullock

 MNXL is available under Public Licence.
 This software is made available under GPL V3

 Please cite your use of MNXL in published work:
 
 J.Bullock, J. Schwab, K. Thalassinos, M. Topf (2016)
 The importance of non-accessible crosslinks and solvent accessible surface distance
 in modelling proteins with restraints from crosslinking mass spectrometry. 
 Molecular and Cellular Proteomics (15) pp.2491–2500

INSTALLATION: Open a terminal session and a move to the directory MNXL is in.

type "setup.py install"

RUNNING MNXL:

type "mnxl" plus any of the below flags:

-h, --help show this help message and exit -data DATA specify experimental data: -data <input_data.txt> -mod_xl MOD_XL [MOD_XL ...] specify simulated model data: -mod_xl <model_data.txt> -jwalk flag to use if starting from .pdb files and running Jwalk -pdb PDB [PDB ...] specify input pdbs: -mod_xl <model_data.pdb>

EXPERIMENTAL DATA INPUT:

Crosslinks should be listed in a pipe-delimited .txt file as so:

res1|chain1|res2|chain2|

eg. 34|A|56|B|

If your pdb file has no chain, insert a lowercase x

eg. 34|x|56|x|

See the example file for a sample list.

MODEL DATA INPUT:

Jwalk output files (or output from any other distance calculation program) can be used as long as it is formatted as follows:

Index Model Atom1 Atom2 SASD Euclidean Distance 1 test.pdb LYS-52-A-CA LYS-129-A-CA 57.1556689427 26.1061187272 etc.

OUTPUT:

MNXL_scores.txt gives the MNXL score as well as the number of matched, violating, and non-accessible crosslinks