_ _ _ __ _
(_) | | (_)/ _| |
___ _ __ _ ___ _ __ _ _ ___| |__ _| |_| |_ _ _
/ __| '__| / __| '_ \| | | | / __| '_ \| | _| __| | | |
| (__| | | \__ \ |_) | |_| | \__ \ | | | | | | |_| |_| |
\___|_| |_|___/ .__/ \__, | |___/_| |_|_|_| \__|\__, |
| | __/ | __/ |
|_| |___/ |___/
Can be used by running the following:
import sys
sys.path.append("path-to-directory")
# now can import functions and objects, like:
from crispy_shifty.protocols.states import grow_terminal_helices
...
The apptainer in containers has been tested on Ubuntu 20.04. The apptainer can be registered as a Jupyter kernel for
running the included Jupyter notebooks, or a conda environment can be created from the included spec files in envs.
While not strictly necessary, GPUs will greatly accelerate the AlphaFold, RFdiffusion, and RFinpainting steps.
No installation is required.
The majority of notebooks and many util scripts are intended to be run on computational resources that Institute for Protein Design labs have access to. It is likely possible to modify the scripts to work on any cluster with a SLURM scheduler, and may be straightforward to do so. To run a small number of design trajectories on a normal desktop computer, individual lines from the generated tasks.cmds files can be run on the command line. Depending on the design step, run time will vary froma few minutes to a few hours.
Example notebooks for designing switches and switch-binder fusions are included in design_switch and design_fusion.
The 00_inputs folder contain example starting point PDB files for the design process. Update the paths in the
input.list files to point to the correct locations of these files on your system. Then run the first notebook to start
the first design step. After that design step has been completed and the data analyzed, move on to run the next notebook
on the outputs of the first design step. Continue this process until you have completed all design steps.