This repo includes utility scripts to generate parametrically guided beta barrel protein backbone structures.
Kim, D.E. et al. Parametrically guided design of soluble beta barrels and transmembrane nanopores using deep learning. 2024
You can clone this repo into a preferred destination directory by going to that directory and then running:
git clone https://github.com/davidekim/parametric_barrels.git
barrels.py is the main script that generates parameter defined barrel cylinders used as input for RF partial diffusion and RFJoint2 inpainting beta barrel structure refinement.
python ./barrels.py --n 6 --S 10 --nres 10
check_barrels.py is a utility script that evaluates beta barrel outputs from RF partial diffusion and RFJoint2 inpainting to determine the extent of beta barrel formation.
python ./check_barrels.py <pdblist> <cylinders dir>
PyRosetta https://www.pyrosetta.org
BBQ https://biocomp.chem.uw.edu.pl/tools/bbq
silent_tools https://github.com/bcov77/silent_tools
Contact David Kim (dekim@uw.edu) for any questions.