BindCraft is an open-source and automated pipeline for de novo protein binder design pipeline using AlphaFold2 backpropagation, MPNN, and PyRosetta.

References:

• Martin Pacesa, Lennart Nickel, Christian Schellhaas, Joseph Schmidt, Ekaterina Pyatova, Lucas Kissling, Patrick Barendse, Jagrity Choudhury, Srajan Kapoor, Ana Alcaraz-Serna, Yehlin Cho, Kourosh H. Ghamary, Laura Vinué, Brahm J. Yachnin, Andrew M. Wollacott, Stephen Buckley, Adrie H. Westphal , Simon Lindhoud, Sandrine Georgeon, Casper A. Goverde, Georgios N. Hatzopoulos, Pierre Gönczy, Yannick D. Muller, Gerald Schwank, Daan C. Swarts, Alex J. Vecchio, Bernard L. Schneider, Sergey Ovchinnikov, Bruno E. Correia
  BindCraft: one-shot design of functional protein binders
  bioRxiv preprint doi: https://doi.org/10.1101/2024.09.30.615802

• BindCraft Github page

• Module Name: BindCraft (see the modules page for more information)
• Unusual environment variables set
  • BC_HOME  installation directory
  • BC_BIN       executable directory
  • BC_SRC       source code directory
  • BC_DATA  sample data directory

Allocate an interactive session and run the program. Sample session:

[user@biowulf]$ interactive --gres=gpu:v100x:1,lscratch:10 --mem=24g -c16
[user@cn0816 ~]$ module load bindcraft 
[+] Loading cuDNN/8.1.0.77/CUDA-11.2.2 libraries...
[+] Loading CUDA Toolkit  11.2.2  ...
[+] Loading PyRosetta 387.py3.10 on cn0816
[+] Loading bindcraft 1.5.0  ...

[user@cn0816 ~]$ cp -r $BC_SRC .
[user@cn0816 ~]$ cd BindCraft-1.5.0
[user@cn0816 ~]$ python -u ./bindcraft.py -h
vailable GPUs:
Tesla V100-SXM2-32GB1: gpu
usage: bindcraft.py [-h] --settings SETTINGS [--filters FILTERS] [--advanced ADVANCED]

Script to run BindCraft binder design.

options:
  -h, --help            show this help message and exit
  --settings SETTINGS, -s SETTINGS
                        Path to the basic settings.json file. Required.
  --filters FILTERS, -f FILTERS
                        Path to the filters.json file used to filter design. If not provided, default will be used.
  --advanced ADVANCED, -a ADVANCED
                        Path to the advanced.json file with additional design settings. If not provided, default will
                        be used.
[user@cn0816 ~]$ ./bindcraft.py \
                        --settings './settings_target/PDL1.json' \
                        --filters './settings_filters/default_filters.json' \
                        --advanced './settings_advanced/default_4stage_multimer.json'
Available GPUs:
Tesla V100-SXM2-32GB1: gpu
┌──────────────────────────────────────────────────────────────────────────────┐
│                                 PyRosetta-4                                  │
│              Created in JHU by Sergey Lyskov and PyRosetta Team              │
│              (C) Copyright Rosetta Commons Member Institutions               │
│                                                                              │
│ NOTE: USE OF PyRosetta FOR COMMERCIAL PURPOSES REQUIRE PURCHASE OF A LICENSE │
│         See LICENSE.PyRosetta.md or email license@uw.edu for details         │
└──────────────────────────────────────────────────────────────────────────────┘
PyRosetta-4 2024 [Rosetta PyRosetta4.Release.python310.linux 2024.39+release.59628fbc5bc09f1221e1642f1f8d157ce49b1410 2024-09-23T07:49:48] retrieved from: http://www.pyrosetta.org
Running binder design for target PDL1
Design settings used: default_4stage_multimer
Filtering designs based on default_filters
Starting trajectory: PDL1_l86_s981562
Stage 1: Test Logits
1 models [0] recycles 1 hard 0 soft 0.02 temp 1 loss 11.80 helix 1.90 pae 0.81 i_pae 0.80 con 4.63 i_con 4.00 plddt 0.30 ptm 0.55 i_ptm 0.11 rg 10.75
2 models [1] recycles 1 hard 0 soft 0.04 temp 1 loss 8.78 helix 1.08 pae 0.74 i_pae 0.71 con 4.38 i_con 3.74 plddt 0.40 ptm 0.56 i_ptm 0.13 rg 1.70
3 models [3] recycles 1 hard 0 soft 0.05 temp 1 loss 7.98 helix 0.77 pae 0.59 i_pae 0.59 con 3.79 i_con 3.74 plddt 0.47 ptm 0.59 i_ptm 0.21 rg 0.97
4 models [0] recycles 1 hard 0 soft 0.07 temp 1 loss 7.93 helix 0.71 pae 0.56 i_pae 0.61 con 3.47 i_con 3.91 plddt 0.52 ptm 0.57 i_ptm 0.17 rg 1.30
5 models [3] recycles 1 hard 0 soft 0.09 temp 1 loss 6.29 helix 0.71 pae 0.42 i_pae 0.48 con 2.40 i_con 3.33 plddt 0.72 ptm 0.59 i_ptm 0.23 rg 1.62
6 models [3] recycles 1 hard 0 soft 0.11 temp 1 loss 6.23 helix 0.72 pae 0.42 i_pae 0.49 con 2.20 i_con 3.45 plddt 0.75
...

[user@cn0816 ~]$ exit
salloc.exe: Relinquishing job allocation 46116226
[user@biowulf ~]$