This repository contains the modeling files and the analysis related to the article "Structure of Complement C3(H2O) Revealed By Quantitative Cross-Linking/Mass Spectrometry And Modeling" by Zhuo A. Chen et al. in Molecular Cell Proteomics 2016. The directory structure is the following:
c3-template c3b-template ic3-template c3-analysis c3b-analysis ic3-analysis data
The directories are organized by system, thereby
ic3 correspond to the three different states of the complement, as discussed in the article.
template directories contain the
modeling.py script, which is run simply by
on a single core and
mpirun -np 16 python modeling.py
analysis directories contain the scripts and the results of the analysis
on the actual production runs (which are available as
at Zenodo - note that two independent
runs were carried out for each state).
clustering.py is the first script that needs to be run. It produces directories with the corresponding structural cluster data. The output directory is
color_model.py assigns coded colors to a structure to finalize the image. The output file is
make_native_aligned.py aligns the cluster structures against a given X-ray structure.
plot_cross_links.py displays the box plot for the crosslinks. The output file is
rmsd.py computes the root mean square distance of the cluster structures from the cluster center. The output file is
rmsf_precision.py computes the root mean squared fluctuation of and the domain-wise precision of a cluster.
show_localization.py is a Chimera
session script to display the localization densities with the right threshold.
xl_matrix.py produces the contact map of the crosslinks; the output file is
Author(s): Riccardo Pellarin
Date: August 2016
License: CC-BY-SA-4.0. This work is freely available under the terms of the Creative Commons Attribution-ShareAlike 4.0 International License.
- Chen ZA, Pellarin R, Fischer L, Sali A, Nilges M, Barlow PN, Rappsilber J., Structure of Complement C3(H2O) Revealed By Quantitative Cross-Linking/Mass Spectrometry And Modeling, Mol Cell Proteomics, 2016, 10.1074/mcp.M115.056473.