pdbx2df 0.2.2

A python package to parse PDBx file into Pandas DataFrames.

pdbx2df

Parse a PDBx file (mmCIF file: pdb_id.cif) into a python dict with PDBx category names as keys and contents belonging to the category as the corresponding values. Each category content is parsed as a Pandas DataFrame whose columns are the attribute names.

Requirements

. Pandas (>=1.0)

Install

pip install pdbx2df

Usage examples

1. If you want to read the 3D coordinates for PDB 1vii into a Pandas DataFrame, and you have downloaded the 1vii.cif file to your current working directory ./, you can:

from pdbx2df import read_pdbx
pdbx_file = './1vii.cif'
pdbx = read_pdbx(pdbx_file, category_names=['_atom_site'])
atoms_df = pdbx['_atom_site']
# 'atoms_df' is a Pandas DataFrame containing the '_atom_site' category which has the detailed 3D coordinates for each atom.

2. If you want to read the FASTA sequence of 1vii, you can:

from pdbx2df import read_pdbx
pdbx_file = './1vii.cif'
pdbx = read_pdbx(pdbx_file, category_names=['_entity_poly'])
fasta_df = pdbx['_entity_poly']
fasta = fasta_df['pdbx_seq_one_letter_code_can'].to_list()[0]  # 1vii only has one sequence
# fasta == 'MLSDEDFKAVFGMTRSAFANLPLWKQQNLKKEKGLF'

3. You can read them simutanously:

from pdbx2df import read_pdbx
pdbx_file = './1vii.cif'
pdbx = read_pdbx(pdbx_file, category_names=['_entity_poly', '_atom_site'])
atoms_df = pdbx['_atom_site']
fasta_df = pdbx['_entity_poly']

Putting a list of category names to category_names, you will get them if they are in the PDBx file.

4. You can parse the whole file by using 'all':

from pdbx2df import read_pdbx
pdbx_file = './1vii.cif'
pdbx = read_pdbx(pdbx_file, category_names=['all'])
atoms_df = pdbx['_atom_site']
fasta_df = pdbx['_entity_poly']
# and more