Nup84 Complex

These scripts demonstrate the use of IMP, MODELLER, and PMI in the modeling of the Nup84 complex using 286 DSS/EDC chemical cross-links and an electron microscopy (EM) 2D class average.

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.

• data contains all relevant data, input structures that were generated by MODELLER or deposited in PDB, etc.

• scripts

  • nup84.isd.modeling.withXrayInterface.py the main IMP/PMI script modeling with 3 crystal interfaces

  • nup84.isd.modeling.py the main IMP/PMI script modeling with no crystal interfaces

  • nup84.topology.withXrayInterface.py constructs Nup84 subunits with 3 crystal interfaces

  • nup84.topology.py constructs Nup84 subunits with no crystal interfaces

  • nup84.merge.py script to merge output files from all runs and cluster; filter threshold on total score can be set here

  • MODELLER_scripts/Nup84 MODELLER scripts to generate comparative models of Nup84

  • MODELLER_scripts/Nup85 MODELLER scripts to generate comparative models of Nup85

  • MODELLER_scripts/Nup120 MODELLER scripts to generate comparative models of Nup120

  • MODELLER_scripts/Nup133 MODELLER scripts to generate comparative models of Nup133

  • MODELLER_scripts/Nup145C MODELLER scripts to generate comparative models of Nup145C

• scripts/output.1/pdbs The best 500 models from the modeling are accumulated in this directory, and updated as the calculation proceeds.

• scripts/output.1/rmfs The structures of the lowest temperature replica will be written here as RMF files.

• scripts/output.1/stat.n.out Log files. They contain all relevant numbers of the calculation.

• outputs For 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.

• cd scripts/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.

with 3 crystal interfaces:

• cd scripts
• python nup84.isd.modeling.withXrayInterface.py &> nup84.isd.modeling.withXrayInterface.out (on a single processor; prepend mpirun -np 4 or similar if you built IMP with MPI support)
• You can add the --test option 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:

• cd scripts
• 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):

• python nup84.merge.py
• (If you used the --test option above, use it here too.)

Finally, analyze the resulting clusters:

• python precision.py
• python accuracy_xray_interface.py
• python contact_map/make_contact_map.py

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.

Last known good IMP version:

Testable: Yes.

Parallelizeable: Yes

Publications:

• 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.