Awesome

Biobox provides a collection of data structures and methods for loading, manipulating and analyzing atomistic and pseudoatomistic structures.

Biobox main features:

• importing of PDB, PQR and GRO files, possibly containing multiple conformations (e.g. multi-PDB, gro trajectory)
• generation of coarse grain shapes composed of specific arrangements of pseudo-atoms
• loading and manipulation of density maps, including their transformation into a solid object upon isovalue definition
• assemblies of any points arrangement can be produced (i.e. densities converted in solid and geometric shapes can be equally treated).

Allowed operations on structures incude:

• generation of assemblies according to custom symmetries
• rototranslation and alignment on principal axes
• on ensembles: RMSD, RMSF, PCA and clustering
• calculation of CCS, SAXS, SASA, convex hull, s2 (for molecules), mass and volume estimation (for densities)
• atomselect for molecules and assemblies of molecules
• shortest solvent accessible path between atoms on molecule (using lazy Theta* or A*)
• density map simulation.

INSTALLATION AND REQUIREMENTS

The best way to install Biobox is via Anaconda conda install biobox -c conda-forge

Biobox can be also installed via pip pip install biobox

Biobox can otherwise be installed manually typing the followin command in the Biobox folder: python setup.py build_ext --inplace followed by python setup.py install. Please make sure the folder where Biobox is located is in your PYTHONPATH.

Biobox requires Python3.x and the following packages:

• numpy
• scipy
• pandas
• scikit-learn
• cython

Optional external software:

• CCS calculation relies on a call to IMPACT (requires definition of IMPACTPATH environment variable)
• SAXS simulations rely on a call to crysol, from ATSAS suite (requires definition of ATSASPATH environment variable)

USAGE

Documentation:

• Biobox's API is available at https://Degiacomi-Lab.github.io/biobox/

Tutorial:

• A Jupyter notebook presenting Biobox's main functionalities is available at https://github.com/Degiacomi-Lab/biobox_notebook
• The notebook can be run directly in a browser via Binder: https://mybinder.org/v2/gh/degiacom/biobox_notebook/HEAD

CITATION

When using Biobox in your work, please cite: L. S. P. Rudden, S. C. Musson, J. L. P. Benesch, M. T. Degiacomi (2021). Biobox: a toolbox for biomolecular modelling, Bioinformatics