FlexPepDock

FlexPepDock: Wanna dock a peptide? Use FlexPepDock!

Interested in peptide docking? Use FlexPepDock, which is a peptide docking software implemented in Rosetta. The easiest way to do that is to use the online server:
http://flexpepdock.furmanlab.cs.huji.ac.il

If you want to run FlexPepDock locally, follow the steps below.
In my example I docked the hexapeptide NT(8-13) with the sequence RRPYIL into the neurotensin receptor. I did this prospectively, without having looked at the bound peptide conformation before doing this. All I knew was that the C-terminal carboxylate interacts with Arg327 (Barroso et al, JBC, 2000) and that the peptide adopts an extended conformation (Luca et al, PNAS, 2003).

1. Create peptide coordinates

You can generate peptide coordinates using Pymol (Build->Residue->Alanine). If you want an extended peptide, it is best to generate coordinates for poly-Ala first, and then mutate to your peptide using the mutation wizard (Wizard->Mutagenesis->Mutate to Arg->Apply).
Save molecule. Do NOT add a amine at the N-terminus and do NOT add a C-terminal carboxylate to the pymol coordinates! Important note: FlexPepDock does not change your Psi angles, so make sure that a proline is in trans if that's what you want!!

2. Create input model peptide coordinates

You need a rough input peptide model for FlexPepDock. The peptide input model should be within 5 Angstroem RMSD to the native structure. You can manually dock your peptide created above into to the receptor by switching to Editing Mode in Pymol, and dragging/rotating the peptide by holding the Shift-Button and Middle and Left-Mouse button, respectively. Don't worry about clashes of the peptide with the protein: the most important thing is that the backbone is within 5 Anstroem of the native structure.

Save the docked peptide coordinates and add them at the below of the PDB coordinates of the apo receptor structure. It is important to add them below the receptor coordinates, separated by a TER statement. Also, there should be no END statements.

3. Run prepack.sh

Run prepack.sh (see code below):

./prepack.sh NTS1_rrpyil_input.pdb

prepack.sh generates pNTS1_rrpyil_input_0001.pdb as output: the protein is protonated and a N-terminal amine and a C-terminal carboxylate have been added to the peptide.

Code of prepack.sh:

#!/bin/csh
 
#$1 is the start.pdb

set arch = `uname -p`
if ( $arch == 'x86_64') then
~londonir/rosetta/rosetta_source/bin/FlexPepDocking.static.linuxgccrelease -s $1 -database /raid1/people/londonir/rosetta/rosetta_database -native $1 -flexpep_prepack -ex1 -ex2aro -unboundrot $1 > log.prepack
else 
echo "I can only run on a x86_64 system..."
endif

4. Run FlexPepDock on Cluster using submit_fpdock.sh

Run FlexPepDock on Cluster using submit_fpdock.sh (see code below):

./submit_fpdock.sh NTS1_rrpyil_input_0001.pdb 200

submit_fpdock.sh takes two arguments: the protonated protein-peptide input model from prepack.sh (NTS1_rrpyil_input_0001.pdb) and the second argument (200) is the number of models you want to generate - 200 is a good number. submit_fpdock.sh calls a script called single_fpdock.sh (see code below), which executes the actual peptide docking. The peptide docking is pretty fast: it takes about 2 minutes per model.

Code of submit_fpdock.sh:

#!/bin/csh

#$1 is the start file (start.pdb)
#$2 is the number of jobs to send (each will attempt nstruct=1)

foreach i (`seq 1 $2`)
qsub -l arch=lx24-amd64 -q all.q -cwd -e ./error -o ./out -v arg1=$i,arg2=$1 ./single_fpdock.sh
end

Code of single_fpdock.sh:

#!/bin/csh

#arg1 is the run prefix number
#arg2 is the start.pdb (and native.pdb)

set arch = `uname -p`
if ( $arch == 'x86_64') then
~londonir/rosetta/rosetta_source/bin/FlexPepDocking.static.linuxgccrelease -s $arg2 -database /raid1/people/londonir/rosetta/rosetta_database -native $arg2 -pep_refine -ex1 -ex2aro -use_input_sc -nstruct 1 -unboundrot $arg2 -out:prefix $arg1'.' > log.$arg1
endif

5. Analyze output models

FlexPepDock outputs a pdb, a score file (.sc) and a log file (log) for each model requested. The score files is a tab-delimited file with many scores and other interesting numbers like Interface buried surface area (I_bsa), number of hydrogen bonds (I_hb), score for the Interface (I_sc) and a score for the peptide (pep_sc). Your main interest is most likely the total score (total_score).

You can print the total scores of each model using this script:

#!/bin/csh
# prints total scores for each model

foreach file (*.sc) 
  echo $file":" `awk 'NR==3 {print $2}' $file`
end