First, MODELLER is used to generate initial structures for the individual components in the Nup84 complex. Then, IMP is used to model these components using DSS/EDC crosslinks and the electron microscopy 2D class average for the entire Nup84 complex.
The modeling protocol will work with a default build of IMP, but for most effective sampling, IMP should be built with MPI so that replica exchange can be used.
List of files and directories:
datacontains all relevant data, input structures that were generated by MODELLER or deposited in PDB, etc.
nup84.isd.modeling.withXrayInterface.pythe main IMP/PMI script modeling with 3 crystal interfaces
nup84.isd.modeling.pythe main IMP/PMI script modeling with no crystal interfaces
nup84.topology.withXrayInterface.pyconstructs Nup84 subunits with 3 crystal interfaces
nup84.topology.pyconstructs Nup84 subunits with no crystal interfaces
nup84.merge.pyscript to merge output files from all runs and cluster; filter threshold on total score can be set here
MODELLER_scripts/Nup84MODELLER scripts to generate comparative models of Nup84
MODELLER_scripts/Nup85MODELLER scripts to generate comparative models of Nup85
MODELLER_scripts/Nup120MODELLER scripts to generate comparative models of Nup120
MODELLER_scripts/Nup133MODELLER scripts to generate comparative models of Nup133
MODELLER_scripts/Nup145CMODELLER scripts to generate comparative models of Nup145C
scripts/output.1/pdbsThe best 500 models from the modeling are accumulated in this directory, and updated as the calculation proceeds.
scripts/output.1/rmfsThe structures of the lowest temperature replica will be written here as RMF files.
scripts/output.1/stat.n.outLog files. They contain all relevant numbers of the calculation.
outputsFor reference, the models described in the Nup84 publication are deposited in this directory. For each of the two clusters discovered in the study, the cluster representative (the best scoring individual model in the cluster) is available in RMF format, together with the top five best scoring models in PDB format. An accompanying stat file contains useful statistics on the simulation, such as whether each of the crosslinks was satisfied. The localization densities, as shown in Figure 6 on the publication are also available, as Chimera session files.
Running the MODELLER scripts:
(cd Nup84 && python all_sjkim_final1.py > all_sjkim_final1.log): ScNup84N 7-488
(cd Nup84 && python all_sjkim_final2.py > all_sjkim_final2.log): ScNup84C 506-726
(cd Nup85 && python all_sjkim_final.py > all_sjkim_final.log): ScNup85 44-744
(cd Nup120 && python all_sjkim_final1.py > all_sjkim_final1.log): ScNup120 1-1037
(cd Nup133 && python all_sjkim_final1.py > all_sjkim_final1.log): ScNup133N 56-480
(cd Nup133 && python all_sjkim_final2.py > all_sjkim_final2.log): ScNup133C 490-1157
(cd Nup145C && python all_sjkim_final.py > all_sjkim_final.log): ScNup145C 126-553
- Note that the Nup133 component is studied in more detail in a separate study.
Running the IMP/PMI scripts for the Nup84 complex:
with 3 crystal interfaces:
python nup84.isd.modeling.withXrayInterface.py &> nup84.isd.modeling.withXrayInterface.out(on a single processor; prepend
mpirun -np 4or similar if you built IMP with MPI support)
- You can add the
--testoption to the command line to quickly test the script; this simply runs the sampling for fewer steps (should complete in an hour or two).
with no crystal interfaces:
python nup84.isd.modeling.py &> nup84.isd.modeling.out
Next, merge and cluster the resulting models (this script can also be used to combine results from multiple independent runs):
- (If you used the
--testoption above, use it here too.)
Finally, analyze the resulting clusters:
Author(s): Riccardo Pellarin, Elina Tjioe, and Seung Joong Kim
Date: October 6th, 2014
License: LGPL. This library is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.
- Yi Shi*, Javier Fernandez-Martinez*, Elina Tjioe*, Riccardo Pellarin*, Seung Joong Kim*, Rosemary Williams, Dina Schneidman-Duhovny, Andrej Sali, Michael P. Rout, and Brian T. Chait, Structural characterization by cross-linking reveals the detailed architecture of a coatomer-related heptameric module from the nuclear pore complex, Molecular & Cellular Proteomics, 2014, mcp.M114.041673.
*These authors contributed equally to this work as co-first authors.