Protein-DNA docking example


This is a complete example of the LightDock docking protocol to model 1AZP protein-DNA complex with the use of residue restraints.

IMPORTANT Please, make sure that you have the python3 version of LightDock installed (pip3 install lightdock). We advise you to follow the basic tutorial about how to run a quick LightDock simulation

Copying the data

Create a directory and copy the sample data provided.

$ cd Desktop
$ mkdir test
$ cd test
$ wget https://raw.githubusercontent.com/lightdock/lightdock.github.io/master/tutorials/examples/1AZP/1AZP_A.pdb
$ wget https://raw.githubusercontent.com/lightdock/lightdock.github.io/master/tutorials/examples/1AZP/1AZP_B.pdb

Specifying residue restraints

LightDock is able to use information derived from either experimental information and/or bioinformatic predictions to drive the docking at several levels. This information is used in the form of residue restraints.

To do so, we first need to create a restraints.list file of the following form.

R A.GLN.27
R A.SER.30
R A.TYR.32
...
L B.DA.68
L B.DC.69
L B.DA.70
...

Where the first column will indicate whether it is a receptor R or ligand L restraint, followed by CHAIN_ID.RESIDUE_NAME.RESIDUE_NUMBER. In this case, LightDock will consider these residue restraints as ACTIVE.

By contrast, if you want to define your residue restraints as PASSIVE you should add an additional column with a P label.

R A.GLN.27 P
R A.SER.30 P
R A.TYR.32 P
...
L B.DA.68 P
L B.DC.69 P
L B.DA.70 P
...

NOTE For a detailed description of the exact implications of ACTIVE and PASSIVE restraints in LightDock, please refer to LightDock goes information-driven

For the sake of simplicity, we will use a list of residue restraints already formatted.

$ wget https://raw.githubusercontent.com/lightdock/lightdock.github.io/master/tutorials/examples/1AZP/restraints.list
$ cat restraints.list

R A.TRP.24
R A.VAL.26
R A.ARG.42

To make the calculations faster, we will only define three residues on the protein side.

Removing and adding hydrogen atoms

First of all, we need the protein partner to have the correct hydrogen atoms as parametrixed in our dna scoring function (dna scoring function is based in AMBER force-field). To do it so, we will use the software reduce which can be downloaded from GitHub.

We remove the previous hydrogens and them rebuild them according to reduce.

$ reduce -Trim 1AZP_A.pdb > 1AZP_A_noh.pdb
$ reduce -BUILD 1AZP_A_noh.pdb > 1AZP_A_h.pdb

Setup

First, we need to run the setup step. We will specify a number of 400 initial swarms and 200 glowworms and will enable flexibility.

At this step, we need to also specify the residue restraints that will bias the docking simulation.

$ lightdock_setup3.py 1AZP_A_h.pdb 1AZP_B.pdb 400 200 -anm -rst restraints.list

@> ProDy is configured: verbosity='info'
[lightdock_setup] INFO: Reading structure from 1AZP_A_h.pdb PDB file...
[lightdock_setup] INFO: 1094 atoms, 66 residues read.
[lightdock_setup] INFO: Reading structure from 1AZP_B.pdb PDB file...
[pdb] WARNING: Possible problem: [ResidueNonStandardError] Can not check non-standard residue DG.1
[pdb] WARNING: Possible problem: [ResidueNonStandardError] Can not check non-standard residue DC.2
[pdb] WARNING: Possible problem: [ResidueNonStandardError] Can not check non-standard residue DG.3
[pdb] WARNING: Possible problem: [ResidueNonStandardError] Can not check non-standard residue DA.4
[pdb] WARNING: Possible problem: [ResidueNonStandardError] Can not check non-standard residue DT.5
[pdb] WARNING: Possible problem: [ResidueNonStandardError] Can not check non-standard residue DC.6
[pdb] WARNING: Possible problem: [ResidueNonStandardError] Can not check non-standard residue DG.7
[pdb] WARNING: Possible problem: [ResidueNonStandardError] Can not check non-standard residue DC.8
[pdb] WARNING: Possible problem: [ResidueNonStandardError] Can not check non-standard residue DG.9
[pdb] WARNING: Possible problem: [ResidueNonStandardError] Can not check non-standard residue DC.10
[pdb] WARNING: Possible problem: [ResidueNonStandardError] Can not check non-standard residue DG.11
[pdb] WARNING: Possible problem: [ResidueNonStandardError] Can not check non-standard residue DA.12
[pdb] WARNING: Possible problem: [ResidueNonStandardError] Can not check non-standard residue DT.13
[pdb] WARNING: Possible problem: [ResidueNonStandardError] Can not check non-standard residue DC.14
[pdb] WARNING: Possible problem: [ResidueNonStandardError] Can not check non-standard residue DG.15
[pdb] WARNING: Possible problem: [ResidueNonStandardError] Can not check non-standard residue DC.16
[lightdock_setup] INFO: 328 atoms, 16 residues read.
[lightdock_setup] INFO: Calculating reference points for receptor 1AZP_A_h.pdb...
[lightdock_setup] INFO: Done.
[lightdock_setup] INFO: Calculating reference points for ligand 1AZP_B.pdb...
[lightdock_setup] INFO: Done.
[lightdock_setup] INFO: Saving processed structure to PDB file...
[lightdock_setup] INFO: Done.
[lightdock_setup] INFO: Saving processed structure to PDB file...
[lightdock_setup] INFO: Done.
[lightdock_setup] INFO: Calculating ANM for receptor molecule...
[lightdock_setup] INFO: 10 normal modes calculated
[lightdock_setup] INFO: Calculating ANM for ligand molecule...
[lightdock_setup] INFO: 10 normal modes calculated
[lightdock_setup] INFO: Reading restraints from restraints.list
[lightdock_setup] INFO: Number of receptor restraints is: 3 (active), 0 (passive)
[lightdock_setup] INFO: Number of ligand restraints is: 0 (active), 0 (passive)
[lightdock_setup] INFO: Calculating starting positions...
[lightdock_setup] INFO: Generated 27 positions files
[lightdock_setup] INFO: Done.
[lightdock_setup] INFO: Number of swarms is 27 after applying restraints
[lightdock_setup] INFO: Preparing environment
[lightdock_setup] INFO: Done.
[lightdock_setup] INFO: LightDock setup OK

At the moment, LightDock is not checking the structure of the nucleotides but rather the naming. This is the reason of the several warning appearing. It is safe to ignore them.

Simulation

We can run our simulation in a local machine or in a HPC cluster. For the first option, simply run the following command.

$ lightdock3.py setup.json 100 -s dna -c 8

Where the flag -c 8 indicates LightDock to use 8 available cores. For this example we will run 100 steps of the protocol and the DNA scoring function -s dna.

To run a LightDock job on a HPC cluster, a Portable Batch System (PBS) file can be generated. This PBS file defines the commands and cluster resources used for the job. A PBS file is a plain-text file that can be easily edited with any UNIX editor.

For example, create a submit_job.sh file containing:

#PBS -N LightDock-1AZP
#PBS -q medium
#PBS -l nodes=1:ppn=16
#PBS -S /bin/bash
#PBS -d ./
#PBS -e ./lightdock.err
#PBS -o ./lightdock.out

lightdock3.py setup.json 100 -s dna -c 16

This script tells the PBS queue manager to use 16 cores of a single node in a queue with name medium, with job name LigthDock-1AZP and with standard output to lightdock.out and error output redirected to lightdock.err.

To run this script you can do it as:

qsub < submit_job.sh

Analysis

Once the simulation has finished (it takes around 1-2 min per 10 steps per swarm), we need to analyze the results as:

  • (1) Generate the structures per swarm (200 glowworms per swarm in this example)
  • (2) Clusterize the predictions per swarm
  • (3) Generate the ranking files
  • (4) Filter by a percentage of satisfied restraints (this is a highly recommended step: >40% in this example)

Here there is a PBS script to do so.

#PBS -N 1AZP-anal
#PBS -q medium
#PBS -l nodes=1:ppn=8
#PBS -S /bin/bash
#PBS -d ./
#PBS -e ./analysis.err
#PBS -o ./analysis.out

### Calculate the number of swarms ###

s=`ls -d ./swarm_* | wc -l`
swarms=$((s-1))


### Create files for Ant-Thony ###

for i in $(seq 0 $swarms)
  do
    echo "cd swarm_${i}; lgd_generate_conformations.py ../1AZP_A_h.pdb ../1AZP_B_h.pdb  gso_100.out 200 > /dev/null 2> /dev/null;" >> generate_lightdock.list;
  done

for i in $(seq 0 $swarms)
  do
    echo "cd swarm_${i}; lgd_cluster_bsas.py gso_100.out > /dev/null 2> /dev/null;" >> cluster_lightdock.list;
  done


### Generate LightDock models ###

ant_thony.py -c 8 generate_lightdock.list;


### Clustering BSAS (rmsd) within swarm ###

ant_thony.py -c 8 cluster_lightdock.list;


### Generate ranking files for filtering ###

lgd_rank.py $s 100;


### Filtering models by >40% of satisfied restraints ###

lgd_filter_restraints.py --cutoff 5.0 --fnat 0.4 rank_by_scoring.list restraints.list A B > /dev/null 2> /dev/null;

NOTE You can also run the previous commands locally in a sequential way.

Once the analysis is finished, a new folder called filtered has been created, which contains any predicted structure which satisfies our 40% filtering. Inside of this directory, there is a file with the ranking of these structures by LightDock dna score (the more positive the better) rank_filtered.list.

We provide for this example a compressed folder 1AZP.tgz of the complete run.

References

For a more complete description of the algorithm as well as different tutorials, please refer to LightDock, or check the following references: