Generating Ramachandran plot and statistics.
Project description
Ramachandran
Ramachandran plot visualizes energetically allowed regions for backbone torsion (dihedral) angles ψ against φ of amino acid residues in protein structure. This Python package provides the implementations from scratch to crawling PDB/PDBx files from RCSB PDB Bank, parsing PDB/PDBx files for extracting geometric information, computing the torsion angles of residues from atom coordinates and the Ramachandran favorable regions from the reference PDB/PDBx files selected, and creating Ramachandran plots for user-provided PDB/PDBx files.
Dependencies
- Python 3.8+
- Numpy 1.20.1+
- Scipy 1.6.0+
- Matplotlib 3.3.4+
Usages
It is recommended to use Docker container to run the program.
Build Docker Image
$ docker build -f docker/ramachandran.Dockerfile --no-cache --tag=ramachandran:0.0.1 .
Run Docker Container
$ docker run -it --rm --gpus device=0 -v $(pwd):/mnt ramachandran:0.0.1
Install
$ pip install ramachandran
Create Ramachandran Plots
$ ramachandran-plot --help
usage: ramachandran-plot [-h] --file-path FILE_PATH
[--save-dir-path SAVE_DIR_PATH]
[--protein-name PROTEIN_NAME]
Ramachandran Plot Tool. Plots for GLY, PRO, pre-PRO, and Other residues will
be created.
optional arguments:
-h, --help show this help message and exit
--file-path FILE_PATH
PDB/PDBx file path. (default: None)
--save-dir-path SAVE_DIR_PATH
Directory path for saving the Ramachandran plots for
the PDB/PDBx file. (default: .)
--protein-name PROTEIN_NAME
Protein name. (default: None)
Demo
$ ramachandran_plot --file-path 1AXC.cif --save-dir-path 1AXC --protein-name 1AXC
General | GLY | PRO | Pre-PRO |
---|---|---|---|
TODO
- Filter homologous proteins for computing the Ramachandran statistics, since too many homologous protein structures will bias the statistics.
- Add the original hard-coded Ramachandran favorable region.
References
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