Protein-Ligand Interaction Profiler (PLIP)

Analyze noncovalent protein-ligand interactions in 3D structures with ease.

| Use Case | Web Server | Docker | Singularity | Python Module | Colab | |---------------------------------------------------------------------------|--------------------|--------------------|--------------------|--------------------|--------------------| | "I want to analyze my protein-ligand complex!" | :heavy_check_mark: | :heavy_check_mark: | :yellow_circle: | :x: | :heavy_check_mark: | | "I want to analyze a billion protein-ligand complexes!" | :x: | :yellow_circle: | :heavy_check_mark: | :yellow_circle: | :x: | | "I love the Linux command line and want to build a workflow around PLIP!" | :x: | :heavy_check_mark: | :heavy_check_mark: | :yellow_circle: |:x: | | "I'm a Python programmer and want to use PLIP in my project!" | :x: | :yellow_circle: | :yellow_circle: | :heavy_check_mark: | :yellow_circle: | | "I want to analyze large complexes!" | :x: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: |

Quickstart

Docker

If you have Docker installed, you can run a PLIP analysis for the structure 1vsn with the following shell command:

On Linux / MacOS:

$ docker run --rm \
    -v ${PWD}:/results \
    -w /results \
    -u $(id -u ${USER}):$(id -g ${USER}) \
    pharmai/plip:latest -i 1vsn -yv

On Windows:

$ docker run --rm \
    -v ${PWD}:/results \
    -w /results \
    -u $(id -u ${USER}):$(id -g ${USER}) \
    pharmai/plip:latest -i 1vsn -yv

Singularity

The equivalent command for our pre-built Singularity image for Linux (available under Releases) is as follows:

$ ./plip.simg -i 1vsn -yv

Singularity allows to use PLIP with ease in HPC environments. Note that you need to have Singularity installed on your base system.

Google Colab

PLIP is available as a Google Colab to be used without the need to install it locally. It can be used without constraints in terms of PDB file and protein sizes.

Usage

This README provides instructions for setup and using basic functions of PLIP. For more details, see the Documentation.

1. Install PLIP

Containerized Image (recommended)

:exclamation: We ship PLIP as pre-built containers for multiple architectures (amd64/ARM), available on the Docker Hub or as pre-built Singularity image under Releases. See the quickstart section above for usage instructions.

Dependencies

If you cannot use the containerized bundle or want to use PLIP sources, make sure you have the following requirements installed:

Python >= 3.6.9
OpenBabel >= 3.0.0 with Python bindings
PyMOL >= 2.3.0 with Python bindings (optional, for visualization only)
ImageMagick >= 7.0 (optional)

Python: If you are on a system where Python 3 is executed using python3 instead of just python, replace the python and pip commands in the following steps with python3 and pip3 accordingly.

OpenBabel: Many users have trouble setting up OpenBabel with Python bindings correctly. We therefore provide some installation help for OpenBabel below.

From Source

Open a terminal and clone this repository using

$ git clone https://github.com/pharmai/plip.git

Either set your PYTHONPATH environment variable to the root directory of your PLIP repository or run the following command in it

$ python setup.py install

Via PyPi

We deploy the PLIP package to PyPi. You can install PLIP as Python module with:

$ pip install plip

Note: Be aware that you still have to install the above mentioned dependencies and link them correctly.

2. Run PLIP

Command Line Tool

Run the plipcmd.py script inside the PLIP folder to detect, report, and visualize interactions. The following example creates a PYMOL visualization for the interactions between the inhibitor NFT and its target protein in the PDB structure 1vsn.

Note: If you have installed PLIP with python setup.py install or PyPi, you will not have to set an alias for the plip command.

# Set an alias to make your life easier and create and enter /tmp/1vsn
$ alias plip='python ~/plip/plip/plipcmd.py'
$ mkdir /tmp/1vsn && cd /tmp/1vsn
# Run PLIP for 1vsn and open the resulting visualization in PyMOL
$ plip -i 1vsn -yv
$ pymol 1VSN_NFT_A_283.pse

Python Module

In your terminal, add the PLIP repository to your PYTHONPATH variable. For our example, we also download a PDB file for testing.

$ export PYTHONPATH=~/plip:${PYTHONPATH}
$ cd /tmp && wget http://files.rcsb.org/download/1EVE.pdb
$ python

In python, import the PLIP modules, load a PDB structure and run the analysis. This small example shows how to print all numbers of residues involved in pi-stacking:

from plip.structure.preparation import PDBComplex

my_mol = PDBComplex()
my_mol.load_pdb('/tmp/1EVE.pdb') # Load the PDB file into PLIP class
print(my_mol) # Shows name of structure and ligand binding sites
my_bsid = 'E20:A:2001' # Unique binding site identifier (HetID:Chain:Position)
my_mol.analyze()
my_interactions = my_mol.interaction_sets[my_bsid] # Contains all interaction data

# Now print numbers of all residues taking part in pi-stacking
print([pistack.resnr for pistack in my_interactions.pistacking]) # Prints [84, 129]

3. Investigate the Results

PLIP offers various output formats, ranging from renderes images and PyMOL session files to human-readable text files and XML files. By default, all files are deposited in the working directory unless and output path is provided. For a full documentation of running options and output formats, please refer to the Documentation.

Versions and Branches

For production environments, you should use the latest tagged commit from the master branch or refer to the Releases page. Newer commits from the master and development branch may contain new but untested and not documented features.

Contributors

Sebastian Salentin (original author) | github.com/ssalentin
Joachim Haupt | github.com/vjhaupt
Melissa F. Adasme Mora | github.com/madasme
Alexandre Mestiashvili | github.com/mestia
Christoph Leberecht | github.com/cleberecht
Florian Kaiser | github.com/fkaiserbio
Katja Linnemann | github.com/kalinni

PLIP Web Server

Visit our PLIP Web Server on plip-tool.biotec.tu-dresden.de.

License Information

PLIP is published under the GNU GPLv2. For more information, please read the LICENSE.txt file. Using PLIP in your commercial or non-commercial project is generally possible when giving a proper reference to this project and the publication in NAR.

Citation Information

If you are using PLIP in your work, please cite

Adasme,M. et al. PLIP 2021: expanding the scope of the protein-ligand interaction profiler to DNA and RNA. Nucl. Acids Res. (05 May 2021), gkab294. doi: 10.1093/nar/gkab294

Salentin,S. et al. PLIP: fully automated protein-ligand interaction profiler. Nucl. Acids Res. (1 July 2015) 43 (W1): W443-W447. doi: 10.1093/nar/gkv315

FAQ

I try to run PLIP, but I'm getting an error message saying: ValueError: [...] is not a recognised Open Babel descriptor type

Make sure OpenBabel is correctly installed. This error can occur if the installed Python bindings don't match the OpenBabel version on your machine. We don't offer technical support for installation of third-party packages but added some installation help for OpenBabel below. Alternatively you can refer to their website.

I'm unsure on how to run PLIP and don't have much Linux experience.

You should consider running PLIP as Docker image, as we describe above.

PLIP is reporting different interactions on several runs!

Due to the non-deterministic nature on how hydrogen atoms can be added to the input structure, it cannot be guaranteed that each run returns exactly the same set of interactions. If you want to make sure to achieve consistent results, you can:

protonate the input structure once with PLIP or your tool of preference
run PLIP with --nohydro

How does PLIP handle NMR stru

Plip

Install / Use

README