BagPype: A Python package for the construction of atomistic, energy-weighted graphs from biomolecular structures

Atomistic, energy-weighted graphs of biomolecular structures allow for versatile and efficient modelling of their properties whilst keeping physico-chemical detail. Starting only with a priori knowledge of the spatial arrangement of individual atoms obtained from structural files available at the Protein Data Bank (PDB), we present a multi-step pipeline leading to an atomistic energy-weighted graph with individual atoms as nodes and chemical interactions as edges. Whilst most graph approaches only consider strong interactions and typically only at the residue level, an advantage of our methodology lies in the inclusion of weaker interactions, such as hydrogen bonds, electrostatics, hydrophobic interactions and π-π stacking interactions in DNA. The latter enable the study of nucleic acids and their complexes with proteins. The graphs obtained by the approach presented here can be combined with any method that uses graph theoretic or network scientific information.