GPCR Model Dock Protocol Capture

KEYWORDS: DOCKING GENERAL Written in Jan 2013 by Elizabeth Nguyen (e dot dong dot nguyen at vanderbilt dot edu)

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This demo contains all the files necessary to replicate the results from the paper:

Challenges of recovering native conformations of ligands docked into comparative models of G-protein coupled receptors. Nguyen,E.D., Norn, C., Frimurer, T., and Meiler,J. (2012), PLOS One. Supplementary Material.

Commands and files are provided to be able to replicate the following steps (from Figure 1):

1. Structural alignment of GPCR templates
2. Sequence alignment of the target GPCR to templates
3. Thread target sequence onto template backbone coordinates
4. Rebuild missing density
5. Rebuild ECL 1,2 and 3
6. Evaluate comparative models by clustering by full-receptor RMSD and knowledge-based pocket residue filter
7. Generate ligand conformations in MOE
8. Dock ligand into comparative models
9. Analyze results by clustering binding modes by ligand RMSD

Files included in this protocol capture

Input files (rosetta_inputs):

1u19A_clean.pdb 
2vt4A_clean.pdb 
2rh1A_clean.pdb 
3emlA_clean.pdb 
3oduA_clean.pdb 
3pblA_clean.pdb 
3rzeA_clean.pdb 
3v2wA_clean.pdb 
3uonA_clean.pdb 
4dajA_clean.pdb 
4dklA_clean.pdb 
4djhA_clean.pdb 
4ea3A_clean.pdb 
4ej4A_clean.pdb
all_gpcrs.fasta 
1u19A.fasta
1u19A.aln
2rh1A_clean.pdb
1u19A_on_2rh1A.pdb
1u19A.jufo_ss
1u19A.psipred_ss2
1u19A.span
1u19A.disulfide
aa1u19A03_05.200_v1_3
aa1u19A09_05.200_v1_3
relax.options
1u19A_on_2rh1A_relax.pdb
ccd_initial.options
1u19A_on_2rh1A.loops
1u19A_on_2rh1A_initial.pdb
1u19A_rmsd01.pdb
1u19A.sdf
1u19A.params
1u19A_confs.pdb 
1u19A_cluster01_01.pdb
1u19A_cluster01_01_ligand.pdb
dock.options
dock.xml 
1u19A_ligand.cluster.mat

Output files (example_outputs):

1u19A_10percent_RMSD.txt
cluster3_1u19A.Centers
cluster3_1u19A.Rows 
1u19A_cluster01_01_ligand_011u19A_cluster01_01_ligand_0001.pdb
all.sdf
cluster3_1u19A_ligand.Centers
cluster3_1u19A_ligand.Rows

Scripts and applications not included in the Rosetta 3.4 release (scripts):

evaluate_score_vs_pocket_rmsd
jufo9d_span.pl
rmsd.tcsh

Command lines to run this protocol capture

• Prepare GPCR crystal structures from the Protein Data Bank.

  rosetta_tools/protein_tools/scripts/clean_pdb.py 2RH1 A > 2rh1A_clean.pdb
  

• Perform a structural alignment of GPCRs using crystal structures from the Protein Data Bank.

  mustang -p . -i 1u19A_clean.pdb 2vt4A_clean.pdb 2rh1A_clean.pdb 3emlA_clean.pdb 3oduA_clean.pdb 3pblA_clean.pdb 3rzeA_clean.pdb 3v2wA_clean.pdb 3uonA_clean.pdb 4dajA_clean.pdb 4dklA_clean.pdb 4djhA_clean.pdb 4ea3A_clean.pdb 4ej4A_clean.pdb -o all_gpcrs -F fasta -D 2.5 -s ON
  

• Sequence alignment of the target GPCR to templates

  Input target sequence 1u19A.fasta and profile alignment all_gpcrs.fasta to http://mobyle.pasteur.fr/cgi-bin/portal.py#forms::clustalO-profile. We used the default settings for this protocol.

• Thread target sequence onto template backbone coordinates

  rosetta_tools/protein_tools/scripts/thread_pdb_from_alignment.py --template=2rh1A_clean --target=1u19A --chain=A --align_format=clustal 1u19A.aln 2rh1A_clean.pdb 1u19A_on_2rh1A.pdb

• Generate secondary structure prediction, constraint file and fragments for bRh.

  • Secondary structure- Jufo9D: http://meilerlab.org/index.php/servers/show?s_id=5

  • Secondary structure- PSIPRED: http://bioinf.cs.ucl.ac.uk/psipred/

  • Transmembrane span prediction based on Jufo9D:

      perl scripts/jufo9d_span.pl 1u19A.jufo9d > 1u19A.span 
    

  • Disulfide bond constraint file: Create file that lists residue number of cysteine residues predicted to disulfide bond according to the alignment with the template.

  • Fragment files: http://www.robetta.org

• Rebuilt missing density

  rosetta_source/bin/loopmodel.linuxgccrelease @ccd_initial.options -database rosetta_database 
  

• Rebuilt ECL 1,2 and 3 with CCD

  rosetta_source/bin/loopmodel.linuxgccrelease @ccd.options -database rosetta_database 
  

• Rebuilt ECL 1,2 and 3 with KIC

  rosetta_source/bin/loopmodel.linuxgccrelease @kic.options -database rosetta_database
  

• Analyze results by clustering top ten percent of comparative models by full receptor RMSD.

  bcl.exe PDBCompare -quality RMSD -atoms CA -pdb_list 1u19A_models.ls -aaclass AACaCb -prefix 1u19A_10percent_
  bcl.exe Cluster -distance_input_file 1u19A_10percent_RMSD.txt -input_format TableLowerTriangle -output_format Rows Centers -output_file cluster3_1u19A -linkage Average -remove_internally_similar_nodes 3
  

• Analyze results by filtering comparative models with a knowledge-based filter.

  scripts/evaluate_score_vs_pocket_rmsd/01_make_distances.csh
  scripts/evaluate_score_vs_pocket_rmsd/02_filter_models.py
  

• Create ligand conformations in MOE.

  See MOE operating guide. LowModeMD with the MMFFx94 force field and Generalized Born solvation model was used to generate conformations within the specified energy cutoff. The ligand conformations were then saved as an .sdf file for conversion to .pdb and .params files for Rosetta.

    rosetta_source/src/python/apps/public/molfile_to_params.py -n 1u19A -p 1u19A 1u19A.sdf 
  

• Dock ligand into comparative models.

  rosetta_source/bin/rosettascripts.linuxgccrelease @dock.options -database rosetta_database
  

• Filter binding modes by energy, clustering and experimental restraints

  /scripts/rmsd.tcsh *.pdb
  bcl.exe ScoreSmallMolecule all.sdf output.sdf -comparison RMSD
  bcl.exe Cluster -distance_input_file 1u19A_ligand.cluster.mat -input_format TableLowerTriangle -output_format Rows Centers -output_file cluster3_1u19A_ligand -linkage Average -remove_internally_similar_nodes 3