pymissense

PyMissense creates the pathogenicity plot and modified pdb as shown in the AlphaMissense paper for custom proteins.

https://github.com/mpi-dortmund/pymissense

Science Score: 75.0%

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  • DOI references
    Found 6 DOI reference(s) in README
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    Links to: science.org, zenodo.org
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    Organization mpi-dortmund has institutional domain (www.mpi-dortmund.mpg.de)
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    Low similarity (9.7%) to scientific vocabulary

Keywords

deep-learning protein-sequences protein-structure protein-structure-prediction structural-biology uniprot
Last synced: 6 months ago · JSON representation ·

Repository

PyMissense creates the pathogenicity plot and modified pdb as shown in the AlphaMissense paper for custom proteins.

Basic Info
  • Host: GitHub
  • Owner: MPI-Dortmund
  • License: mpl-2.0
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 1.03 MB
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  • Open Issues: 3
  • Releases: 5
Topics
deep-learning protein-sequences protein-structure protein-structure-prediction structural-biology uniprot
Created over 2 years ago · Last pushed over 2 years ago
Metadata Files
Readme License Citation

README.md

DOI

pymissense

PyMissense generates the pathogenicity plot and modified pdb as shown in the AlphaMissense paper for custom proteins.

What it does

AlphaMissense allows you to identify regions in your amino acid chain that are critical for protein function. This script does two things:

  1. It generates a plot similar to Figure 3D of the AlphaMissense paper

  1. It generates a modified PDB file where the temperature factor (bfactor) is replaced by the pathogenicity predicted by AlphaMissense, allowing the effect to be visualised with Chimerax, as in Figure 3E of the paper:

How to install

pip install pymissense

How to use it

General usage is: ``` usage: pymissense[-h] [--tsv TSV] [--pdbpath PDBPATH] [--maxacid MAXACID] uniprotid outputpath

AlphaMissense plot and pdb generator

positional arguments: uniprotid UNIPROT ID outputpath Output folder

options: -h, --help show this help message and exit --tsv TSV You can provide the path to the tsv file if you want to skip the download. (default: None) --pdbpath PDBPATH If defined, it will write the pathogenicity as bfactor in that PDB. If its not defined or not existing it will instead download the alphafold predicted PDB (default: None) --maxacid MAXACID Maximum squence number to use in the plot. (default: None) ```

You can give the optional argument --pdbpath if you want to use an experimental PDB, otherwise it will download the alphafold predicted PDB instead. With --tsv you can provide the decompressed AlphaMissense database, so that pymissense does not need to download it.

For example, to reproduce Figure 3D (the middle one) and generate the PDB shown in Figure 3E do:

wget https://files.rcsb.org/download/7UPI.pdb pymissense Q9UQ13 out --maxacid 200 --pdbpath 7upi.pdb

Note that only the first 200 amino acids are shown in the plots and the pathogenicity is shown with the experimental PDB 7upi.

Contributions

This script was developed in collaboration with Tobias Raisch

Owner

  • Name: Max Planck Institute of Molecular Physiology
  • Login: MPI-Dortmund
  • Kind: organization
  • Location: Dortmund, Germany

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Wagner"
  given-names: "Thorsten"
  orcid: "https://orcid.org/0000-0002-1550-8275"
- family-names: "Raisch"
  given-names: "Tobias"
  oricid: "https://orcid.org/0000-0002-6531-3812"
title: "pymissense"
version: 1.1.0
doi: 10.5281/zenodo.8383401
date-released: 2023-09-27
url: "https://github.com/MPI-Dortmund/pymissense"

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