PyCoM - Protein Coevolution Database (API & Python Library)

PyCoM is a Python API and libray to the Coevolution Matrix database (PyCoMdb), containing 457,622 annotated proteins, from UniProtKB/Swiss-Prot with their coevolution matrices calculated using HH-suite3 and CCMpred.

We provide you simple tools written in Python to query, extract and visualise data for your choice of protein(s).

The code is open source and available on GitHub.

Installing is as simple as running:

pip3 install git+https://github.com/scdantu/pycom

And you are ready to run the code!

from pycom import PyCom, CoMAnalysis
import matplotlib.pyplot as plt

pyc = PyCom(remote=True)
prots = pyc.find(        # search for proteins with:
    min_length=200,      # 200-210 residues
    max_length=210,
    disease='cancer',    # that are associated with cancer
    has_substrate=True,  # have a known substrate
    page=1,
    matrix=True          # and load their coevolution matrices
)

CoMAnalysis().add_contact_predictions(prots)  # add contact predictions

plt.axis('off'); plt.title(f'Contact Map for uniprot_id={prots.uniprot_id[0]}')
plt.imshow(prots.contact_matrix[0])  # plot the contact map

print(prots.iloc[0])  # print the protein's details

Output:

uniprot_id P62070 neff 12.754 sequence_length 204 sequence MAAAGWRDGSGQEK... organism_id 9606 helix_frac 0.29902 turn_frac 0.019608 strand_frac 0.220588 has_ptm 1 has_pdb 1 has_substrate 1 matrix [[0.0, 0.268, ... contact_matrix [[0.0, 0.0, ... Name: 0, dtype: object

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Features

PyCoM breaks down into:

• PyCoMdb: A database of coevolution matrices for proteins from UniProtKB/Swiss-Prot, with 457,622 annotated proteins.

  • Available at: https://pycom.brunel.ac.uk/downloads/

• PyCoM Python Library: A Python API to query, extract and visualise coevolution matrices from PyCoMdb

  • Available at: https://github.com/scdantu/pycom

  • Guides: Getting Started

  • This library supports:

    • Querying - Search for proteins based on various criteria

    • Coevolution Matrices - Load coevolution matrices for proteins

    • Analysis - A set of tools for performing analysis on coevolution matrices Analysis Tutorial

    • PDB&AlphaFold PDB parsing/analysis - A set of tools for parsing and analysing PDB files. PDB Tutorial

• PyCoM API: A RESTful API to query, extract and visualise coevolution matrices from PyCoMdb

  • Available at: https://pycom.brunel.ac.uk/api/

  • Guide to the API

• Alignment File Repository: A repository of 370,000+ alignment files, available for download

  • Available at: https://pycom.brunel.ac.uk/alignments/

  • Tutorial: Using the Alignment Repository

If you are more interested in alignment data (rather than Protein Residue-Residue Contacts), we also provide these at: https://pycom.brunel.ac.uk/alignments/

The parameters for generating the alignment using HH-suite3 can be found in Kamisetty et al. 2013.

How to Cite

Bibik. P, Alibai. S, Pandini. A, Dantu, S.C. “PyCoM: a python API to query, extract and visualise coevolution matrices”. 2023

Authors

• Philipp Bibik*, GitHub Link - Lead Developer of Database, API, & Python Library

• Sabriyeh Alibai* - Literature Review, Use Cases, & Testing

• Alessandro Pandini* - Scientific Advisor

• Sarath Dantu* - Corresponding Author, PI

*Brunel University London, UK

Contents:

• PyCoM
• Getting Started
  • Quick guides
  • Differences
• Tutorials
  • Tutorial 1: Workflow of PyCoM
    • Setup
    • Initalise pycom objects
    • Create a query dictionary
    • Save and retrieve progress
    • Analyse search results
    • Add biological features
    • Some Statistics
    • Coevolution matrix analysis
    • Help on UniProt Controlled Vocabulary
  • Tutorial 2: Use cases
    • UniProtID
    • Sequence
    • EC and CATH
    • Disease
    • Multiple Keywords
    • Interpreting coevolution matrix
  • Tutorial 3: Analysing alignment(s)
    • Functions to download, read and transform alignment files
    • Download the alignment file
    • Read the alignment file
    • Convert the sequence to FASTA format
    • Transfrom sequence list to frequency matrix
    • Plot the Logo images
    • Matrix transformation examples
    • Some more Logo images
  • Tutorial 4: Generate images from the paper
    • Save the query to a csv file
    • Read query data from csv file
    • Supported query keywords:
    • Plot N_eff
    • Plot Sequence length distribution
    • Get columns in the dataframe
    • Add biological features to the dataframe for each protein
    • Save the progress to a csv file
  • Tutorial 5: Contact prediction and PDB comparison
    • Settings:
    • Load and display contact map from PyCom
    • Loading contact and distance matrices from PDB structure
    • Comparing Predicted Contacts to experimental structures
• Database
  • Instructions
  • Query keywords
• Documentation
  • Quick Summary
  • Class Documentation
    • PyCom class
    • Matrix analysis
• GitHub

Indices and tables

• Index